Sanjay Saint, MD, MPH

Diagnostic error—defined as a failure to establish an accurate and timely explanation of the patient’s health problem—is an important source of patient harm.¹ Data suggest that all patients will experience at least 1 diagnostic error in their lifetime.^2-4 Not surprisingly, diagnostic errors are among the leading categories of paid malpractice claims in the United States.⁵

Despite diagnostic errors being morbid and sometimes deadly in the hospital,^6,7 little is known about how residents and learners approach diagnostic decision making. Errors in diagnosis are believed to stem from cognitive or system failures,⁸ with errors in cognition believed to occur due to rapid, reflexive thinking operating in the absence of a more analytical, deliberate process. System-based problems (eg, lack of expert availability, technology barriers, and access to data) have also been cited as contributors.⁹ However, whether and how these apply to trainees is not known.

Therefore, we conducted a focused ethnography of inpatient medicine teams (ie, attendings, residents, interns, and medical students) in 2 affiliated teaching hospitals, aiming to (a) observe the process of diagnosis by trainees and (b) identify methods to improve the diagnostic process and prevent errors.

We designed a multimethod, focused ethnographic study to examine diagnostic decision making in hospital settings.^10,11 In contrast to anthropologic ethnographies that study entire fields using open-ended questions, our study was designed to examine the process of diagnosis from the perspective of clinicians engaged in this activity.¹¹ This approach allowed us to capture diagnostic decisions and cognitive and system-based factors in a manner currently lacking in the literature.¹²

Setting and Participants

Between January 2016 and May 2016, we observed the members of four inpatient internal medicine teaching teams at 2 affiliated teaching hospitals. We purposefully selected teaching teams for observation because they are the primary model of care in academic settings and we have expertise in carrying out similar studies.^13,14 Teaching teams typically consisted of a medical attending (senior-level physician), 1 senior resident (a second- or third-year postgraduate trainee), two interns (a trainee in their first postgraduate year), and two to four  medical students. Teams were selected at random using existing schedules and followed Monday to Friday so as to permit observation of work on call and noncall days. Owing to manpower limitations, weekend and night shifts were not observed. However, overnight events were captured during morning rounds.

Most of the teams began rounds at 8:30 AM. Typically, rounds lasted for 90–120 min and concluded with a recap (ie, “running the list”) with a review of explicit plans for patients after they had been evaluated by the attending. This discussion often occurred in the team rooms, with the attending leading the discussion with the trainees.

Data Collection

A multidisciplinary team, including clinicians (eg, physicians, nurses), nonclinicians (eg, qualitative researchers, social scientists), and healthcare engineers, conducted the observations. We observed preround activities of interns and residents before arrival of the attending (7:00 AM - 8:30 AM), followed by morning rounds with the entire team, and afternoon work that included senior residents, interns, and students.

To capture multiple aspects of the diagnostic process, we collected data using field notes modeled on components of the National Academy of Science model for diagnosis (Appendix).^1,15 This model encompasses phases of the diagnostic process (eg, data gathering, integration, formulation of a working diagnosis, treatment delivery, and outcomes) and the work system (team members, organization, technology and tools, physical environment, tasks).

Focus Groups and Interviews

At the end of weekly observations, we conducted focus groups with the residents and one-on- one interviews with the attendings. Focus groups with the residents were conducted to encourage a group discussion about the diagnostic process. Separate interviews with the attendings were performed to ensure that power differentials did not influence discussions. During focus groups, we specifically asked about challenges and possible solutions to improve diagnosis. Experienced qualitative methodologists (J.F., M.H., M.Q.) used semistructured interview guides for discussions (Appendix).

Data Analysis

After aggregating and reading the data, three reviewers (V.C., S.K., S.S.) began inductive analysis by handwriting notes and initial reflective thoughts to create preliminary codes. Multiple team members then reread the original field notes and the focus group/interview data to refine the preliminary codes and develop additional codes. Next, relationships between codes were identified and used to develop key themes. Triangulation of data collected from observations and interview/focus group sessions was carried out to compare data that we surmised with data that were verbalized by the team. The developed themes were discussed as a group to ensure consistency of major findings.

Ethical and Regulatory Oversight

This study was reviewed and approved by the Institutional Review Boards at the University of Michigan Health System (HUM-00106657) and the VA Ann Arbor Healthcare System (1-2016-010040).

Four teaching teams (4 attendings, 4 senior residents, 9 interns, and 14 medical students) were observed over 33 distinct shifts and 168 hours. Observations included morning rounds (96 h), postround call days (52 h), and postround non-call days (20 h). Morning rounds lasted an average of 127 min (range: 48-232 min) and included an average of 9 patients (range: 4-16 patients).

Themes Regarding the Diagnostic Process

We identified the following 4 primary themes related to the diagnostic process in teaching hospitals: (1) diagnosis is a social phenomenon; (2) data necessary to make diagnoses are fragmented; (3) distractions undermine the diagnostic process; and (4) time pressures interfere with diagnostic decision making (Appendix Table 1).

(1) Diagnosis is a Social Phenomenon.

Team members viewed the process of diagnosis as a social exchange of facts, findings, and strategies within a defined structure. The opportunity to discuss impressions with others was valued as a means to share, test, and process assumptions.

“Rounds are the most important part of the process. That is where we make most decisions in a collective, collaborative way with the attending present. We bounce ideas off each other.” (Intern)

Typical of social processes, variations based on time of day and schedule were observed. For instance, during call days, learners gathered data and formed working diagnosis and treatment plans with minimal attending interaction. This separation of roles and responsibilities introduced a hierarchy within diagnosis as follows:

“The interns would not call me first; they would talk to the senior resident and then if the senior thought he should chat with me, then they would call. But for the most part, they gather information and come up with the plan.” (Attending).

The work system was suited to facilitate social interactions. For instance, designated rooms (with team members informally assigned to a computer) provided physical proximity of the resident to interns and medical students. In this space, numerous informal discussions between team members (eg, “What do you think about this test?” “I’m not sure what to do about this finding.” “Should I call a [consult] on this patient?”) were observed. Although proximity to each other was viewed as beneficial, dangers to the social nature of diagnosis in the form of anchoring (ie, a cognitive bias where emphasis is placed on the first piece of data)¹⁶ were also mentioned. Similarly, the paradox associated with social proof (ie, the pressure to assume conformity within a group) was also observed as disagreement between team members and attendings rarely occurred during observations.

“I mean, they’re the attending, right? It’s hard to argue with them when they want a test or something done. When I do push back, it’s rare that others will support me–so it’s usually me and the attending.” (Resident)

“I would push back if I think it’s really bad for the patient or could cause harm–but the truth is, it doesn’t happen much.” (Intern)

(2) Data Necessary to Make Diagnoses are Fragmented

Team members universally cited fragmentation in data delivery, retrieval, and processing as a barrier to diagnosis. Team members indicated that test results might not be looked at or acted upon in a timely manner, and participants pointed to the electronic medical record as a source of this challenge.

“Before I knew about [the app for Epic], I would literally sit on the computer to get all the information we would need on rounds. Its key to making decisions. We often say we will do something, only to find the test result doesn’t support it–and then we’re back to square 1.” (Intern)

Information used by teams came from myriad sources (eg, patients, family members, electronic records) and from various settings (eg, emergency department, patient rooms, discussions with consultants). Additionally, test results often appeared without warning. Thus, availability of information was poorly aligned with clinical duties.

“They (the lab) will call us when a blood culture is positive or something is off. That is very helpful but it often comes later in the day, when we’re done with rounds.” (Resident)

The work system was highlighted as a key contributor to data fragmentation. Peculiarities of our electronic medical record (EMR) and how data were collected, stored, or presented were described as “frustrating,” and “unsafe,” by team members. Correspondingly, we frequently observed interns asking for assistance for tasks such as ordering tests or finding information despite being “trained” to use the EMR.

“People have to learn how to filter, how to recognize the most important points and link data streams together in terms of causality. But we assume they know where to find that information. It’s actually a very hard thing to do, for both the house staff and me.” (Attending)

(3) Distractions Undermine the Diagnostic Process

Distractions often created cognitive difficulties. For example, ambient noise and interruptions from neighbors working on other teams were cited as barriers to diagnosis. In addition, we observed several team members using headphones to drown out ambient noise while working on the computer.

“I know I shouldn’t do it (wear headphones), but I have no other way of turning down the noise so I can concentrate.” (Intern)

Similarly, the unpredictable nature and the volume of pages often interrupted thinking about diagnosis.

“Sometimes the pager just goes off all the time and (after making sure its not an urgent issue), I will just ignore it for a bit, especially if I am in the middle of something. It would be great if I could finish my thought process knowing I would not be interrupted.” (Resident)

To mitigate this problem, 1 attending described how he would proactively seek out nurses caring for his patients to “head off” questions (eg, “I will renew the restraints and medications this morning,” and “Is there anything you need in terms of orders for this patient that I can take care of now?”) that might lead to pages. Another resident described his approach as follows:

“I make it a point to tell the nurses where I will be hanging out and where they can find me if they have any questions. I tell them to come talk to me rather than page me since that will be less distracting.” (Resident).

Most of the interns described documentation work such as writing admission and progress notes in negative terms (“an academic exercise,” “part of the billing activity”). However, in the context of interruptions, some described this as helpful.

“The most valuable part of the thinking process was writing the assessment and plan because that’s actually my schema for all problems. It literally is the only time where I can sit and collect my thoughts to formulate a diagnosis and plan.” (Intern)

(4) Time Pressures Interfere With Diagnostic Decision Making

All team members spoke about the challenge of finding time for diagnosis during the workday. Often, they had to skip learning sessions for this purpose.

“They tell us we should go to morning report or noon conference but when I’m running around trying to get things done. I hate having to choose between my education and doing what’s best for the patient–but that’s often what it comes down to.” (Intern)

When specifically asked whether setting aside dedicated time to specifically review and formulate diagnoses would be valuable, respondents were uniformly enthusiastic. Team members described attentional conflicts as being the worst when “cross covering” other teams on call days, as their patient load effectively doubled during this time. Of note, cross-covering occurred when teams were also on call—and thus took them away from important diagnostic activities such as data gathering or synthesis for patients they were admitting.

“If you were to ever design a system where errors were likely–this is how you would design it: take a team with little supervision, double their patient load, keep them busy with new challenging cases and then ask questions about patients they know little about.” (Resident)

Although diagnostic errors have been called “the next frontier for patient safety,”¹⁷ little is known about the process, barriers, and facilitators to diagnosis in teaching hospitals. In this focused ethnography conducted at 2 academic medical centers, we identified multiple cognitive and system-level challenges and potential strategies to improve diagnosis from trainees engaged in this activity. Key themes identified by those we observed included the social nature of diagnosis, fragmented information delivery, constant distractions and interruptions, and time pressures. In turn, these insights allow us to generate strategies that can be applied to improve the diagnostic process in teaching hospitals.

Our study underscores the importance of social interactions in diagnosis. In contrast, most of the interventions to prevent diagnostic errors target individual providers through practices such as metacognition and “thinking about thinking.”^18-20 These interventions are based on Daniel Kahnemann’s work on dual thought process. Type 1 thought processes are fast, subconscious, reflexive, largely intuitive, and more vulnerable to error. In contrast, Type 2 processes are slower, deliberate, analytic, and less prone to error.²¹ Although an individual’s Type 2 thought capacity is limited, a major goal of cognitive interventions is to encourage Type 2 over Type 1 thinking, an approach termed “de-biasing.”^22-24 Unfortunately, cognitive interventions testing such approaches have suffered mixed results–perhaps because of lack of focus on collective wisdom or group thinking, which may be key to diagnosis from our findings.^9,25 In this sense, morning rounds were a social gathering used to strategize and develop care plans, but with limited time to think about diagnosis.²⁶ Introduction of defined periods for individuals to engage in diagnostic activities such as de-biasing (ie, asking “what else could this be)²⁷ before or after rounds may provide an opportunity for reflection and improving diagnosis. In addition, embedding tools such as diagnosis expanders and checklists within these defined time slots^28,29 may prove to be useful in reflecting on diagnosis and preventing diagnostic errors.

An unexpected yet important finding from this study were the challenges posed by distractions and the physical environment. Potentially maladaptive workarounds to these interruptions included use of headphones; more productive strategies included updating nurses with plans to avert pages and creating a list of activities to ensure that key tasks were not forgotten.^30,31 Applying lessons from aviation, a focused effort to limit distractions during key portions of the day, might be worth considering for diagnostic safety.³² Similarly, improving the environment in which diagnosis occurs—including creating spaces that are quiet, orderly, and optimized for thinking—may be valuable.³³Our study has limitations. First, our findings are limited to direct observations; we are thus unable to comment on how unobserved aspects of care (eg, cognitive processes) might have influenced our findings. Our observations of clinical care might also have introduced a Hawthorne effect. However, because we were closely integrated with teams and conducted focus groups to corroborate our assessments, we believe that this was not the case. Second, we did not identify diagnostic errors or link processes we observed to errors. Third, our approach is limited to 2 teaching centers, thereby limiting the generalizability of findings. Relatedly, we were only able to conduct observations during weekdays; differences in weekend and night resources might affect our insights.

The cognitive and system-based barriers faced by clinicians in teaching hospitals suggest that new methods to improve diagnosis are needed. Future interventions such as defined “time-outs” for diagnosis, strategies focused on limiting distractions, and methods to improve communication between team members are novel and have parallels in other industries. As challenges to quantify diagnostic errors abound,³⁴ improving cognitive- and system-based factors via reflection through communication, concentration, and organization is necessary to improve medical decision making in academic medical centers.

Disclosures

None declared for all coauthors.

Funding

This project was supported by grant number P30HS024385 from the Agency for Healthcare Research and Quality. The funding source played no role in study design, data acquisition, analysis or decision to report these data. Dr. Chopra is supported by a career development award from the Agency of Healthcare Research and Quality (1-K08-HS022835-01). Dr. Krein is supported by a VA Health Services Research and Development Research Career Scientist Award (RCS 11-222). Dr. Singh is partially supported by Houston VA HSR&D Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality or the Department of Veterans Affairs.

Diagnostic error—defined as a failure to establish an accurate and timely explanation of the patient’s health problem—is an important source of patient harm.¹ Data suggest that all patients will experience at least 1 diagnostic error in their lifetime.^2-4 Not surprisingly, diagnostic errors are among the leading categories of paid malpractice claims in the United States.⁵

Despite diagnostic errors being morbid and sometimes deadly in the hospital,^6,7 little is known about how residents and learners approach diagnostic decision making. Errors in diagnosis are believed to stem from cognitive or system failures,⁸ with errors in cognition believed to occur due to rapid, reflexive thinking operating in the absence of a more analytical, deliberate process. System-based problems (eg, lack of expert availability, technology barriers, and access to data) have also been cited as contributors.⁹ However, whether and how these apply to trainees is not known.

Therefore, we conducted a focused ethnography of inpatient medicine teams (ie, attendings, residents, interns, and medical students) in 2 affiliated teaching hospitals, aiming to (a) observe the process of diagnosis by trainees and (b) identify methods to improve the diagnostic process and prevent errors.

We designed a multimethod, focused ethnographic study to examine diagnostic decision making in hospital settings.^10,11 In contrast to anthropologic ethnographies that study entire fields using open-ended questions, our study was designed to examine the process of diagnosis from the perspective of clinicians engaged in this activity.¹¹ This approach allowed us to capture diagnostic decisions and cognitive and system-based factors in a manner currently lacking in the literature.¹²

Setting and Participants

Between January 2016 and May 2016, we observed the members of four inpatient internal medicine teaching teams at 2 affiliated teaching hospitals. We purposefully selected teaching teams for observation because they are the primary model of care in academic settings and we have expertise in carrying out similar studies.^13,14 Teaching teams typically consisted of a medical attending (senior-level physician), 1 senior resident (a second- or third-year postgraduate trainee), two interns (a trainee in their first postgraduate year), and two to four  medical students. Teams were selected at random using existing schedules and followed Monday to Friday so as to permit observation of work on call and noncall days. Owing to manpower limitations, weekend and night shifts were not observed. However, overnight events were captured during morning rounds.

Most of the teams began rounds at 8:30 AM. Typically, rounds lasted for 90–120 min and concluded with a recap (ie, “running the list”) with a review of explicit plans for patients after they had been evaluated by the attending. This discussion often occurred in the team rooms, with the attending leading the discussion with the trainees.

Data Collection

A multidisciplinary team, including clinicians (eg, physicians, nurses), nonclinicians (eg, qualitative researchers, social scientists), and healthcare engineers, conducted the observations. We observed preround activities of interns and residents before arrival of the attending (7:00 AM - 8:30 AM), followed by morning rounds with the entire team, and afternoon work that included senior residents, interns, and students.

To capture multiple aspects of the diagnostic process, we collected data using field notes modeled on components of the National Academy of Science model for diagnosis (Appendix).^1,15 This model encompasses phases of the diagnostic process (eg, data gathering, integration, formulation of a working diagnosis, treatment delivery, and outcomes) and the work system (team members, organization, technology and tools, physical environment, tasks).

Focus Groups and Interviews

At the end of weekly observations, we conducted focus groups with the residents and one-on- one interviews with the attendings. Focus groups with the residents were conducted to encourage a group discussion about the diagnostic process. Separate interviews with the attendings were performed to ensure that power differentials did not influence discussions. During focus groups, we specifically asked about challenges and possible solutions to improve diagnosis. Experienced qualitative methodologists (J.F., M.H., M.Q.) used semistructured interview guides for discussions (Appendix).

Data Analysis

After aggregating and reading the data, three reviewers (V.C., S.K., S.S.) began inductive analysis by handwriting notes and initial reflective thoughts to create preliminary codes. Multiple team members then reread the original field notes and the focus group/interview data to refine the preliminary codes and develop additional codes. Next, relationships between codes were identified and used to develop key themes. Triangulation of data collected from observations and interview/focus group sessions was carried out to compare data that we surmised with data that were verbalized by the team. The developed themes were discussed as a group to ensure consistency of major findings.

Ethical and Regulatory Oversight

This study was reviewed and approved by the Institutional Review Boards at the University of Michigan Health System (HUM-00106657) and the VA Ann Arbor Healthcare System (1-2016-010040).

Four teaching teams (4 attendings, 4 senior residents, 9 interns, and 14 medical students) were observed over 33 distinct shifts and 168 hours. Observations included morning rounds (96 h), postround call days (52 h), and postround non-call days (20 h). Morning rounds lasted an average of 127 min (range: 48-232 min) and included an average of 9 patients (range: 4-16 patients).

Themes Regarding the Diagnostic Process

We identified the following 4 primary themes related to the diagnostic process in teaching hospitals: (1) diagnosis is a social phenomenon; (2) data necessary to make diagnoses are fragmented; (3) distractions undermine the diagnostic process; and (4) time pressures interfere with diagnostic decision making (Appendix Table 1).

(1) Diagnosis is a Social Phenomenon.

Team members viewed the process of diagnosis as a social exchange of facts, findings, and strategies within a defined structure. The opportunity to discuss impressions with others was valued as a means to share, test, and process assumptions.

“Rounds are the most important part of the process. That is where we make most decisions in a collective, collaborative way with the attending present. We bounce ideas off each other.” (Intern)

Typical of social processes, variations based on time of day and schedule were observed. For instance, during call days, learners gathered data and formed working diagnosis and treatment plans with minimal attending interaction. This separation of roles and responsibilities introduced a hierarchy within diagnosis as follows:

“The interns would not call me first; they would talk to the senior resident and then if the senior thought he should chat with me, then they would call. But for the most part, they gather information and come up with the plan.” (Attending).

The work system was suited to facilitate social interactions. For instance, designated rooms (with team members informally assigned to a computer) provided physical proximity of the resident to interns and medical students. In this space, numerous informal discussions between team members (eg, “What do you think about this test?” “I’m not sure what to do about this finding.” “Should I call a [consult] on this patient?”) were observed. Although proximity to each other was viewed as beneficial, dangers to the social nature of diagnosis in the form of anchoring (ie, a cognitive bias where emphasis is placed on the first piece of data)¹⁶ were also mentioned. Similarly, the paradox associated with social proof (ie, the pressure to assume conformity within a group) was also observed as disagreement between team members and attendings rarely occurred during observations.

“I mean, they’re the attending, right? It’s hard to argue with them when they want a test or something done. When I do push back, it’s rare that others will support me–so it’s usually me and the attending.” (Resident)

“I would push back if I think it’s really bad for the patient or could cause harm–but the truth is, it doesn’t happen much.” (Intern)

(2) Data Necessary to Make Diagnoses are Fragmented

Team members universally cited fragmentation in data delivery, retrieval, and processing as a barrier to diagnosis. Team members indicated that test results might not be looked at or acted upon in a timely manner, and participants pointed to the electronic medical record as a source of this challenge.

“Before I knew about [the app for Epic], I would literally sit on the computer to get all the information we would need on rounds. Its key to making decisions. We often say we will do something, only to find the test result doesn’t support it–and then we’re back to square 1.” (Intern)

Information used by teams came from myriad sources (eg, patients, family members, electronic records) and from various settings (eg, emergency department, patient rooms, discussions with consultants). Additionally, test results often appeared without warning. Thus, availability of information was poorly aligned with clinical duties.

“They (the lab) will call us when a blood culture is positive or something is off. That is very helpful but it often comes later in the day, when we’re done with rounds.” (Resident)

The work system was highlighted as a key contributor to data fragmentation. Peculiarities of our electronic medical record (EMR) and how data were collected, stored, or presented were described as “frustrating,” and “unsafe,” by team members. Correspondingly, we frequently observed interns asking for assistance for tasks such as ordering tests or finding information despite being “trained” to use the EMR.

“People have to learn how to filter, how to recognize the most important points and link data streams together in terms of causality. But we assume they know where to find that information. It’s actually a very hard thing to do, for both the house staff and me.” (Attending)

(3) Distractions Undermine the Diagnostic Process

Distractions often created cognitive difficulties. For example, ambient noise and interruptions from neighbors working on other teams were cited as barriers to diagnosis. In addition, we observed several team members using headphones to drown out ambient noise while working on the computer.

“I know I shouldn’t do it (wear headphones), but I have no other way of turning down the noise so I can concentrate.” (Intern)

Similarly, the unpredictable nature and the volume of pages often interrupted thinking about diagnosis.

“Sometimes the pager just goes off all the time and (after making sure its not an urgent issue), I will just ignore it for a bit, especially if I am in the middle of something. It would be great if I could finish my thought process knowing I would not be interrupted.” (Resident)

To mitigate this problem, 1 attending described how he would proactively seek out nurses caring for his patients to “head off” questions (eg, “I will renew the restraints and medications this morning,” and “Is there anything you need in terms of orders for this patient that I can take care of now?”) that might lead to pages. Another resident described his approach as follows:

“I make it a point to tell the nurses where I will be hanging out and where they can find me if they have any questions. I tell them to come talk to me rather than page me since that will be less distracting.” (Resident).

Most of the interns described documentation work such as writing admission and progress notes in negative terms (“an academic exercise,” “part of the billing activity”). However, in the context of interruptions, some described this as helpful.

“The most valuable part of the thinking process was writing the assessment and plan because that’s actually my schema for all problems. It literally is the only time where I can sit and collect my thoughts to formulate a diagnosis and plan.” (Intern)

(4) Time Pressures Interfere With Diagnostic Decision Making

All team members spoke about the challenge of finding time for diagnosis during the workday. Often, they had to skip learning sessions for this purpose.

“They tell us we should go to morning report or noon conference but when I’m running around trying to get things done. I hate having to choose between my education and doing what’s best for the patient–but that’s often what it comes down to.” (Intern)

When specifically asked whether setting aside dedicated time to specifically review and formulate diagnoses would be valuable, respondents were uniformly enthusiastic. Team members described attentional conflicts as being the worst when “cross covering” other teams on call days, as their patient load effectively doubled during this time. Of note, cross-covering occurred when teams were also on call—and thus took them away from important diagnostic activities such as data gathering or synthesis for patients they were admitting.

“If you were to ever design a system where errors were likely–this is how you would design it: take a team with little supervision, double their patient load, keep them busy with new challenging cases and then ask questions about patients they know little about.” (Resident)

Although diagnostic errors have been called “the next frontier for patient safety,”¹⁷ little is known about the process, barriers, and facilitators to diagnosis in teaching hospitals. In this focused ethnography conducted at 2 academic medical centers, we identified multiple cognitive and system-level challenges and potential strategies to improve diagnosis from trainees engaged in this activity. Key themes identified by those we observed included the social nature of diagnosis, fragmented information delivery, constant distractions and interruptions, and time pressures. In turn, these insights allow us to generate strategies that can be applied to improve the diagnostic process in teaching hospitals.

Our study underscores the importance of social interactions in diagnosis. In contrast, most of the interventions to prevent diagnostic errors target individual providers through practices such as metacognition and “thinking about thinking.”^18-20 These interventions are based on Daniel Kahnemann’s work on dual thought process. Type 1 thought processes are fast, subconscious, reflexive, largely intuitive, and more vulnerable to error. In contrast, Type 2 processes are slower, deliberate, analytic, and less prone to error.²¹ Although an individual’s Type 2 thought capacity is limited, a major goal of cognitive interventions is to encourage Type 2 over Type 1 thinking, an approach termed “de-biasing.”^22-24 Unfortunately, cognitive interventions testing such approaches have suffered mixed results–perhaps because of lack of focus on collective wisdom or group thinking, which may be key to diagnosis from our findings.^9,25 In this sense, morning rounds were a social gathering used to strategize and develop care plans, but with limited time to think about diagnosis.²⁶ Introduction of defined periods for individuals to engage in diagnostic activities such as de-biasing (ie, asking “what else could this be)²⁷ before or after rounds may provide an opportunity for reflection and improving diagnosis. In addition, embedding tools such as diagnosis expanders and checklists within these defined time slots^28,29 may prove to be useful in reflecting on diagnosis and preventing diagnostic errors.

An unexpected yet important finding from this study were the challenges posed by distractions and the physical environment. Potentially maladaptive workarounds to these interruptions included use of headphones; more productive strategies included updating nurses with plans to avert pages and creating a list of activities to ensure that key tasks were not forgotten.^30,31 Applying lessons from aviation, a focused effort to limit distractions during key portions of the day, might be worth considering for diagnostic safety.³² Similarly, improving the environment in which diagnosis occurs—including creating spaces that are quiet, orderly, and optimized for thinking—may be valuable.³³Our study has limitations. First, our findings are limited to direct observations; we are thus unable to comment on how unobserved aspects of care (eg, cognitive processes) might have influenced our findings. Our observations of clinical care might also have introduced a Hawthorne effect. However, because we were closely integrated with teams and conducted focus groups to corroborate our assessments, we believe that this was not the case. Second, we did not identify diagnostic errors or link processes we observed to errors. Third, our approach is limited to 2 teaching centers, thereby limiting the generalizability of findings. Relatedly, we were only able to conduct observations during weekdays; differences in weekend and night resources might affect our insights.

The cognitive and system-based barriers faced by clinicians in teaching hospitals suggest that new methods to improve diagnosis are needed. Future interventions such as defined “time-outs” for diagnosis, strategies focused on limiting distractions, and methods to improve communication between team members are novel and have parallels in other industries. As challenges to quantify diagnostic errors abound,³⁴ improving cognitive- and system-based factors via reflection through communication, concentration, and organization is necessary to improve medical decision making in academic medical centers.

Disclosures

None declared for all coauthors.

Funding

This project was supported by grant number P30HS024385 from the Agency for Healthcare Research and Quality. The funding source played no role in study design, data acquisition, analysis or decision to report these data. Dr. Chopra is supported by a career development award from the Agency of Healthcare Research and Quality (1-K08-HS022835-01). Dr. Krein is supported by a VA Health Services Research and Development Research Career Scientist Award (RCS 11-222). Dr. Singh is partially supported by Houston VA HSR&D Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality or the Department of Veterans Affairs.

Diagnostic error—defined as a failure to establish an accurate and timely explanation of the patient’s health problem—is an important source of patient harm.¹ Data suggest that all patients will experience at least 1 diagnostic error in their lifetime.^2-4 Not surprisingly, diagnostic errors are among the leading categories of paid malpractice claims in the United States.⁵

Despite diagnostic errors being morbid and sometimes deadly in the hospital,^6,7 little is known about how residents and learners approach diagnostic decision making. Errors in diagnosis are believed to stem from cognitive or system failures,⁸ with errors in cognition believed to occur due to rapid, reflexive thinking operating in the absence of a more analytical, deliberate process. System-based problems (eg, lack of expert availability, technology barriers, and access to data) have also been cited as contributors.⁹ However, whether and how these apply to trainees is not known.

Therefore, we conducted a focused ethnography of inpatient medicine teams (ie, attendings, residents, interns, and medical students) in 2 affiliated teaching hospitals, aiming to (a) observe the process of diagnosis by trainees and (b) identify methods to improve the diagnostic process and prevent errors.

We designed a multimethod, focused ethnographic study to examine diagnostic decision making in hospital settings.^10,11 In contrast to anthropologic ethnographies that study entire fields using open-ended questions, our study was designed to examine the process of diagnosis from the perspective of clinicians engaged in this activity.¹¹ This approach allowed us to capture diagnostic decisions and cognitive and system-based factors in a manner currently lacking in the literature.¹²

Setting and Participants

Between January 2016 and May 2016, we observed the members of four inpatient internal medicine teaching teams at 2 affiliated teaching hospitals. We purposefully selected teaching teams for observation because they are the primary model of care in academic settings and we have expertise in carrying out similar studies.^13,14 Teaching teams typically consisted of a medical attending (senior-level physician), 1 senior resident (a second- or third-year postgraduate trainee), two interns (a trainee in their first postgraduate year), and two to four  medical students. Teams were selected at random using existing schedules and followed Monday to Friday so as to permit observation of work on call and noncall days. Owing to manpower limitations, weekend and night shifts were not observed. However, overnight events were captured during morning rounds.

Most of the teams began rounds at 8:30 AM. Typically, rounds lasted for 90–120 min and concluded with a recap (ie, “running the list”) with a review of explicit plans for patients after they had been evaluated by the attending. This discussion often occurred in the team rooms, with the attending leading the discussion with the trainees.

Data Collection

A multidisciplinary team, including clinicians (eg, physicians, nurses), nonclinicians (eg, qualitative researchers, social scientists), and healthcare engineers, conducted the observations. We observed preround activities of interns and residents before arrival of the attending (7:00 AM - 8:30 AM), followed by morning rounds with the entire team, and afternoon work that included senior residents, interns, and students.

To capture multiple aspects of the diagnostic process, we collected data using field notes modeled on components of the National Academy of Science model for diagnosis (Appendix).^1,15 This model encompasses phases of the diagnostic process (eg, data gathering, integration, formulation of a working diagnosis, treatment delivery, and outcomes) and the work system (team members, organization, technology and tools, physical environment, tasks).

Focus Groups and Interviews

At the end of weekly observations, we conducted focus groups with the residents and one-on- one interviews with the attendings. Focus groups with the residents were conducted to encourage a group discussion about the diagnostic process. Separate interviews with the attendings were performed to ensure that power differentials did not influence discussions. During focus groups, we specifically asked about challenges and possible solutions to improve diagnosis. Experienced qualitative methodologists (J.F., M.H., M.Q.) used semistructured interview guides for discussions (Appendix).

Data Analysis

After aggregating and reading the data, three reviewers (V.C., S.K., S.S.) began inductive analysis by handwriting notes and initial reflective thoughts to create preliminary codes. Multiple team members then reread the original field notes and the focus group/interview data to refine the preliminary codes and develop additional codes. Next, relationships between codes were identified and used to develop key themes. Triangulation of data collected from observations and interview/focus group sessions was carried out to compare data that we surmised with data that were verbalized by the team. The developed themes were discussed as a group to ensure consistency of major findings.

Ethical and Regulatory Oversight

This study was reviewed and approved by the Institutional Review Boards at the University of Michigan Health System (HUM-00106657) and the VA Ann Arbor Healthcare System (1-2016-010040).

Four teaching teams (4 attendings, 4 senior residents, 9 interns, and 14 medical students) were observed over 33 distinct shifts and 168 hours. Observations included morning rounds (96 h), postround call days (52 h), and postround non-call days (20 h). Morning rounds lasted an average of 127 min (range: 48-232 min) and included an average of 9 patients (range: 4-16 patients).

Themes Regarding the Diagnostic Process

We identified the following 4 primary themes related to the diagnostic process in teaching hospitals: (1) diagnosis is a social phenomenon; (2) data necessary to make diagnoses are fragmented; (3) distractions undermine the diagnostic process; and (4) time pressures interfere with diagnostic decision making (Appendix Table 1).

(1) Diagnosis is a Social Phenomenon.

Team members viewed the process of diagnosis as a social exchange of facts, findings, and strategies within a defined structure. The opportunity to discuss impressions with others was valued as a means to share, test, and process assumptions.

“Rounds are the most important part of the process. That is where we make most decisions in a collective, collaborative way with the attending present. We bounce ideas off each other.” (Intern)

Typical of social processes, variations based on time of day and schedule were observed. For instance, during call days, learners gathered data and formed working diagnosis and treatment plans with minimal attending interaction. This separation of roles and responsibilities introduced a hierarchy within diagnosis as follows:

“The interns would not call me first; they would talk to the senior resident and then if the senior thought he should chat with me, then they would call. But for the most part, they gather information and come up with the plan.” (Attending).

The work system was suited to facilitate social interactions. For instance, designated rooms (with team members informally assigned to a computer) provided physical proximity of the resident to interns and medical students. In this space, numerous informal discussions between team members (eg, “What do you think about this test?” “I’m not sure what to do about this finding.” “Should I call a [consult] on this patient?”) were observed. Although proximity to each other was viewed as beneficial, dangers to the social nature of diagnosis in the form of anchoring (ie, a cognitive bias where emphasis is placed on the first piece of data)¹⁶ were also mentioned. Similarly, the paradox associated with social proof (ie, the pressure to assume conformity within a group) was also observed as disagreement between team members and attendings rarely occurred during observations.

“I mean, they’re the attending, right? It’s hard to argue with them when they want a test or something done. When I do push back, it’s rare that others will support me–so it’s usually me and the attending.” (Resident)

“I would push back if I think it’s really bad for the patient or could cause harm–but the truth is, it doesn’t happen much.” (Intern)

(2) Data Necessary to Make Diagnoses are Fragmented

Team members universally cited fragmentation in data delivery, retrieval, and processing as a barrier to diagnosis. Team members indicated that test results might not be looked at or acted upon in a timely manner, and participants pointed to the electronic medical record as a source of this challenge.

“Before I knew about [the app for Epic], I would literally sit on the computer to get all the information we would need on rounds. Its key to making decisions. We often say we will do something, only to find the test result doesn’t support it–and then we’re back to square 1.” (Intern)

Information used by teams came from myriad sources (eg, patients, family members, electronic records) and from various settings (eg, emergency department, patient rooms, discussions with consultants). Additionally, test results often appeared without warning. Thus, availability of information was poorly aligned with clinical duties.

“They (the lab) will call us when a blood culture is positive or something is off. That is very helpful but it often comes later in the day, when we’re done with rounds.” (Resident)

The work system was highlighted as a key contributor to data fragmentation. Peculiarities of our electronic medical record (EMR) and how data were collected, stored, or presented were described as “frustrating,” and “unsafe,” by team members. Correspondingly, we frequently observed interns asking for assistance for tasks such as ordering tests or finding information despite being “trained” to use the EMR.

“People have to learn how to filter, how to recognize the most important points and link data streams together in terms of causality. But we assume they know where to find that information. It’s actually a very hard thing to do, for both the house staff and me.” (Attending)

(3) Distractions Undermine the Diagnostic Process

Distractions often created cognitive difficulties. For example, ambient noise and interruptions from neighbors working on other teams were cited as barriers to diagnosis. In addition, we observed several team members using headphones to drown out ambient noise while working on the computer.

“I know I shouldn’t do it (wear headphones), but I have no other way of turning down the noise so I can concentrate.” (Intern)

Similarly, the unpredictable nature and the volume of pages often interrupted thinking about diagnosis.

“Sometimes the pager just goes off all the time and (after making sure its not an urgent issue), I will just ignore it for a bit, especially if I am in the middle of something. It would be great if I could finish my thought process knowing I would not be interrupted.” (Resident)

To mitigate this problem, 1 attending described how he would proactively seek out nurses caring for his patients to “head off” questions (eg, “I will renew the restraints and medications this morning,” and “Is there anything you need in terms of orders for this patient that I can take care of now?”) that might lead to pages. Another resident described his approach as follows:

“I make it a point to tell the nurses where I will be hanging out and where they can find me if they have any questions. I tell them to come talk to me rather than page me since that will be less distracting.” (Resident).

Most of the interns described documentation work such as writing admission and progress notes in negative terms (“an academic exercise,” “part of the billing activity”). However, in the context of interruptions, some described this as helpful.

“The most valuable part of the thinking process was writing the assessment and plan because that’s actually my schema for all problems. It literally is the only time where I can sit and collect my thoughts to formulate a diagnosis and plan.” (Intern)

(4) Time Pressures Interfere With Diagnostic Decision Making

All team members spoke about the challenge of finding time for diagnosis during the workday. Often, they had to skip learning sessions for this purpose.

“They tell us we should go to morning report or noon conference but when I’m running around trying to get things done. I hate having to choose between my education and doing what’s best for the patient–but that’s often what it comes down to.” (Intern)

When specifically asked whether setting aside dedicated time to specifically review and formulate diagnoses would be valuable, respondents were uniformly enthusiastic. Team members described attentional conflicts as being the worst when “cross covering” other teams on call days, as their patient load effectively doubled during this time. Of note, cross-covering occurred when teams were also on call—and thus took them away from important diagnostic activities such as data gathering or synthesis for patients they were admitting.

“If you were to ever design a system where errors were likely–this is how you would design it: take a team with little supervision, double their patient load, keep them busy with new challenging cases and then ask questions about patients they know little about.” (Resident)

Although diagnostic errors have been called “the next frontier for patient safety,”¹⁷ little is known about the process, barriers, and facilitators to diagnosis in teaching hospitals. In this focused ethnography conducted at 2 academic medical centers, we identified multiple cognitive and system-level challenges and potential strategies to improve diagnosis from trainees engaged in this activity. Key themes identified by those we observed included the social nature of diagnosis, fragmented information delivery, constant distractions and interruptions, and time pressures. In turn, these insights allow us to generate strategies that can be applied to improve the diagnostic process in teaching hospitals.

Our study underscores the importance of social interactions in diagnosis. In contrast, most of the interventions to prevent diagnostic errors target individual providers through practices such as metacognition and “thinking about thinking.”^18-20 These interventions are based on Daniel Kahnemann’s work on dual thought process. Type 1 thought processes are fast, subconscious, reflexive, largely intuitive, and more vulnerable to error. In contrast, Type 2 processes are slower, deliberate, analytic, and less prone to error.²¹ Although an individual’s Type 2 thought capacity is limited, a major goal of cognitive interventions is to encourage Type 2 over Type 1 thinking, an approach termed “de-biasing.”^22-24 Unfortunately, cognitive interventions testing such approaches have suffered mixed results–perhaps because of lack of focus on collective wisdom or group thinking, which may be key to diagnosis from our findings.^9,25 In this sense, morning rounds were a social gathering used to strategize and develop care plans, but with limited time to think about diagnosis.²⁶ Introduction of defined periods for individuals to engage in diagnostic activities such as de-biasing (ie, asking “what else could this be)²⁷ before or after rounds may provide an opportunity for reflection and improving diagnosis. In addition, embedding tools such as diagnosis expanders and checklists within these defined time slots^28,29 may prove to be useful in reflecting on diagnosis and preventing diagnostic errors.

An unexpected yet important finding from this study were the challenges posed by distractions and the physical environment. Potentially maladaptive workarounds to these interruptions included use of headphones; more productive strategies included updating nurses with plans to avert pages and creating a list of activities to ensure that key tasks were not forgotten.^30,31 Applying lessons from aviation, a focused effort to limit distractions during key portions of the day, might be worth considering for diagnostic safety.³² Similarly, improving the environment in which diagnosis occurs—including creating spaces that are quiet, orderly, and optimized for thinking—may be valuable.³³Our study has limitations. First, our findings are limited to direct observations; we are thus unable to comment on how unobserved aspects of care (eg, cognitive processes) might have influenced our findings. Our observations of clinical care might also have introduced a Hawthorne effect. However, because we were closely integrated with teams and conducted focus groups to corroborate our assessments, we believe that this was not the case. Second, we did not identify diagnostic errors or link processes we observed to errors. Third, our approach is limited to 2 teaching centers, thereby limiting the generalizability of findings. Relatedly, we were only able to conduct observations during weekdays; differences in weekend and night resources might affect our insights.

The cognitive and system-based barriers faced by clinicians in teaching hospitals suggest that new methods to improve diagnosis are needed. Future interventions such as defined “time-outs” for diagnosis, strategies focused on limiting distractions, and methods to improve communication between team members are novel and have parallels in other industries. As challenges to quantify diagnostic errors abound,³⁴ improving cognitive- and system-based factors via reflection through communication, concentration, and organization is necessary to improve medical decision making in academic medical centers.

Disclosures

None declared for all coauthors.

Funding

This project was supported by grant number P30HS024385 from the Agency for Healthcare Research and Quality. The funding source played no role in study design, data acquisition, analysis or decision to report these data. Dr. Chopra is supported by a career development award from the Agency of Healthcare Research and Quality (1-K08-HS022835-01). Dr. Krein is supported by a VA Health Services Research and Development Research Career Scientist Award (RCS 11-222). Dr. Singh is partially supported by Houston VA HSR&D Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413). The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality or the Department of Veterans Affairs.

Annual healthcare costs in the United States are over $3 trillion and are garnering significant national attention.¹ The United States spends approximately 2.5 times more per capita on healthcare when compared to other developed nations.² One source of unnecessary cost in healthcare is defensive medicine. Defensive medicine has been defined by Congress as occurring “when doctors order tests, procedures, or visits, or avoid certain high-risk patients or procedures, primarily (but not necessarily) because of concern about malpractice liability.”³

Though difficult to assess, in 1 study, defensive medicine was estimated to cost $45 billion annually.⁴ While general agreement exists that physicians practice defensive medicine, the extent of defensive practices and the subsequent impact on healthcare costs remain unclear. This is especially true for a group of clinicians that is rapidly increasing in number: hospitalists. Currently, there are more than 50,000 hospitalists in the United States,⁵ yet the prevalence of defensive medicine in this relatively new specialty is unknown. Inpatient care is complex and time constraints can impede establishing an optimal therapeutic relationship with the patient, potentially raising liability fears. We therefore sought to quantify hospitalist physician estimates of the cost of defensive medicine and assess correlates of their estimates. As being sued might spur defensive behaviors, we also assessed how many hospitalists reported being sued and whether this was associated with their estimates of defensive medicine.

Survey Questionnaire

In a previously published survey-based analysis, we reported on physician practice and overuse for 2 common scenarios in hospital medicine: preoperative evaluation and management of uncomplicated syncope.⁶ After responding to the vignettes, each physician was asked to provide demographic and employment information and malpractice history. In addition, they were asked the following: In your best estimation, what percentage of healthcare-related resources (eg, hospital admissions, diagnostic testing, treatment) are spent purely because of defensive medicine concerns? __________% resources

Survey Sample & Administration

The survey was sent to a sample of 1753 hospitalists, randomly identified through the Society of Hospital Medicine’s (SHM) database of members and annual meeting attendees. It is estimated that almost 30% of practicing hospitalists in the United States are members of the SHM.⁵ A full description of the sampling methodology was previously published.⁶ Selected hospitalists were mailed surveys, a $20 financial incentive, and subsequent reminders between June and October 2011.

The study was exempted from institutional review board review by the University of Michigan and the VA Ann Arbor Healthcare System.

Variables

The primary outcome of interest was the response to the “% resources” estimated to be spent on defensive medicine. This was analyzed as a continuous variable. Independent variables included the following: VA employment, malpractice insurance payer, employer, history of malpractice lawsuit, sex, race, and years practicing as a physician.

Statistical Analysis

Analyses were conducted using SAS, version 9.4 (SAS Institute). Descriptive statistics were first calculated for all variables. Next, bivariable comparisons between the outcome variables and other variables of interest were performed. Multivariable comparisons were made using linear regression for the outcome of estimated resources spent on defensive medicine. A P value of < 0.05 was considered statistically significant.

Of the 1753 surveys mailed, 253 were excluded due to incorrect addresses or because the recipients were not practicing hospitalists. A total of 1020 were completed and returned, yielding a 68% response rate (1020 out of 1500 eligible). The hospitalist respondents were in practice for an average of 11 years (range 1-40 years). Respondents represented all 50 states and had a diverse background of experience and demographic characteristics, which has been previously described.⁶

Resources Estimated Spent on Defensive Medicine

Hospitalists reported, on average, that they believed defensive medicine accounted for 37.5% (standard deviation, 20.2%) of all healthcare spending. Results from the multivariable regression are presented in the Table. Hospitalists affiliated with a VA hospital reported 5.5% less in resources spent on defensive medicine than those not affiliated with a VA hospital (32.2% VA vs 37.7% non-VA, P = 0.025). For every 10 years in practice, the estimate of resources spent on defensive medicine decreased by 3% (P = 0.003). Those who were male (36.4% male vs 39.4% female, P = 0.023) and non-Hispanic white (32.5% non-Hispanic white vs 44.7% other, P ≤ 0.001) also estimated less resources spent on defensive medicine. We did not find an association between a hospitalist reporting being sued and their perception of resources spent on defensive medicine.  

Risk of Being Sued

Over a quarter of our sample (25.6%) reported having been sued at least once for medical malpractice. The proportion of hospitalists that reported a history of being sued generally increased with more years of practice (Figure). For those who had been in practice for at least 20 years, more than half (55%) had been sued at least once during their career.

In a national survey, hospitalists estimated that almost 40% of all healthcare-related resources are spent purely because of defensive medicine concerns. This estimate was affected by personal demographic and employment factors. Our second major finding is that over one-quarter of a large random sample of hospitalist physicians reported being sued for malpractice.

Hospitalist perceptions of defensive medicine varied significantly based on employment at a VA hospital, with VA-affiliated hospitalists reporting less estimated spending on defensive medicine. This effect may reflect a less litigious environment within the VA, even though physicians practicing within the VA can be reported to the National Practitioner Data Bank.⁷ The different environment may be due to the VA’s patient mix (VA patients tend to be poorer, older, sicker, and have more mental illness)⁸; however, it could also be due to its de facto practice of a form of enterprise liability, in which, by law, the VA assumes responsibility for negligence, sheltering its physicians from direct liability.

We also found that the higher the number of years a hospitalist reported practicing, the lower the perception of resources being spent on defensive medicine. The reason for this finding is unclear. There has been a recent focus on high-value care and overspending, and perhaps younger hospitalists are more aware of these initiatives and thus have higher estimates. Additionally, non-Hispanic white male respondents estimated a lower amount spent on defensive medicine compared with other respondents. This is consistent with previous studies of risk perception which have noted a “white male effect” in which white males generally perceive a wide range of risks to be lower than female and non-white individuals, likely due to sociopolitical factors.⁹ Here, the white male effect is particularly interesting, considering that male physicians are almost 2.5 times as likely as female physicians to report being sued.¹⁰

Similar to prior studies,¹¹ there was no association with personal liability claim experience and perceived resources spent on defensive medicine. It is unclear why personal experience of being sued does not appear to be associated with perceptions of defensive medicine practice. It is possible that the fear of being sued is worse than the actual experience or that physicians believe that lawsuits are either random events or inevitable and, as a result, do not change their practice patterns.

The lifetime risk of being named in a malpractice suit is substantial for hospitalists: in our study, over half of hospitalists in practice for 20 years or more reported they had been sued. This corresponds with the projection made by Jena and colleagues,¹² which estimated that 55% of internal medicine physicians will be sued by the age of 45, a number just slightly higher than the average for all physicians.

Our study has important limitations. Our sample was of hospitalists and therefore may not be reflective of other medical specialties. Second, due to the nature of the study design, the responses to spending on defensive medicine may not represent actual practice. Third, we did not confirm details such as place of employment or history of lawsuit, and this may be subject to recall bias. However, physicians are unlikely to forget having been sued. Finally, this survey is observational and cross-sectional. Our data imply association rather than causation. Without longitudinal data, it is impossible to know if years of practice correlate with perceived defensive medicine spending due to a generational effect or a longitudinal effect (such as more confidence in diagnostic skills with more years of practice).

Despite these limitations, our survey has important policy implications. First, we found that defensive medicine is perceived by hospitalists to be costly. Although physicians likely overestimated the cost (37.5%, or an estimated $1 trillion is far higher than previous estimates of approximately 2% of all healthcare spending),⁴ it also demonstrates the extent to which physicians feel as though the medical care that is provided may be unnecessary. Second, at least a quarter of hospitalist physicians have been sued, and the risk of being named as a defendant in a lawsuit increases the longer they have been in clinical practice.

Given these findings, policies aimed to reduce the practice of defensive medicine may help the rising costs of healthcare. Reducing defensive medicine requires decreasing physician fears of liability and related reporting. Traditional tort reforms (with the exception of damage caps) have not been proven to do this. And damage caps can be inequitable, hard to pass, and even found to be unconstitutional in some states.¹³ However, other reform options hold promise in reducing liability fears, including enterprise liability, safe harbor legislation, and health courts.¹³ Finally, shared decision-making models may also provide a method to reduce defensive fears as well.⁶

Acknowledgments

The authors thank the Society of Hospital Medicine, Dr. Scott Flanders, Andrew Hickner, and David Ratz for their assistance with this project.

Disclosure

The authors received financial support from the Blue Cross Blue Shield of Michigan Foundation, the Department of Veterans Affairs Health Services Research and Development Center for Clinical Management Research, the University of Michigan Specialist-Hospitalist Allied Research Program, and the Ann Arbor University of Michigan VA Patient Safety Enhancement Program.

Disclaimer

The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of Blue Cross Blue Shield of Michigan Foundation, the Department of Veterans Affairs, or the Society of Hospital Medicine.

Annual healthcare costs in the United States are over $3 trillion and are garnering significant national attention.¹ The United States spends approximately 2.5 times more per capita on healthcare when compared to other developed nations.² One source of unnecessary cost in healthcare is defensive medicine. Defensive medicine has been defined by Congress as occurring “when doctors order tests, procedures, or visits, or avoid certain high-risk patients or procedures, primarily (but not necessarily) because of concern about malpractice liability.”³

Though difficult to assess, in 1 study, defensive medicine was estimated to cost $45 billion annually.⁴ While general agreement exists that physicians practice defensive medicine, the extent of defensive practices and the subsequent impact on healthcare costs remain unclear. This is especially true for a group of clinicians that is rapidly increasing in number: hospitalists. Currently, there are more than 50,000 hospitalists in the United States,⁵ yet the prevalence of defensive medicine in this relatively new specialty is unknown. Inpatient care is complex and time constraints can impede establishing an optimal therapeutic relationship with the patient, potentially raising liability fears. We therefore sought to quantify hospitalist physician estimates of the cost of defensive medicine and assess correlates of their estimates. As being sued might spur defensive behaviors, we also assessed how many hospitalists reported being sued and whether this was associated with their estimates of defensive medicine.

Survey Questionnaire

In a previously published survey-based analysis, we reported on physician practice and overuse for 2 common scenarios in hospital medicine: preoperative evaluation and management of uncomplicated syncope.⁶ After responding to the vignettes, each physician was asked to provide demographic and employment information and malpractice history. In addition, they were asked the following: In your best estimation, what percentage of healthcare-related resources (eg, hospital admissions, diagnostic testing, treatment) are spent purely because of defensive medicine concerns? __________% resources

Survey Sample & Administration

The survey was sent to a sample of 1753 hospitalists, randomly identified through the Society of Hospital Medicine’s (SHM) database of members and annual meeting attendees. It is estimated that almost 30% of practicing hospitalists in the United States are members of the SHM.⁵ A full description of the sampling methodology was previously published.⁶ Selected hospitalists were mailed surveys, a $20 financial incentive, and subsequent reminders between June and October 2011.

The study was exempted from institutional review board review by the University of Michigan and the VA Ann Arbor Healthcare System.

Variables

The primary outcome of interest was the response to the “% resources” estimated to be spent on defensive medicine. This was analyzed as a continuous variable. Independent variables included the following: VA employment, malpractice insurance payer, employer, history of malpractice lawsuit, sex, race, and years practicing as a physician.

Statistical Analysis

Analyses were conducted using SAS, version 9.4 (SAS Institute). Descriptive statistics were first calculated for all variables. Next, bivariable comparisons between the outcome variables and other variables of interest were performed. Multivariable comparisons were made using linear regression for the outcome of estimated resources spent on defensive medicine. A P value of < 0.05 was considered statistically significant.

Of the 1753 surveys mailed, 253 were excluded due to incorrect addresses or because the recipients were not practicing hospitalists. A total of 1020 were completed and returned, yielding a 68% response rate (1020 out of 1500 eligible). The hospitalist respondents were in practice for an average of 11 years (range 1-40 years). Respondents represented all 50 states and had a diverse background of experience and demographic characteristics, which has been previously described.⁶

Resources Estimated Spent on Defensive Medicine

Hospitalists reported, on average, that they believed defensive medicine accounted for 37.5% (standard deviation, 20.2%) of all healthcare spending. Results from the multivariable regression are presented in the Table. Hospitalists affiliated with a VA hospital reported 5.5% less in resources spent on defensive medicine than those not affiliated with a VA hospital (32.2% VA vs 37.7% non-VA, P = 0.025). For every 10 years in practice, the estimate of resources spent on defensive medicine decreased by 3% (P = 0.003). Those who were male (36.4% male vs 39.4% female, P = 0.023) and non-Hispanic white (32.5% non-Hispanic white vs 44.7% other, P ≤ 0.001) also estimated less resources spent on defensive medicine. We did not find an association between a hospitalist reporting being sued and their perception of resources spent on defensive medicine.  

Risk of Being Sued

Over a quarter of our sample (25.6%) reported having been sued at least once for medical malpractice. The proportion of hospitalists that reported a history of being sued generally increased with more years of practice (Figure). For those who had been in practice for at least 20 years, more than half (55%) had been sued at least once during their career.

In a national survey, hospitalists estimated that almost 40% of all healthcare-related resources are spent purely because of defensive medicine concerns. This estimate was affected by personal demographic and employment factors. Our second major finding is that over one-quarter of a large random sample of hospitalist physicians reported being sued for malpractice.

Hospitalist perceptions of defensive medicine varied significantly based on employment at a VA hospital, with VA-affiliated hospitalists reporting less estimated spending on defensive medicine. This effect may reflect a less litigious environment within the VA, even though physicians practicing within the VA can be reported to the National Practitioner Data Bank.⁷ The different environment may be due to the VA’s patient mix (VA patients tend to be poorer, older, sicker, and have more mental illness)⁸; however, it could also be due to its de facto practice of a form of enterprise liability, in which, by law, the VA assumes responsibility for negligence, sheltering its physicians from direct liability.

We also found that the higher the number of years a hospitalist reported practicing, the lower the perception of resources being spent on defensive medicine. The reason for this finding is unclear. There has been a recent focus on high-value care and overspending, and perhaps younger hospitalists are more aware of these initiatives and thus have higher estimates. Additionally, non-Hispanic white male respondents estimated a lower amount spent on defensive medicine compared with other respondents. This is consistent with previous studies of risk perception which have noted a “white male effect” in which white males generally perceive a wide range of risks to be lower than female and non-white individuals, likely due to sociopolitical factors.⁹ Here, the white male effect is particularly interesting, considering that male physicians are almost 2.5 times as likely as female physicians to report being sued.¹⁰

Similar to prior studies,¹¹ there was no association with personal liability claim experience and perceived resources spent on defensive medicine. It is unclear why personal experience of being sued does not appear to be associated with perceptions of defensive medicine practice. It is possible that the fear of being sued is worse than the actual experience or that physicians believe that lawsuits are either random events or inevitable and, as a result, do not change their practice patterns.

The lifetime risk of being named in a malpractice suit is substantial for hospitalists: in our study, over half of hospitalists in practice for 20 years or more reported they had been sued. This corresponds with the projection made by Jena and colleagues,¹² which estimated that 55% of internal medicine physicians will be sued by the age of 45, a number just slightly higher than the average for all physicians.

Our study has important limitations. Our sample was of hospitalists and therefore may not be reflective of other medical specialties. Second, due to the nature of the study design, the responses to spending on defensive medicine may not represent actual practice. Third, we did not confirm details such as place of employment or history of lawsuit, and this may be subject to recall bias. However, physicians are unlikely to forget having been sued. Finally, this survey is observational and cross-sectional. Our data imply association rather than causation. Without longitudinal data, it is impossible to know if years of practice correlate with perceived defensive medicine spending due to a generational effect or a longitudinal effect (such as more confidence in diagnostic skills with more years of practice).

Despite these limitations, our survey has important policy implications. First, we found that defensive medicine is perceived by hospitalists to be costly. Although physicians likely overestimated the cost (37.5%, or an estimated $1 trillion is far higher than previous estimates of approximately 2% of all healthcare spending),⁴ it also demonstrates the extent to which physicians feel as though the medical care that is provided may be unnecessary. Second, at least a quarter of hospitalist physicians have been sued, and the risk of being named as a defendant in a lawsuit increases the longer they have been in clinical practice.

Given these findings, policies aimed to reduce the practice of defensive medicine may help the rising costs of healthcare. Reducing defensive medicine requires decreasing physician fears of liability and related reporting. Traditional tort reforms (with the exception of damage caps) have not been proven to do this. And damage caps can be inequitable, hard to pass, and even found to be unconstitutional in some states.¹³ However, other reform options hold promise in reducing liability fears, including enterprise liability, safe harbor legislation, and health courts.¹³ Finally, shared decision-making models may also provide a method to reduce defensive fears as well.⁶

Acknowledgments

The authors thank the Society of Hospital Medicine, Dr. Scott Flanders, Andrew Hickner, and David Ratz for their assistance with this project.

Disclosure

The authors received financial support from the Blue Cross Blue Shield of Michigan Foundation, the Department of Veterans Affairs Health Services Research and Development Center for Clinical Management Research, the University of Michigan Specialist-Hospitalist Allied Research Program, and the Ann Arbor University of Michigan VA Patient Safety Enhancement Program.

Disclaimer

The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of Blue Cross Blue Shield of Michigan Foundation, the Department of Veterans Affairs, or the Society of Hospital Medicine.

Annual healthcare costs in the United States are over $3 trillion and are garnering significant national attention.¹ The United States spends approximately 2.5 times more per capita on healthcare when compared to other developed nations.² One source of unnecessary cost in healthcare is defensive medicine. Defensive medicine has been defined by Congress as occurring “when doctors order tests, procedures, or visits, or avoid certain high-risk patients or procedures, primarily (but not necessarily) because of concern about malpractice liability.”³

Though difficult to assess, in 1 study, defensive medicine was estimated to cost $45 billion annually.⁴ While general agreement exists that physicians practice defensive medicine, the extent of defensive practices and the subsequent impact on healthcare costs remain unclear. This is especially true for a group of clinicians that is rapidly increasing in number: hospitalists. Currently, there are more than 50,000 hospitalists in the United States,⁵ yet the prevalence of defensive medicine in this relatively new specialty is unknown. Inpatient care is complex and time constraints can impede establishing an optimal therapeutic relationship with the patient, potentially raising liability fears. We therefore sought to quantify hospitalist physician estimates of the cost of defensive medicine and assess correlates of their estimates. As being sued might spur defensive behaviors, we also assessed how many hospitalists reported being sued and whether this was associated with their estimates of defensive medicine.

Survey Questionnaire

In a previously published survey-based analysis, we reported on physician practice and overuse for 2 common scenarios in hospital medicine: preoperative evaluation and management of uncomplicated syncope.⁶ After responding to the vignettes, each physician was asked to provide demographic and employment information and malpractice history. In addition, they were asked the following: In your best estimation, what percentage of healthcare-related resources (eg, hospital admissions, diagnostic testing, treatment) are spent purely because of defensive medicine concerns? __________% resources

Survey Sample & Administration

The survey was sent to a sample of 1753 hospitalists, randomly identified through the Society of Hospital Medicine’s (SHM) database of members and annual meeting attendees. It is estimated that almost 30% of practicing hospitalists in the United States are members of the SHM.⁵ A full description of the sampling methodology was previously published.⁶ Selected hospitalists were mailed surveys, a $20 financial incentive, and subsequent reminders between June and October 2011.

The study was exempted from institutional review board review by the University of Michigan and the VA Ann Arbor Healthcare System.

Variables

The primary outcome of interest was the response to the “% resources” estimated to be spent on defensive medicine. This was analyzed as a continuous variable. Independent variables included the following: VA employment, malpractice insurance payer, employer, history of malpractice lawsuit, sex, race, and years practicing as a physician.

Statistical Analysis

Analyses were conducted using SAS, version 9.4 (SAS Institute). Descriptive statistics were first calculated for all variables. Next, bivariable comparisons between the outcome variables and other variables of interest were performed. Multivariable comparisons were made using linear regression for the outcome of estimated resources spent on defensive medicine. A P value of < 0.05 was considered statistically significant.

Of the 1753 surveys mailed, 253 were excluded due to incorrect addresses or because the recipients were not practicing hospitalists. A total of 1020 were completed and returned, yielding a 68% response rate (1020 out of 1500 eligible). The hospitalist respondents were in practice for an average of 11 years (range 1-40 years). Respondents represented all 50 states and had a diverse background of experience and demographic characteristics, which has been previously described.⁶

Resources Estimated Spent on Defensive Medicine

Hospitalists reported, on average, that they believed defensive medicine accounted for 37.5% (standard deviation, 20.2%) of all healthcare spending. Results from the multivariable regression are presented in the Table. Hospitalists affiliated with a VA hospital reported 5.5% less in resources spent on defensive medicine than those not affiliated with a VA hospital (32.2% VA vs 37.7% non-VA, P = 0.025). For every 10 years in practice, the estimate of resources spent on defensive medicine decreased by 3% (P = 0.003). Those who were male (36.4% male vs 39.4% female, P = 0.023) and non-Hispanic white (32.5% non-Hispanic white vs 44.7% other, P ≤ 0.001) also estimated less resources spent on defensive medicine. We did not find an association between a hospitalist reporting being sued and their perception of resources spent on defensive medicine.  

Risk of Being Sued

Over a quarter of our sample (25.6%) reported having been sued at least once for medical malpractice. The proportion of hospitalists that reported a history of being sued generally increased with more years of practice (Figure). For those who had been in practice for at least 20 years, more than half (55%) had been sued at least once during their career.

In a national survey, hospitalists estimated that almost 40% of all healthcare-related resources are spent purely because of defensive medicine concerns. This estimate was affected by personal demographic and employment factors. Our second major finding is that over one-quarter of a large random sample of hospitalist physicians reported being sued for malpractice.

Hospitalist perceptions of defensive medicine varied significantly based on employment at a VA hospital, with VA-affiliated hospitalists reporting less estimated spending on defensive medicine. This effect may reflect a less litigious environment within the VA, even though physicians practicing within the VA can be reported to the National Practitioner Data Bank.⁷ The different environment may be due to the VA’s patient mix (VA patients tend to be poorer, older, sicker, and have more mental illness)⁸; however, it could also be due to its de facto practice of a form of enterprise liability, in which, by law, the VA assumes responsibility for negligence, sheltering its physicians from direct liability.

We also found that the higher the number of years a hospitalist reported practicing, the lower the perception of resources being spent on defensive medicine. The reason for this finding is unclear. There has been a recent focus on high-value care and overspending, and perhaps younger hospitalists are more aware of these initiatives and thus have higher estimates. Additionally, non-Hispanic white male respondents estimated a lower amount spent on defensive medicine compared with other respondents. This is consistent with previous studies of risk perception which have noted a “white male effect” in which white males generally perceive a wide range of risks to be lower than female and non-white individuals, likely due to sociopolitical factors.⁹ Here, the white male effect is particularly interesting, considering that male physicians are almost 2.5 times as likely as female physicians to report being sued.¹⁰

Similar to prior studies,¹¹ there was no association with personal liability claim experience and perceived resources spent on defensive medicine. It is unclear why personal experience of being sued does not appear to be associated with perceptions of defensive medicine practice. It is possible that the fear of being sued is worse than the actual experience or that physicians believe that lawsuits are either random events or inevitable and, as a result, do not change their practice patterns.

The lifetime risk of being named in a malpractice suit is substantial for hospitalists: in our study, over half of hospitalists in practice for 20 years or more reported they had been sued. This corresponds with the projection made by Jena and colleagues,¹² which estimated that 55% of internal medicine physicians will be sued by the age of 45, a number just slightly higher than the average for all physicians.

Our study has important limitations. Our sample was of hospitalists and therefore may not be reflective of other medical specialties. Second, due to the nature of the study design, the responses to spending on defensive medicine may not represent actual practice. Third, we did not confirm details such as place of employment or history of lawsuit, and this may be subject to recall bias. However, physicians are unlikely to forget having been sued. Finally, this survey is observational and cross-sectional. Our data imply association rather than causation. Without longitudinal data, it is impossible to know if years of practice correlate with perceived defensive medicine spending due to a generational effect or a longitudinal effect (such as more confidence in diagnostic skills with more years of practice).

Despite these limitations, our survey has important policy implications. First, we found that defensive medicine is perceived by hospitalists to be costly. Although physicians likely overestimated the cost (37.5%, or an estimated $1 trillion is far higher than previous estimates of approximately 2% of all healthcare spending),⁴ it also demonstrates the extent to which physicians feel as though the medical care that is provided may be unnecessary. Second, at least a quarter of hospitalist physicians have been sued, and the risk of being named as a defendant in a lawsuit increases the longer they have been in clinical practice.

Given these findings, policies aimed to reduce the practice of defensive medicine may help the rising costs of healthcare. Reducing defensive medicine requires decreasing physician fears of liability and related reporting. Traditional tort reforms (with the exception of damage caps) have not been proven to do this. And damage caps can be inequitable, hard to pass, and even found to be unconstitutional in some states.¹³ However, other reform options hold promise in reducing liability fears, including enterprise liability, safe harbor legislation, and health courts.¹³ Finally, shared decision-making models may also provide a method to reduce defensive fears as well.⁶

Acknowledgments

The authors thank the Society of Hospital Medicine, Dr. Scott Flanders, Andrew Hickner, and David Ratz for their assistance with this project.

Disclosure

The authors received financial support from the Blue Cross Blue Shield of Michigan Foundation, the Department of Veterans Affairs Health Services Research and Development Center for Clinical Management Research, the University of Michigan Specialist-Hospitalist Allied Research Program, and the Ann Arbor University of Michigan VA Patient Safety Enhancement Program.

Disclaimer

The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of Blue Cross Blue Shield of Michigan Foundation, the Department of Veterans Affairs, or the Society of Hospital Medicine.

Approximately a century ago, Francis Peabody taught that “the secret of the care of the patient is in caring for the patient.”¹ His advice remains true today. Despite the advent of novel diagnostic tests, technologically sophisticated interventional procedures, and life-saving medications, perhaps the most important skill a bedside clinician can use is the ability to connect with patients.

The literature on patient-physician interaction is vast^2-11 and generally indicates that exemplary bedside clinicians are able to interact well with patients by being competent, trustworthy, personable, empathetic, and effective communicators. “Etiquette-based medicine,” first proposed by Kahn,¹² emphasizes the importance of certain behaviors from physicians, such as introducing yourself and explaining your role, shaking hands, sitting down when speaking to patients, and asking open-ended questions.

Yet, improving patient-physician interactions remains necessary. A recent systematic review reported that almost half of the reviewed studies on the patient-physician relationship published between 2000 and 2014 conveyed the idea that the patient-physician relationship is deteriorating.¹³

As part of a broader study to understand the behaviors and approaches of exemplary inpatient attending physicians,^14-16 we examined how 12 carefully selected physicians interacted with their patients during inpatient teaching rounds.

Overview

We conducted a multisite study using an exploratory, qualitative approach to inquiry, which has been described previously.^14-16 Our primary purpose was to study the attributes and behaviors of outstanding general medicine attendings in the setting of inpatient rounds. The focus of this article is on the attendings’ interactions with patients.

We used a modified snowball sampling approach¹⁷ to identify 12 exemplary physicians. First, we contacted individuals throughout the United States who were known to the principal investigator (S.S.) and asked for suggestions of excellent clinician educators (also referred to as attendings) for potential inclusion in the study. In addition to these personal contacts, other individuals unknown to the investigative team were contacted and asked to provide suggestions for attendings to include in the study. Specifically, the US News & World Report 2015 Top Medical Schools: Research Rankings,¹⁸ which are widely used to represent the best U.S. hospitals, were reviewed in an effort to identify attendings from a broad range of medical schools. Using this list, we identified other medical schools that were in the top 25 and were not already represented. We contacted the division chiefs of general internal (or hospital) medicine, chairs and chiefs of departments of internal medicine, and internal medicine residency program directors from these medical schools and asked for recommendations of attendings from both within and outside their institutions whom they considered to be great inpatient teachers.

This sampling method resulted in 59 potential participants. An internet search was conducted on each potential participant to obtain further information about the individuals and their institutions. Both personal characteristics (medical education, training, and educational awards) and organizational characteristics (geographic location, hospital size and affiliation, and patient population) were considered so that a variety of organizations and backgrounds were represented. Through this process, the list was narrowed to 16 attendings who were contacted to participate in the study, of which 12 agreed. The number of attendings examined was appropriate because saturation of metathemes can occur in as little as 6 interviews, and data saturation occurs at 12 interviews.¹⁹ The participants were asked to provide a list of their current learners (ie, residents and medical students) and 6 to 10 former learners to contact for interviews and focus groups.

Data Collection

Observations

Two researchers conducted the one-day site visits. One was a physician (S.S.) and the other a medical anthropologist (M.H.), and both have extensive experience in qualitative methods. The only exception was the site visit at the principal investigator’s own institution, which was conducted by the medical anthropologist and a nonpracticing physician who was unknown to the participants. The team structure varied slightly among different institutions but in general was composed of 1 attending, 1 senior medical resident, 1 to 2 interns, and approximately 2 medical students. Each site visit began with observing the attendings (n = 12) and current learners (n = 57) on morning rounds, which included their interactions with patients. These observations lasted approximately 2 to 3 hours. The observers took handwritten field notes, paying particular attention to group interactions, teaching approaches, and patient interactions. The observers stood outside the medical team circle and remained silent during rounds so as to be unobtrusive to the teams’ discussions. The observers discussed and compared their notes after each site visit.

Interviews and Focus Groups

The research team also conducted individual, semistructured interviews with the attendings (n = 12), focus groups with their current teams (n = 46), and interviews or focus groups with their former learners (n = 26). Current learners were asked open-ended questions about their roles on the teams, their opinions of the attendings, and the care the attendings provide to their patients. Because they were observed during rounds, the researchers asked for clarification about specific interactions observed during the teaching rounds. Depending on availability and location, former learners either participated in in-person focus groups or interviews on the day of the site visit, or in a later telephone interview. All interviews and focus groups were audio recorded and transcribed.

This study was deemed to be exempt from regulation by the University of Michigan Institutional Review Board. All participants were informed that their participation was completely voluntary and that they could refuse to answer any question.

Data Analysis

Data were analyzed using a thematic analysis approach,²⁰ which involves reading through the data to identify patterns (and create codes) that relate to behaviors, experiences, meanings, and activities. The patterns are then grouped into themes to help further explain the findings.²¹ The research team members (S.S. and M.H.) met after the first site visit and developed initial ideas about meanings and possible patterns. One team member (M.H.) read all the transcripts from the site visit and, based on the data, developed a codebook to be used for this study. This process was repeated after every site visit, and the coding definitions were refined as necessary. All transcripts were reviewed to apply any new codes when they developed. NVivo^® 10 software (QSR International, Melbourne, Australia) was used to assist with the qualitative data analysis.

To ensure consistency and identify relationships between codes, code reports listing all the data linked to a specific code were generated after all the field notes and transcripts were coded. Once verified, codes were grouped based on similarities and relationships into prominent themes related to physician-patient interactions by 2 team members (S.S. and M.H.), though all members reviewed them and concurred.

Care for the Patient’s Well-Being

The attendings we observed appeared to openly care for their patients’ well-being and were focused on the patients’ wants and needs. We noted that attendings were generally very attentive to the patients’ comfort. For example, we observed one attending sending the senior resident to find the patient’s nurse in order to obtain additional pain medications. The attending said to the patient several times, “I’m sorry you’re in so much pain.” When the team was leaving, she asked the intern to stay with the patient until the medications had been administered.

Consideration of the “Big Picture”

Our exemplary attendings kept the “big picture” (that is, the patient’s overall medical and social needs) in clear focus. They behaved in a way to ensure that the patients understood the key points of their care and explained so the patients and families could understand. A current learner said, “[The attending] really makes sure that the patient understands what’s going on. And she always asks them, ‘What do you understand, what do you know, how can we fill in any blanks?’ And that makes the patient really involved in their own care, which I think is important.” This reflection was supported by direct observations. Attendings posed the following questions at the conclusion of patient interactions: “Tell me what you know.” “Tell me what our plan is.” “What did the lung doctors tell you yesterday?” These questions, which have been termed “teach-back” and are crucial for health literacy, were not meant to quiz the patient but rather to ensure the patient and family understood the plan.

We noticed that the attendings effectively explained clinical details and the plan of care to the patient while avoiding medical jargon. The following is an example of one interaction with a patient: “You threw up and created a tear in the food tube. Air got from that into the middle of the chest, not into the lungs. Air isn’t normally there. If it is just air, the body will reabsorb [it]... But we worry about bacteria getting in with the air. We need to figure out if it is an infection. We’re still trying to figure it out. Hang in there with us.” One learner commented, “… since we do bedside presentations, he has a great way of translating our gibberish, basically, to real language the patient understands.”

Finally, the attendings anticipated what patients would need in the outpatient setting. We observed that attendings stressed what the next steps would be during transitions of care. As one learner put it, “But he also thinks ahead; what do they need as an outpatient?” Another current learner commented on how another attending always asked about the social situations of his patients stating, “And then there is the social part of it. So, he is very much interested [in] where do they live? What is their support system? So, I think it has been a very holistic approach to patient care.”

Respect for the Patient

The attendings we observed were steadfastly respectful toward patients. As one attending told us, “The patient’s room is sacred space, and it’s a privilege for us to be there. And if we don’t earn that privilege, then we don’t get to go there.” We observed that the attendings generally referred to the patient as Mr. or Ms. (last name) rather than the patient’s first name unless the patient insisted. We also noticed that many of the attendings would introduce the team members to the patients or ask each member to introduce himself or herself. They also tended to leave the room and patient the way they were found, for example, by pushing the patient’s bedside table so that it was back within his or her reach or placing socks back onto the patient’s feet.

We noted that many of our attendings used appropriate humor with patients and families. As one learner explained, “I think Dr. [attending] makes most of our patients laugh during rounds. I don’t know if you noticed, but he really puts a smile on their face[s] whenever he walks in. … Maybe it would catch them off guard the first day, but after that, they are so happy to see him.”

Finally, we noticed that several of our attendings made sure to meet the patient at eye level during discussions by either kneeling or sitting on a chair. One of the attendings put it this way: “That’s a horrible power dynamic when you’re an inpatient and you’re sick and someone’s standing over you telling you things, and I like to be able to make eye contact with people, and often times that requires me to kneel down or to sit on a stool or to sit on the bed. … I feel like you’re able to connect with the people in a much better way…” Learners viewed this behavior favorably. As one told us, “[The attending] gets down to their level and makes sure that all of their questions are answered. So that is one thing that other attendings don’t necessarily do.”

In our national, qualitative study of 12 exemplary attending physicians, we found that these clinicians generally exhibited the following behaviors with patients. First, they were personable and caring and made significant attempts to connect with their patients. This occasionally took the form of using touch to comfort patients. Second, they tended to seek the “big picture” and tried to understand what patients would need upon hospital discharge. They communicated plans clearly to patients and families and inquired if those plans were understood. Finally, they showed respect toward their patients without fail. Such respect took many forms but included leaving the patient and room exactly as they were found and speaking with patients at eye level.

Our findings are largely consistent with other key studies in this field. Not surprisingly, the attendings we observed adhered to the major suggestions that Branch and colleagues² put forth more than 15 years ago to improve the teaching of the humanistic dimension of the patient-physician relationship. Examples include greeting the patient, introducing team members and explaining each person’s role, asking open-ended questions, providing patient education, placing oneself at the same level as the patient, using appropriate touch, and being respectful. Weissmann et al.²² also found similar themes in their study of teaching physicians at 4 universities from 2003 to 2004. In that study, role-modeling was the primary method used by physician educators to teach the humanistic aspects of medical care, including nonverbal communication (eg, touch and eye contact), demonstration of respect, and building a personal connection with the patients.²²In a focus group-based study performed at a teaching hospital in Boston, Ramani and Orlander²³ concluded that both participating teachers and learners considered the patient’s bedside as a valuable venue to learn humanistic skills. Unfortunately, they also noted that there has been a decline in bedside teaching related to various factors, including documentation requirements and electronic medical records.²³ Our attendings all demonstrated the value of teaching at a patient’s bedside. Not only could physical examination skills be demonstrated but role-modeling of interpersonal skills could be observed by learners.

Block and colleagues²⁴ observed 29 interns in 732 patient encounters in 2 Baltimore training programs using Kahn’s “etiquette-based medicine” behaviors as a guide.¹² They found that interns introduced themselves 40% of the time, explained their role 37% of the time, touched patients on 65% of visits (including as part of the physical examination), asked open-ended questions 75% of the time, and sat down with patients during only 9% of visits.²⁴ Tackett et al.⁷ observed 24 hospitalists who collectively cared for 226 unique patients in 3 Baltimore-area hospitals. They found that each of the following behaviors was performed less than 30% of the time: explains role in care, shakes hand, and sits down.⁷ However, our attendings appeared to adhere to these behaviors to a much higher extent, though we did not quantify the interactions. This lends support to the notion that effective patient-physician interactions are the foundation of great teaching.

The attendings we observed (most of whom are inpatient based) tended to the contextual issues of the patients, such as their home environments and social support. Our exemplary physicians did what they could to ensure that patients received the appropriate follow-up care upon discharge.

Our study has important limitations. First, it was conducted in a limited number of US hospitals. The institutions represented were generally large, research-intensive, academic medical centers. Therefore, our findings may not apply to settings that are different from the hospitals studied. Second, our study included only 12 attendings and their learners, which may also limit the study’s generalizability. Third, we focused exclusively on teaching within general medicine rounds. Thus, our findings may not be generalizable to other subspecialties. Fourth, attendings were selected through a nonexhaustive method, increasing the potential for selection bias. However, the multisite design, the modified snowball sampling, and the inclusion of several types of institutions in the final participant pool introduced diversity to the final list. Former-learner responses were subject to recall bias. Finally, the study design is susceptible to observer bias. Attempts to reduce this included the diversity of the observers (ie, both a clinician and a nonclinician, the latter of whom was unfamiliar with medical education) and review of the data and coding by multiple research team members to ensure validity. Although we cannot discount the potential role of a Hawthorne effect on our data collection, the research team attempted to mitigate this by standing apart from the care teams and remaining unobtrusive during observations.

Limitations notwithstanding, we believe that our multisite study is important given the longstanding imperative to improve patient-physician interactions. We found empirical support for behaviors proposed by Branch and colleagues² and Kahn¹² in order to enhance these relationships. While others have studied attendings and their current learners,²² we add to the literature by also examining former learners’ perspectives on how the attendings’ teaching and role-modeling have created and sustained a lasting impact. The key findings of our national, qualitative study (care for the patient’s well-being, consideration of the “big picture,” and respect for the patient) can be readily adopted and honed by physicians to improve their interactions with hospitalized patients.

Acknowledgments

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Department of Veterans Affairs.

Funding

Dr. Saint provided funding for this study using a University of Michigan endowment.

Disclosure

The authors declare no conflicts of interest.

Approximately a century ago, Francis Peabody taught that “the secret of the care of the patient is in caring for the patient.”¹ His advice remains true today. Despite the advent of novel diagnostic tests, technologically sophisticated interventional procedures, and life-saving medications, perhaps the most important skill a bedside clinician can use is the ability to connect with patients.

The literature on patient-physician interaction is vast^2-11 and generally indicates that exemplary bedside clinicians are able to interact well with patients by being competent, trustworthy, personable, empathetic, and effective communicators. “Etiquette-based medicine,” first proposed by Kahn,¹² emphasizes the importance of certain behaviors from physicians, such as introducing yourself and explaining your role, shaking hands, sitting down when speaking to patients, and asking open-ended questions.

Yet, improving patient-physician interactions remains necessary. A recent systematic review reported that almost half of the reviewed studies on the patient-physician relationship published between 2000 and 2014 conveyed the idea that the patient-physician relationship is deteriorating.¹³

As part of a broader study to understand the behaviors and approaches of exemplary inpatient attending physicians,^14-16 we examined how 12 carefully selected physicians interacted with their patients during inpatient teaching rounds.

Overview

We conducted a multisite study using an exploratory, qualitative approach to inquiry, which has been described previously.^14-16 Our primary purpose was to study the attributes and behaviors of outstanding general medicine attendings in the setting of inpatient rounds. The focus of this article is on the attendings’ interactions with patients.

We used a modified snowball sampling approach¹⁷ to identify 12 exemplary physicians. First, we contacted individuals throughout the United States who were known to the principal investigator (S.S.) and asked for suggestions of excellent clinician educators (also referred to as attendings) for potential inclusion in the study. In addition to these personal contacts, other individuals unknown to the investigative team were contacted and asked to provide suggestions for attendings to include in the study. Specifically, the US News & World Report 2015 Top Medical Schools: Research Rankings,¹⁸ which are widely used to represent the best U.S. hospitals, were reviewed in an effort to identify attendings from a broad range of medical schools. Using this list, we identified other medical schools that were in the top 25 and were not already represented. We contacted the division chiefs of general internal (or hospital) medicine, chairs and chiefs of departments of internal medicine, and internal medicine residency program directors from these medical schools and asked for recommendations of attendings from both within and outside their institutions whom they considered to be great inpatient teachers.

This sampling method resulted in 59 potential participants. An internet search was conducted on each potential participant to obtain further information about the individuals and their institutions. Both personal characteristics (medical education, training, and educational awards) and organizational characteristics (geographic location, hospital size and affiliation, and patient population) were considered so that a variety of organizations and backgrounds were represented. Through this process, the list was narrowed to 16 attendings who were contacted to participate in the study, of which 12 agreed. The number of attendings examined was appropriate because saturation of metathemes can occur in as little as 6 interviews, and data saturation occurs at 12 interviews.¹⁹ The participants were asked to provide a list of their current learners (ie, residents and medical students) and 6 to 10 former learners to contact for interviews and focus groups.

Data Collection

Observations

Two researchers conducted the one-day site visits. One was a physician (S.S.) and the other a medical anthropologist (M.H.), and both have extensive experience in qualitative methods. The only exception was the site visit at the principal investigator’s own institution, which was conducted by the medical anthropologist and a nonpracticing physician who was unknown to the participants. The team structure varied slightly among different institutions but in general was composed of 1 attending, 1 senior medical resident, 1 to 2 interns, and approximately 2 medical students. Each site visit began with observing the attendings (n = 12) and current learners (n = 57) on morning rounds, which included their interactions with patients. These observations lasted approximately 2 to 3 hours. The observers took handwritten field notes, paying particular attention to group interactions, teaching approaches, and patient interactions. The observers stood outside the medical team circle and remained silent during rounds so as to be unobtrusive to the teams’ discussions. The observers discussed and compared their notes after each site visit.

Interviews and Focus Groups

The research team also conducted individual, semistructured interviews with the attendings (n = 12), focus groups with their current teams (n = 46), and interviews or focus groups with their former learners (n = 26). Current learners were asked open-ended questions about their roles on the teams, their opinions of the attendings, and the care the attendings provide to their patients. Because they were observed during rounds, the researchers asked for clarification about specific interactions observed during the teaching rounds. Depending on availability and location, former learners either participated in in-person focus groups or interviews on the day of the site visit, or in a later telephone interview. All interviews and focus groups were audio recorded and transcribed.

This study was deemed to be exempt from regulation by the University of Michigan Institutional Review Board. All participants were informed that their participation was completely voluntary and that they could refuse to answer any question.

Data Analysis

Data were analyzed using a thematic analysis approach,²⁰ which involves reading through the data to identify patterns (and create codes) that relate to behaviors, experiences, meanings, and activities. The patterns are then grouped into themes to help further explain the findings.²¹ The research team members (S.S. and M.H.) met after the first site visit and developed initial ideas about meanings and possible patterns. One team member (M.H.) read all the transcripts from the site visit and, based on the data, developed a codebook to be used for this study. This process was repeated after every site visit, and the coding definitions were refined as necessary. All transcripts were reviewed to apply any new codes when they developed. NVivo^® 10 software (QSR International, Melbourne, Australia) was used to assist with the qualitative data analysis.

To ensure consistency and identify relationships between codes, code reports listing all the data linked to a specific code were generated after all the field notes and transcripts were coded. Once verified, codes were grouped based on similarities and relationships into prominent themes related to physician-patient interactions by 2 team members (S.S. and M.H.), though all members reviewed them and concurred.

Care for the Patient’s Well-Being

The attendings we observed appeared to openly care for their patients’ well-being and were focused on the patients’ wants and needs. We noted that attendings were generally very attentive to the patients’ comfort. For example, we observed one attending sending the senior resident to find the patient’s nurse in order to obtain additional pain medications. The attending said to the patient several times, “I’m sorry you’re in so much pain.” When the team was leaving, she asked the intern to stay with the patient until the medications had been administered.

Consideration of the “Big Picture”

Our exemplary attendings kept the “big picture” (that is, the patient’s overall medical and social needs) in clear focus. They behaved in a way to ensure that the patients understood the key points of their care and explained so the patients and families could understand. A current learner said, “[The attending] really makes sure that the patient understands what’s going on. And she always asks them, ‘What do you understand, what do you know, how can we fill in any blanks?’ And that makes the patient really involved in their own care, which I think is important.” This reflection was supported by direct observations. Attendings posed the following questions at the conclusion of patient interactions: “Tell me what you know.” “Tell me what our plan is.” “What did the lung doctors tell you yesterday?” These questions, which have been termed “teach-back” and are crucial for health literacy, were not meant to quiz the patient but rather to ensure the patient and family understood the plan.

We noticed that the attendings effectively explained clinical details and the plan of care to the patient while avoiding medical jargon. The following is an example of one interaction with a patient: “You threw up and created a tear in the food tube. Air got from that into the middle of the chest, not into the lungs. Air isn’t normally there. If it is just air, the body will reabsorb [it]... But we worry about bacteria getting in with the air. We need to figure out if it is an infection. We’re still trying to figure it out. Hang in there with us.” One learner commented, “… since we do bedside presentations, he has a great way of translating our gibberish, basically, to real language the patient understands.”

Finally, the attendings anticipated what patients would need in the outpatient setting. We observed that attendings stressed what the next steps would be during transitions of care. As one learner put it, “But he also thinks ahead; what do they need as an outpatient?” Another current learner commented on how another attending always asked about the social situations of his patients stating, “And then there is the social part of it. So, he is very much interested [in] where do they live? What is their support system? So, I think it has been a very holistic approach to patient care.”

Respect for the Patient

The attendings we observed were steadfastly respectful toward patients. As one attending told us, “The patient’s room is sacred space, and it’s a privilege for us to be there. And if we don’t earn that privilege, then we don’t get to go there.” We observed that the attendings generally referred to the patient as Mr. or Ms. (last name) rather than the patient’s first name unless the patient insisted. We also noticed that many of the attendings would introduce the team members to the patients or ask each member to introduce himself or herself. They also tended to leave the room and patient the way they were found, for example, by pushing the patient’s bedside table so that it was back within his or her reach or placing socks back onto the patient’s feet.

We noted that many of our attendings used appropriate humor with patients and families. As one learner explained, “I think Dr. [attending] makes most of our patients laugh during rounds. I don’t know if you noticed, but he really puts a smile on their face[s] whenever he walks in. … Maybe it would catch them off guard the first day, but after that, they are so happy to see him.”

Finally, we noticed that several of our attendings made sure to meet the patient at eye level during discussions by either kneeling or sitting on a chair. One of the attendings put it this way: “That’s a horrible power dynamic when you’re an inpatient and you’re sick and someone’s standing over you telling you things, and I like to be able to make eye contact with people, and often times that requires me to kneel down or to sit on a stool or to sit on the bed. … I feel like you’re able to connect with the people in a much better way…” Learners viewed this behavior favorably. As one told us, “[The attending] gets down to their level and makes sure that all of their questions are answered. So that is one thing that other attendings don’t necessarily do.”

In our national, qualitative study of 12 exemplary attending physicians, we found that these clinicians generally exhibited the following behaviors with patients. First, they were personable and caring and made significant attempts to connect with their patients. This occasionally took the form of using touch to comfort patients. Second, they tended to seek the “big picture” and tried to understand what patients would need upon hospital discharge. They communicated plans clearly to patients and families and inquired if those plans were understood. Finally, they showed respect toward their patients without fail. Such respect took many forms but included leaving the patient and room exactly as they were found and speaking with patients at eye level.

Our findings are largely consistent with other key studies in this field. Not surprisingly, the attendings we observed adhered to the major suggestions that Branch and colleagues² put forth more than 15 years ago to improve the teaching of the humanistic dimension of the patient-physician relationship. Examples include greeting the patient, introducing team members and explaining each person’s role, asking open-ended questions, providing patient education, placing oneself at the same level as the patient, using appropriate touch, and being respectful. Weissmann et al.²² also found similar themes in their study of teaching physicians at 4 universities from 2003 to 2004. In that study, role-modeling was the primary method used by physician educators to teach the humanistic aspects of medical care, including nonverbal communication (eg, touch and eye contact), demonstration of respect, and building a personal connection with the patients.²²In a focus group-based study performed at a teaching hospital in Boston, Ramani and Orlander²³ concluded that both participating teachers and learners considered the patient’s bedside as a valuable venue to learn humanistic skills. Unfortunately, they also noted that there has been a decline in bedside teaching related to various factors, including documentation requirements and electronic medical records.²³ Our attendings all demonstrated the value of teaching at a patient’s bedside. Not only could physical examination skills be demonstrated but role-modeling of interpersonal skills could be observed by learners.

Block and colleagues²⁴ observed 29 interns in 732 patient encounters in 2 Baltimore training programs using Kahn’s “etiquette-based medicine” behaviors as a guide.¹² They found that interns introduced themselves 40% of the time, explained their role 37% of the time, touched patients on 65% of visits (including as part of the physical examination), asked open-ended questions 75% of the time, and sat down with patients during only 9% of visits.²⁴ Tackett et al.⁷ observed 24 hospitalists who collectively cared for 226 unique patients in 3 Baltimore-area hospitals. They found that each of the following behaviors was performed less than 30% of the time: explains role in care, shakes hand, and sits down.⁷ However, our attendings appeared to adhere to these behaviors to a much higher extent, though we did not quantify the interactions. This lends support to the notion that effective patient-physician interactions are the foundation of great teaching.

The attendings we observed (most of whom are inpatient based) tended to the contextual issues of the patients, such as their home environments and social support. Our exemplary physicians did what they could to ensure that patients received the appropriate follow-up care upon discharge.

Our study has important limitations. First, it was conducted in a limited number of US hospitals. The institutions represented were generally large, research-intensive, academic medical centers. Therefore, our findings may not apply to settings that are different from the hospitals studied. Second, our study included only 12 attendings and their learners, which may also limit the study’s generalizability. Third, we focused exclusively on teaching within general medicine rounds. Thus, our findings may not be generalizable to other subspecialties. Fourth, attendings were selected through a nonexhaustive method, increasing the potential for selection bias. However, the multisite design, the modified snowball sampling, and the inclusion of several types of institutions in the final participant pool introduced diversity to the final list. Former-learner responses were subject to recall bias. Finally, the study design is susceptible to observer bias. Attempts to reduce this included the diversity of the observers (ie, both a clinician and a nonclinician, the latter of whom was unfamiliar with medical education) and review of the data and coding by multiple research team members to ensure validity. Although we cannot discount the potential role of a Hawthorne effect on our data collection, the research team attempted to mitigate this by standing apart from the care teams and remaining unobtrusive during observations.

Limitations notwithstanding, we believe that our multisite study is important given the longstanding imperative to improve patient-physician interactions. We found empirical support for behaviors proposed by Branch and colleagues² and Kahn¹² in order to enhance these relationships. While others have studied attendings and their current learners,²² we add to the literature by also examining former learners’ perspectives on how the attendings’ teaching and role-modeling have created and sustained a lasting impact. The key findings of our national, qualitative study (care for the patient’s well-being, consideration of the “big picture,” and respect for the patient) can be readily adopted and honed by physicians to improve their interactions with hospitalized patients.

Acknowledgments

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Department of Veterans Affairs.

Funding

Dr. Saint provided funding for this study using a University of Michigan endowment.

Disclosure

The authors declare no conflicts of interest.

Approximately a century ago, Francis Peabody taught that “the secret of the care of the patient is in caring for the patient.”¹ His advice remains true today. Despite the advent of novel diagnostic tests, technologically sophisticated interventional procedures, and life-saving medications, perhaps the most important skill a bedside clinician can use is the ability to connect with patients.

The literature on patient-physician interaction is vast^2-11 and generally indicates that exemplary bedside clinicians are able to interact well with patients by being competent, trustworthy, personable, empathetic, and effective communicators. “Etiquette-based medicine,” first proposed by Kahn,¹² emphasizes the importance of certain behaviors from physicians, such as introducing yourself and explaining your role, shaking hands, sitting down when speaking to patients, and asking open-ended questions.

Yet, improving patient-physician interactions remains necessary. A recent systematic review reported that almost half of the reviewed studies on the patient-physician relationship published between 2000 and 2014 conveyed the idea that the patient-physician relationship is deteriorating.¹³

As part of a broader study to understand the behaviors and approaches of exemplary inpatient attending physicians,^14-16 we examined how 12 carefully selected physicians interacted with their patients during inpatient teaching rounds.

Overview

We conducted a multisite study using an exploratory, qualitative approach to inquiry, which has been described previously.^14-16 Our primary purpose was to study the attributes and behaviors of outstanding general medicine attendings in the setting of inpatient rounds. The focus of this article is on the attendings’ interactions with patients.

We used a modified snowball sampling approach¹⁷ to identify 12 exemplary physicians. First, we contacted individuals throughout the United States who were known to the principal investigator (S.S.) and asked for suggestions of excellent clinician educators (also referred to as attendings) for potential inclusion in the study. In addition to these personal contacts, other individuals unknown to the investigative team were contacted and asked to provide suggestions for attendings to include in the study. Specifically, the US News & World Report 2015 Top Medical Schools: Research Rankings,¹⁸ which are widely used to represent the best U.S. hospitals, were reviewed in an effort to identify attendings from a broad range of medical schools. Using this list, we identified other medical schools that were in the top 25 and were not already represented. We contacted the division chiefs of general internal (or hospital) medicine, chairs and chiefs of departments of internal medicine, and internal medicine residency program directors from these medical schools and asked for recommendations of attendings from both within and outside their institutions whom they considered to be great inpatient teachers.

This sampling method resulted in 59 potential participants. An internet search was conducted on each potential participant to obtain further information about the individuals and their institutions. Both personal characteristics (medical education, training, and educational awards) and organizational characteristics (geographic location, hospital size and affiliation, and patient population) were considered so that a variety of organizations and backgrounds were represented. Through this process, the list was narrowed to 16 attendings who were contacted to participate in the study, of which 12 agreed. The number of attendings examined was appropriate because saturation of metathemes can occur in as little as 6 interviews, and data saturation occurs at 12 interviews.¹⁹ The participants were asked to provide a list of their current learners (ie, residents and medical students) and 6 to 10 former learners to contact for interviews and focus groups.

Data Collection

Observations

Two researchers conducted the one-day site visits. One was a physician (S.S.) and the other a medical anthropologist (M.H.), and both have extensive experience in qualitative methods. The only exception was the site visit at the principal investigator’s own institution, which was conducted by the medical anthropologist and a nonpracticing physician who was unknown to the participants. The team structure varied slightly among different institutions but in general was composed of 1 attending, 1 senior medical resident, 1 to 2 interns, and approximately 2 medical students. Each site visit began with observing the attendings (n = 12) and current learners (n = 57) on morning rounds, which included their interactions with patients. These observations lasted approximately 2 to 3 hours. The observers took handwritten field notes, paying particular attention to group interactions, teaching approaches, and patient interactions. The observers stood outside the medical team circle and remained silent during rounds so as to be unobtrusive to the teams’ discussions. The observers discussed and compared their notes after each site visit.

Interviews and Focus Groups

The research team also conducted individual, semistructured interviews with the attendings (n = 12), focus groups with their current teams (n = 46), and interviews or focus groups with their former learners (n = 26). Current learners were asked open-ended questions about their roles on the teams, their opinions of the attendings, and the care the attendings provide to their patients. Because they were observed during rounds, the researchers asked for clarification about specific interactions observed during the teaching rounds. Depending on availability and location, former learners either participated in in-person focus groups or interviews on the day of the site visit, or in a later telephone interview. All interviews and focus groups were audio recorded and transcribed.

This study was deemed to be exempt from regulation by the University of Michigan Institutional Review Board. All participants were informed that their participation was completely voluntary and that they could refuse to answer any question.

Data Analysis

Data were analyzed using a thematic analysis approach,²⁰ which involves reading through the data to identify patterns (and create codes) that relate to behaviors, experiences, meanings, and activities. The patterns are then grouped into themes to help further explain the findings.²¹ The research team members (S.S. and M.H.) met after the first site visit and developed initial ideas about meanings and possible patterns. One team member (M.H.) read all the transcripts from the site visit and, based on the data, developed a codebook to be used for this study. This process was repeated after every site visit, and the coding definitions were refined as necessary. All transcripts were reviewed to apply any new codes when they developed. NVivo^® 10 software (QSR International, Melbourne, Australia) was used to assist with the qualitative data analysis.

To ensure consistency and identify relationships between codes, code reports listing all the data linked to a specific code were generated after all the field notes and transcripts were coded. Once verified, codes were grouped based on similarities and relationships into prominent themes related to physician-patient interactions by 2 team members (S.S. and M.H.), though all members reviewed them and concurred.

Care for the Patient’s Well-Being

The attendings we observed appeared to openly care for their patients’ well-being and were focused on the patients’ wants and needs. We noted that attendings were generally very attentive to the patients’ comfort. For example, we observed one attending sending the senior resident to find the patient’s nurse in order to obtain additional pain medications. The attending said to the patient several times, “I’m sorry you’re in so much pain.” When the team was leaving, she asked the intern to stay with the patient until the medications had been administered.

Consideration of the “Big Picture”

Our exemplary attendings kept the “big picture” (that is, the patient’s overall medical and social needs) in clear focus. They behaved in a way to ensure that the patients understood the key points of their care and explained so the patients and families could understand. A current learner said, “[The attending] really makes sure that the patient understands what’s going on. And she always asks them, ‘What do you understand, what do you know, how can we fill in any blanks?’ And that makes the patient really involved in their own care, which I think is important.” This reflection was supported by direct observations. Attendings posed the following questions at the conclusion of patient interactions: “Tell me what you know.” “Tell me what our plan is.” “What did the lung doctors tell you yesterday?” These questions, which have been termed “teach-back” and are crucial for health literacy, were not meant to quiz the patient but rather to ensure the patient and family understood the plan.

We noticed that the attendings effectively explained clinical details and the plan of care to the patient while avoiding medical jargon. The following is an example of one interaction with a patient: “You threw up and created a tear in the food tube. Air got from that into the middle of the chest, not into the lungs. Air isn’t normally there. If it is just air, the body will reabsorb [it]... But we worry about bacteria getting in with the air. We need to figure out if it is an infection. We’re still trying to figure it out. Hang in there with us.” One learner commented, “… since we do bedside presentations, he has a great way of translating our gibberish, basically, to real language the patient understands.”

Finally, the attendings anticipated what patients would need in the outpatient setting. We observed that attendings stressed what the next steps would be during transitions of care. As one learner put it, “But he also thinks ahead; what do they need as an outpatient?” Another current learner commented on how another attending always asked about the social situations of his patients stating, “And then there is the social part of it. So, he is very much interested [in] where do they live? What is their support system? So, I think it has been a very holistic approach to patient care.”

Respect for the Patient

The attendings we observed were steadfastly respectful toward patients. As one attending told us, “The patient’s room is sacred space, and it’s a privilege for us to be there. And if we don’t earn that privilege, then we don’t get to go there.” We observed that the attendings generally referred to the patient as Mr. or Ms. (last name) rather than the patient’s first name unless the patient insisted. We also noticed that many of the attendings would introduce the team members to the patients or ask each member to introduce himself or herself. They also tended to leave the room and patient the way they were found, for example, by pushing the patient’s bedside table so that it was back within his or her reach or placing socks back onto the patient’s feet.

We noted that many of our attendings used appropriate humor with patients and families. As one learner explained, “I think Dr. [attending] makes most of our patients laugh during rounds. I don’t know if you noticed, but he really puts a smile on their face[s] whenever he walks in. … Maybe it would catch them off guard the first day, but after that, they are so happy to see him.”

Finally, we noticed that several of our attendings made sure to meet the patient at eye level during discussions by either kneeling or sitting on a chair. One of the attendings put it this way: “That’s a horrible power dynamic when you’re an inpatient and you’re sick and someone’s standing over you telling you things, and I like to be able to make eye contact with people, and often times that requires me to kneel down or to sit on a stool or to sit on the bed. … I feel like you’re able to connect with the people in a much better way…” Learners viewed this behavior favorably. As one told us, “[The attending] gets down to their level and makes sure that all of their questions are answered. So that is one thing that other attendings don’t necessarily do.”

In our national, qualitative study of 12 exemplary attending physicians, we found that these clinicians generally exhibited the following behaviors with patients. First, they were personable and caring and made significant attempts to connect with their patients. This occasionally took the form of using touch to comfort patients. Second, they tended to seek the “big picture” and tried to understand what patients would need upon hospital discharge. They communicated plans clearly to patients and families and inquired if those plans were understood. Finally, they showed respect toward their patients without fail. Such respect took many forms but included leaving the patient and room exactly as they were found and speaking with patients at eye level.

Our findings are largely consistent with other key studies in this field. Not surprisingly, the attendings we observed adhered to the major suggestions that Branch and colleagues² put forth more than 15 years ago to improve the teaching of the humanistic dimension of the patient-physician relationship. Examples include greeting the patient, introducing team members and explaining each person’s role, asking open-ended questions, providing patient education, placing oneself at the same level as the patient, using appropriate touch, and being respectful. Weissmann et al.²² also found similar themes in their study of teaching physicians at 4 universities from 2003 to 2004. In that study, role-modeling was the primary method used by physician educators to teach the humanistic aspects of medical care, including nonverbal communication (eg, touch and eye contact), demonstration of respect, and building a personal connection with the patients.²²In a focus group-based study performed at a teaching hospital in Boston, Ramani and Orlander²³ concluded that both participating teachers and learners considered the patient’s bedside as a valuable venue to learn humanistic skills. Unfortunately, they also noted that there has been a decline in bedside teaching related to various factors, including documentation requirements and electronic medical records.²³ Our attendings all demonstrated the value of teaching at a patient’s bedside. Not only could physical examination skills be demonstrated but role-modeling of interpersonal skills could be observed by learners.

Block and colleagues²⁴ observed 29 interns in 732 patient encounters in 2 Baltimore training programs using Kahn’s “etiquette-based medicine” behaviors as a guide.¹² They found that interns introduced themselves 40% of the time, explained their role 37% of the time, touched patients on 65% of visits (including as part of the physical examination), asked open-ended questions 75% of the time, and sat down with patients during only 9% of visits.²⁴ Tackett et al.⁷ observed 24 hospitalists who collectively cared for 226 unique patients in 3 Baltimore-area hospitals. They found that each of the following behaviors was performed less than 30% of the time: explains role in care, shakes hand, and sits down.⁷ However, our attendings appeared to adhere to these behaviors to a much higher extent, though we did not quantify the interactions. This lends support to the notion that effective patient-physician interactions are the foundation of great teaching.

The attendings we observed (most of whom are inpatient based) tended to the contextual issues of the patients, such as their home environments and social support. Our exemplary physicians did what they could to ensure that patients received the appropriate follow-up care upon discharge.

Our study has important limitations. First, it was conducted in a limited number of US hospitals. The institutions represented were generally large, research-intensive, academic medical centers. Therefore, our findings may not apply to settings that are different from the hospitals studied. Second, our study included only 12 attendings and their learners, which may also limit the study’s generalizability. Third, we focused exclusively on teaching within general medicine rounds. Thus, our findings may not be generalizable to other subspecialties. Fourth, attendings were selected through a nonexhaustive method, increasing the potential for selection bias. However, the multisite design, the modified snowball sampling, and the inclusion of several types of institutions in the final participant pool introduced diversity to the final list. Former-learner responses were subject to recall bias. Finally, the study design is susceptible to observer bias. Attempts to reduce this included the diversity of the observers (ie, both a clinician and a nonclinician, the latter of whom was unfamiliar with medical education) and review of the data and coding by multiple research team members to ensure validity. Although we cannot discount the potential role of a Hawthorne effect on our data collection, the research team attempted to mitigate this by standing apart from the care teams and remaining unobtrusive during observations.

Limitations notwithstanding, we believe that our multisite study is important given the longstanding imperative to improve patient-physician interactions. We found empirical support for behaviors proposed by Branch and colleagues² and Kahn¹² in order to enhance these relationships. While others have studied attendings and their current learners,²² we add to the literature by also examining former learners’ perspectives on how the attendings’ teaching and role-modeling have created and sustained a lasting impact. The key findings of our national, qualitative study (care for the patient’s well-being, consideration of the “big picture,” and respect for the patient) can be readily adopted and honed by physicians to improve their interactions with hospitalized patients.

Acknowledgments

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Department of Veterans Affairs.

Funding

Dr. Saint provided funding for this study using a University of Michigan endowment.

Disclosure

The authors declare no conflicts of interest.

Abstract

• Background: Although transfusion guidelines have changed considerably over the past 2 decades, the adoption of patient blood management programs has not been fully realized across hospitals in the United States.
• Objective: To evaluate trends in red blood cell (RBC), platelet, and plasma transfusion at 3 Veterans Health Administration (VHA) hospitals from 2000 through 2010.
• Methods: Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization. Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type.
• Results: There were 176,521 hospitalizations in 69,621 patients; of these, 13.6% of hospitalizations involved transfusion of blood products (12.7% RBCs, 1.4% platelets, 3.0% plasma). Transfusion occurred in 25.2% of surgical and 5.3% of medical hospitalizations. Transfusion use peaked in 2002 for surgical hospitalizations and declined afterwards (P < 0.001). There was no significant change in transfusion use over time (P = 0.126) for medical hospitalizations. In hospitalizations that involved transfusions, there was a 20.3% reduction in the proportion of hospitalizations in which ≥ 3 units of RBCs were given (from 51.7% to 41.1%; P < 0.001) and a 73.6% increase when 1 RBC unit was given (from 8.0% to 13.8%; P < 0.001) from 2000-2010. Of the hospitalizations with RBC transfusion, 9.6% involved the use of 1 unit over the entire study period. The most common principal diagnoses for medical patients receiving transfusion were anemia, malignancy, heart failure, pneumonia and renal failure. Over time, transfusion utilization increased in patients who were admitted for infection (P = 0.009).
• Conclusion: Blood transfusions in 3 VHA hospitals have decreased over time for surgical patients but remained the same for medical patients. Further study examining appropriateness of blood products in medical patients appears necessary.

Key words: Transfusion; red blood cells; plasma; platelets; veterans.

Transfusion practices during hospitalization have changed considerably over the past 2 decades. Guided by evidence from randomized controlled trials, patient blood management programs have been expanded [1]. Such programs include recommendations regarding minimization of blood loss during surgery, prevention and treatment of anemia, strategies for reducing transfusions in both medical and surgical patients, improved blood utilization, education of health professionals, and standardization of blood management-related metrics [2]. Some of the guidelines have been incorporated into the Choosing Wisely initiative of the American Board of Internal Medicine Foundation, including: (a) don’t transfuse more units of blood than absolutely necessary, (b) don’t transfuse red blood cells for iron deficiency without hemodynamic instability, (c) don’t routinely use blood products to reverse warfarin, and (d) don’t perform serial blood counts on clinically stable patients [3]. Although there has been growing interest in blood management, only 37.8% of the 607 AABB (formerly, American Association of Blood Banks) facilities in the United States reported having a patient blood management program in 2013 [2].

While the importance of blood safety is recognized, data regarding the overall trends in practices are conflicting. A study using the Nationwide Inpatient Sample indicated that there was a 5.6% annual mean increase in the transfusion of blood products from 2002 to 2011 in the United States [4]. This contrasts with the experience of Kaiser Permanente in Northern California, in which the incidence of RBC transfusion decreased by 3.2% from 2009 to 2013 [5]. A decline in rates of intraoperative transfusion was also reported among elderly veterans in the United States from 1997 to 2009 [6].

We conducted a study in hospitalized veterans with 2 main objectives: (a) to evaluate trends in utilization of red blood cells (RBCs), platelets, and plasma over time, and (b) to identify those groups of veterans who received specific blood products. We were particularly interested in transfusion use in medical patients.

Methods

Participants were hospitalized veterans at 3 Department of Veterans Affairs (VA) medical centers. Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization.

Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type. Surgical hospitalizations were defined as admissions in which any surgical procedure occurred, whereas medical hospitalizations were defined as admissions without any surgery. Alpha was set at 0.05, 2-tailed. All analyses were conducted in Stata/MP 14.1 (StataCorp, College Station, TX). The study received institutional review board approval from the VA Ann Arbor Healthcare System.

Results

From 2000 through 2010, there were 176,521 hospitalizations in 69,621 patients. Within this cohort, 6% were < 40 years of age, 66% were 40 to 69 years of age, and 28% were 70 years or older at the time of admission. In this cohort, 96% of patients were male. Overall, 13.6% of all hospitalizations involved transfusion of a blood product (12.7% RBCs, 1.4% platelets, 3.0% plasma).

Transfusion occurred in 25.2% of surgical hospitalizations and 5.3% of medical hospitalizations. For surgical hospitalizations, transfusion use peaked in 2002 (when 30.9% of the surgical hospitalizations involved a trans-fusion) and significantly declined afterwards (P < 0.001). By 2010, 22.5% of the surgical hospitalizations involved a transfusion. Most of the surgeries where blood products were transfused involved cardiovascular procedures. For medical hospitalizations only, there was no significant change in transfusion use over time, either from 2000 to 2010 (P = 0.126) or from 2002 to 2010 (P = 0.072). In 2010, 5.2% of the medical hospitalizations involved a transfusion.

Rates of transfusion varied by principal diagnosis (Figure 1). For patients admitted with a principal diagnosis of infection (n = 20,981 hospitalizations), there was an increase in the percentage of hospitalizations in which transfusions (RBCs, platelet, plasma) were administered over time (P = 0.009) (Figure 1). For patients admitted with a principal diagnosis of malignancy (n = 12,904 hospitalizations), cardiovascular disease (n = 40,324 hospitalizations), and other diagnoses (n = 102,312 hospitalizations), there were no significant linear trends over the entire study period (P = 0.191, P = 0.052, P = 0.314, respectively). Rather, blood utilization peaked in year 2002 and significantly declined afterwards for patients admitted for malignancy (P < 0.001) and for cardiovascular disease (P < 0.001).

The most common principal diagnoses for medical patients receiving any transfusion (RBCs, platelet, plasma) are listed in Table 1. For medical patients with a principal diagnosis of anemia, 88% of hospitalizations involved a transfusion (Table 1). Transfusion occurred in 6% to 11% of medical hospitalizations with malignancies, heart failure, pneumonia or renal failure (Table 1). A considerable proportion (43%) of medical patients with gastrointestinal hemorrhage received a transfusion.

Discussion

We also observed secular trends in the volume of RBCs administered. There was an increase in the percentage of hospitalizations in which 1 or 2 RBC units were used and a decline in transfusion of 3 or more units. The reduction in the use of 3 or more RBC units may reflect the adoption and integration of recommendations in patient blood management by clinicians,

which encourage assessment of the patients’ symptoms in determining whether additional units are necessary [7]. Such guidelines also endorse the avoidance of routine
administration of 2 units of RBCs if 1 unit is sufficient [8]. We have previously shown that, after coronary artery bypass grafting, 2 RBC units doubled the risk of pneumonia [9]; additional analyses indicated that 1 or 2 units of RBCs were associated with increased postoperative morbidity [10]. In addition, our previous research indicated that the probability of infection increased considerably between 1 and 2 RBC units, with a more gradual increase beyond 2 units [11]. With this evidence in mind, some studies at single sites have reported that there was a dramatic decline from 2 RBC units before initiation of patient blood management programs to 1 unit after the programs were implemented [12,13].

Medical patients who received a transfusion were often admitted for reason of anemia, cancer, organ failure, or pneumonia. Some researchers are now reporting that blood use, at certain sites, is becoming more common in medical rather than surgical patients, which may be due to an expansion of patient blood management procedures in surgery [16]. There are a substantial number of patient blood management programs among surgical specialties and their adoption has expanded [17]. Although there are fewer patient blood management programs in the nonsurgical setting, some have been targeted to internal medicine physicians and specifically, to hospitalists [1,18]. For example, a toolkit from the Society of Hospital Medicine centers on anemia management and includes anemia assessment, treatment, evaluation of RBC transfusion risk, blood conservation, optimization of coagulation, and patient-centered decision-making [19]. Additionally, bundling of patient blood management strategies has been launched to help encourage a wider adoption of such programs [20].

While guidelines regarding use of RBCs are becoming increasingly recognized, recommendations for the use of platelets and plasma are hampered by the paucity of evidence from randomized controlled trials [21,22]. There is moderate-quality evidence for the use of platelets with therapy-induced hypoproliferative thrombocytopenia in hospitalized patients [21], but low quality evidence for other uses. Moreover, a recent review of plasma transfusion in bleeding patients found no randomized controlled trials on plasma use in hospitalized patients, although several trials were currently underway [22].

Our findings need to be considered in the context of the following limitations. The data were from 3 VA hospitals, so the results may not reflect patterns of usage at other hospitals. However, AABB reports that there has been a general decrease in transfusion of allogeneic whole blood and RBC units since 2008 at the AABB-affiliated sites in the United States [2]; this is similar to the pattern that we observed in surgical patients. In addition, we report an overall view of trends without having details regarding which specific factors influenced changes in transfusion during this 11-year period. It is possible that the severity of hospitalized patients may have changed with time which could have influenced decisions regarding the need for transfusion.

In conclusion, the use of blood products decreased in surgical patients since 2002 but remained the same in medical patients in this VA population. Transfusions increased over time for patients who were admitted to the hospital for reason of infection, but decreased since 2002 for those admitted for cardiovascular disease or cancer. The number of RBC units per hospitalization decreased over time. Additional surveillance is needed to determine whether recent evidence regarding blood management has been incorporated into clinical practice for medical patients, as we strive to deliver optimal care to our veterans.

Corresponding author: Mary A.M. Rogers, PhD, MS, Dept. of Internal Medicine, Univ. of Michigan, 016-422W NCRC, Ann Arbor, MI 48109-2800, maryroge@umich.edu.

Funding/support: Department of Veterans Affairs, Clinical Sciences Research & Development Service Merit Review Award (EPID-011-11S). The contents do not represent the views of the U.S. Department of Veterans Affairs or the U.S. Government.

Financial disclosures: None.

Author contributions: conception and design, MAMR, SS; analysis and interpretation of data, MAMR, JDB, DR, LK, SS; drafting of article, MAMR; critical revision of the article, MAMR, MTG, DR, LK, SS, VC; statistical expertise, MAMR, DR; obtaining of funding, MTG, SS, VC; administrative or technical support, MTG, LK, SS, VC; collection and assembly of data, JDB, LK.

Abstract

• Background: Although transfusion guidelines have changed considerably over the past 2 decades, the adoption of patient blood management programs has not been fully realized across hospitals in the United States.
• Objective: To evaluate trends in red blood cell (RBC), platelet, and plasma transfusion at 3 Veterans Health Administration (VHA) hospitals from 2000 through 2010.
• Methods: Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization. Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type.
• Results: There were 176,521 hospitalizations in 69,621 patients; of these, 13.6% of hospitalizations involved transfusion of blood products (12.7% RBCs, 1.4% platelets, 3.0% plasma). Transfusion occurred in 25.2% of surgical and 5.3% of medical hospitalizations. Transfusion use peaked in 2002 for surgical hospitalizations and declined afterwards (P < 0.001). There was no significant change in transfusion use over time (P = 0.126) for medical hospitalizations. In hospitalizations that involved transfusions, there was a 20.3% reduction in the proportion of hospitalizations in which ≥ 3 units of RBCs were given (from 51.7% to 41.1%; P < 0.001) and a 73.6% increase when 1 RBC unit was given (from 8.0% to 13.8%; P < 0.001) from 2000-2010. Of the hospitalizations with RBC transfusion, 9.6% involved the use of 1 unit over the entire study period. The most common principal diagnoses for medical patients receiving transfusion were anemia, malignancy, heart failure, pneumonia and renal failure. Over time, transfusion utilization increased in patients who were admitted for infection (P = 0.009).
• Conclusion: Blood transfusions in 3 VHA hospitals have decreased over time for surgical patients but remained the same for medical patients. Further study examining appropriateness of blood products in medical patients appears necessary.

Key words: Transfusion; red blood cells; plasma; platelets; veterans.

Transfusion practices during hospitalization have changed considerably over the past 2 decades. Guided by evidence from randomized controlled trials, patient blood management programs have been expanded [1]. Such programs include recommendations regarding minimization of blood loss during surgery, prevention and treatment of anemia, strategies for reducing transfusions in both medical and surgical patients, improved blood utilization, education of health professionals, and standardization of blood management-related metrics [2]. Some of the guidelines have been incorporated into the Choosing Wisely initiative of the American Board of Internal Medicine Foundation, including: (a) don’t transfuse more units of blood than absolutely necessary, (b) don’t transfuse red blood cells for iron deficiency without hemodynamic instability, (c) don’t routinely use blood products to reverse warfarin, and (d) don’t perform serial blood counts on clinically stable patients [3]. Although there has been growing interest in blood management, only 37.8% of the 607 AABB (formerly, American Association of Blood Banks) facilities in the United States reported having a patient blood management program in 2013 [2].

While the importance of blood safety is recognized, data regarding the overall trends in practices are conflicting. A study using the Nationwide Inpatient Sample indicated that there was a 5.6% annual mean increase in the transfusion of blood products from 2002 to 2011 in the United States [4]. This contrasts with the experience of Kaiser Permanente in Northern California, in which the incidence of RBC transfusion decreased by 3.2% from 2009 to 2013 [5]. A decline in rates of intraoperative transfusion was also reported among elderly veterans in the United States from 1997 to 2009 [6].

We conducted a study in hospitalized veterans with 2 main objectives: (a) to evaluate trends in utilization of red blood cells (RBCs), platelets, and plasma over time, and (b) to identify those groups of veterans who received specific blood products. We were particularly interested in transfusion use in medical patients.

Methods

Participants were hospitalized veterans at 3 Department of Veterans Affairs (VA) medical centers. Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization.

Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type. Surgical hospitalizations were defined as admissions in which any surgical procedure occurred, whereas medical hospitalizations were defined as admissions without any surgery. Alpha was set at 0.05, 2-tailed. All analyses were conducted in Stata/MP 14.1 (StataCorp, College Station, TX). The study received institutional review board approval from the VA Ann Arbor Healthcare System.

Results

From 2000 through 2010, there were 176,521 hospitalizations in 69,621 patients. Within this cohort, 6% were < 40 years of age, 66% were 40 to 69 years of age, and 28% were 70 years or older at the time of admission. In this cohort, 96% of patients were male. Overall, 13.6% of all hospitalizations involved transfusion of a blood product (12.7% RBCs, 1.4% platelets, 3.0% plasma).

Transfusion occurred in 25.2% of surgical hospitalizations and 5.3% of medical hospitalizations. For surgical hospitalizations, transfusion use peaked in 2002 (when 30.9% of the surgical hospitalizations involved a trans-fusion) and significantly declined afterwards (P < 0.001). By 2010, 22.5% of the surgical hospitalizations involved a transfusion. Most of the surgeries where blood products were transfused involved cardiovascular procedures. For medical hospitalizations only, there was no significant change in transfusion use over time, either from 2000 to 2010 (P = 0.126) or from 2002 to 2010 (P = 0.072). In 2010, 5.2% of the medical hospitalizations involved a transfusion.

Rates of transfusion varied by principal diagnosis (Figure 1). For patients admitted with a principal diagnosis of infection (n = 20,981 hospitalizations), there was an increase in the percentage of hospitalizations in which transfusions (RBCs, platelet, plasma) were administered over time (P = 0.009) (Figure 1). For patients admitted with a principal diagnosis of malignancy (n = 12,904 hospitalizations), cardiovascular disease (n = 40,324 hospitalizations), and other diagnoses (n = 102,312 hospitalizations), there were no significant linear trends over the entire study period (P = 0.191, P = 0.052, P = 0.314, respectively). Rather, blood utilization peaked in year 2002 and significantly declined afterwards for patients admitted for malignancy (P < 0.001) and for cardiovascular disease (P < 0.001).

The most common principal diagnoses for medical patients receiving any transfusion (RBCs, platelet, plasma) are listed in Table 1. For medical patients with a principal diagnosis of anemia, 88% of hospitalizations involved a transfusion (Table 1). Transfusion occurred in 6% to 11% of medical hospitalizations with malignancies, heart failure, pneumonia or renal failure (Table 1). A considerable proportion (43%) of medical patients with gastrointestinal hemorrhage received a transfusion.

Discussion

We also observed secular trends in the volume of RBCs administered. There was an increase in the percentage of hospitalizations in which 1 or 2 RBC units were used and a decline in transfusion of 3 or more units. The reduction in the use of 3 or more RBC units may reflect the adoption and integration of recommendations in patient blood management by clinicians,

which encourage assessment of the patients’ symptoms in determining whether additional units are necessary [7]. Such guidelines also endorse the avoidance of routine
administration of 2 units of RBCs if 1 unit is sufficient [8]. We have previously shown that, after coronary artery bypass grafting, 2 RBC units doubled the risk of pneumonia [9]; additional analyses indicated that 1 or 2 units of RBCs were associated with increased postoperative morbidity [10]. In addition, our previous research indicated that the probability of infection increased considerably between 1 and 2 RBC units, with a more gradual increase beyond 2 units [11]. With this evidence in mind, some studies at single sites have reported that there was a dramatic decline from 2 RBC units before initiation of patient blood management programs to 1 unit after the programs were implemented [12,13].

Medical patients who received a transfusion were often admitted for reason of anemia, cancer, organ failure, or pneumonia. Some researchers are now reporting that blood use, at certain sites, is becoming more common in medical rather than surgical patients, which may be due to an expansion of patient blood management procedures in surgery [16]. There are a substantial number of patient blood management programs among surgical specialties and their adoption has expanded [17]. Although there are fewer patient blood management programs in the nonsurgical setting, some have been targeted to internal medicine physicians and specifically, to hospitalists [1,18]. For example, a toolkit from the Society of Hospital Medicine centers on anemia management and includes anemia assessment, treatment, evaluation of RBC transfusion risk, blood conservation, optimization of coagulation, and patient-centered decision-making [19]. Additionally, bundling of patient blood management strategies has been launched to help encourage a wider adoption of such programs [20].

While guidelines regarding use of RBCs are becoming increasingly recognized, recommendations for the use of platelets and plasma are hampered by the paucity of evidence from randomized controlled trials [21,22]. There is moderate-quality evidence for the use of platelets with therapy-induced hypoproliferative thrombocytopenia in hospitalized patients [21], but low quality evidence for other uses. Moreover, a recent review of plasma transfusion in bleeding patients found no randomized controlled trials on plasma use in hospitalized patients, although several trials were currently underway [22].

Our findings need to be considered in the context of the following limitations. The data were from 3 VA hospitals, so the results may not reflect patterns of usage at other hospitals. However, AABB reports that there has been a general decrease in transfusion of allogeneic whole blood and RBC units since 2008 at the AABB-affiliated sites in the United States [2]; this is similar to the pattern that we observed in surgical patients. In addition, we report an overall view of trends without having details regarding which specific factors influenced changes in transfusion during this 11-year period. It is possible that the severity of hospitalized patients may have changed with time which could have influenced decisions regarding the need for transfusion.

In conclusion, the use of blood products decreased in surgical patients since 2002 but remained the same in medical patients in this VA population. Transfusions increased over time for patients who were admitted to the hospital for reason of infection, but decreased since 2002 for those admitted for cardiovascular disease or cancer. The number of RBC units per hospitalization decreased over time. Additional surveillance is needed to determine whether recent evidence regarding blood management has been incorporated into clinical practice for medical patients, as we strive to deliver optimal care to our veterans.

Corresponding author: Mary A.M. Rogers, PhD, MS, Dept. of Internal Medicine, Univ. of Michigan, 016-422W NCRC, Ann Arbor, MI 48109-2800, maryroge@umich.edu.

Funding/support: Department of Veterans Affairs, Clinical Sciences Research & Development Service Merit Review Award (EPID-011-11S). The contents do not represent the views of the U.S. Department of Veterans Affairs or the U.S. Government.

Financial disclosures: None.

Author contributions: conception and design, MAMR, SS; analysis and interpretation of data, MAMR, JDB, DR, LK, SS; drafting of article, MAMR; critical revision of the article, MAMR, MTG, DR, LK, SS, VC; statistical expertise, MAMR, DR; obtaining of funding, MTG, SS, VC; administrative or technical support, MTG, LK, SS, VC; collection and assembly of data, JDB, LK.

Abstract

• Background: Although transfusion guidelines have changed considerably over the past 2 decades, the adoption of patient blood management programs has not been fully realized across hospitals in the United States.
• Objective: To evaluate trends in red blood cell (RBC), platelet, and plasma transfusion at 3 Veterans Health Administration (VHA) hospitals from 2000 through 2010.
• Methods: Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization. Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type.
• Results: There were 176,521 hospitalizations in 69,621 patients; of these, 13.6% of hospitalizations involved transfusion of blood products (12.7% RBCs, 1.4% platelets, 3.0% plasma). Transfusion occurred in 25.2% of surgical and 5.3% of medical hospitalizations. Transfusion use peaked in 2002 for surgical hospitalizations and declined afterwards (P < 0.001). There was no significant change in transfusion use over time (P = 0.126) for medical hospitalizations. In hospitalizations that involved transfusions, there was a 20.3% reduction in the proportion of hospitalizations in which ≥ 3 units of RBCs were given (from 51.7% to 41.1%; P < 0.001) and a 73.6% increase when 1 RBC unit was given (from 8.0% to 13.8%; P < 0.001) from 2000-2010. Of the hospitalizations with RBC transfusion, 9.6% involved the use of 1 unit over the entire study period. The most common principal diagnoses for medical patients receiving transfusion were anemia, malignancy, heart failure, pneumonia and renal failure. Over time, transfusion utilization increased in patients who were admitted for infection (P = 0.009).
• Conclusion: Blood transfusions in 3 VHA hospitals have decreased over time for surgical patients but remained the same for medical patients. Further study examining appropriateness of blood products in medical patients appears necessary.

Key words: Transfusion; red blood cells; plasma; platelets; veterans.

Transfusion practices during hospitalization have changed considerably over the past 2 decades. Guided by evidence from randomized controlled trials, patient blood management programs have been expanded [1]. Such programs include recommendations regarding minimization of blood loss during surgery, prevention and treatment of anemia, strategies for reducing transfusions in both medical and surgical patients, improved blood utilization, education of health professionals, and standardization of blood management-related metrics [2]. Some of the guidelines have been incorporated into the Choosing Wisely initiative of the American Board of Internal Medicine Foundation, including: (a) don’t transfuse more units of blood than absolutely necessary, (b) don’t transfuse red blood cells for iron deficiency without hemodynamic instability, (c) don’t routinely use blood products to reverse warfarin, and (d) don’t perform serial blood counts on clinically stable patients [3]. Although there has been growing interest in blood management, only 37.8% of the 607 AABB (formerly, American Association of Blood Banks) facilities in the United States reported having a patient blood management program in 2013 [2].

While the importance of blood safety is recognized, data regarding the overall trends in practices are conflicting. A study using the Nationwide Inpatient Sample indicated that there was a 5.6% annual mean increase in the transfusion of blood products from 2002 to 2011 in the United States [4]. This contrasts with the experience of Kaiser Permanente in Northern California, in which the incidence of RBC transfusion decreased by 3.2% from 2009 to 2013 [5]. A decline in rates of intraoperative transfusion was also reported among elderly veterans in the United States from 1997 to 2009 [6].

We conducted a study in hospitalized veterans with 2 main objectives: (a) to evaluate trends in utilization of red blood cells (RBCs), platelets, and plasma over time, and (b) to identify those groups of veterans who received specific blood products. We were particularly interested in transfusion use in medical patients.

Methods

Participants were hospitalized veterans at 3 Department of Veterans Affairs (VA) medical centers. Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization.

Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type. Surgical hospitalizations were defined as admissions in which any surgical procedure occurred, whereas medical hospitalizations were defined as admissions without any surgery. Alpha was set at 0.05, 2-tailed. All analyses were conducted in Stata/MP 14.1 (StataCorp, College Station, TX). The study received institutional review board approval from the VA Ann Arbor Healthcare System.

Results

From 2000 through 2010, there were 176,521 hospitalizations in 69,621 patients. Within this cohort, 6% were < 40 years of age, 66% were 40 to 69 years of age, and 28% were 70 years or older at the time of admission. In this cohort, 96% of patients were male. Overall, 13.6% of all hospitalizations involved transfusion of a blood product (12.7% RBCs, 1.4% platelets, 3.0% plasma).

Transfusion occurred in 25.2% of surgical hospitalizations and 5.3% of medical hospitalizations. For surgical hospitalizations, transfusion use peaked in 2002 (when 30.9% of the surgical hospitalizations involved a trans-fusion) and significantly declined afterwards (P < 0.001). By 2010, 22.5% of the surgical hospitalizations involved a transfusion. Most of the surgeries where blood products were transfused involved cardiovascular procedures. For medical hospitalizations only, there was no significant change in transfusion use over time, either from 2000 to 2010 (P = 0.126) or from 2002 to 2010 (P = 0.072). In 2010, 5.2% of the medical hospitalizations involved a transfusion.

Rates of transfusion varied by principal diagnosis (Figure 1). For patients admitted with a principal diagnosis of infection (n = 20,981 hospitalizations), there was an increase in the percentage of hospitalizations in which transfusions (RBCs, platelet, plasma) were administered over time (P = 0.009) (Figure 1). For patients admitted with a principal diagnosis of malignancy (n = 12,904 hospitalizations), cardiovascular disease (n = 40,324 hospitalizations), and other diagnoses (n = 102,312 hospitalizations), there were no significant linear trends over the entire study period (P = 0.191, P = 0.052, P = 0.314, respectively). Rather, blood utilization peaked in year 2002 and significantly declined afterwards for patients admitted for malignancy (P < 0.001) and for cardiovascular disease (P < 0.001).

The most common principal diagnoses for medical patients receiving any transfusion (RBCs, platelet, plasma) are listed in Table 1. For medical patients with a principal diagnosis of anemia, 88% of hospitalizations involved a transfusion (Table 1). Transfusion occurred in 6% to 11% of medical hospitalizations with malignancies, heart failure, pneumonia or renal failure (Table 1). A considerable proportion (43%) of medical patients with gastrointestinal hemorrhage received a transfusion.

Discussion

We also observed secular trends in the volume of RBCs administered. There was an increase in the percentage of hospitalizations in which 1 or 2 RBC units were used and a decline in transfusion of 3 or more units. The reduction in the use of 3 or more RBC units may reflect the adoption and integration of recommendations in patient blood management by clinicians,

which encourage assessment of the patients’ symptoms in determining whether additional units are necessary [7]. Such guidelines also endorse the avoidance of routine
administration of 2 units of RBCs if 1 unit is sufficient [8]. We have previously shown that, after coronary artery bypass grafting, 2 RBC units doubled the risk of pneumonia [9]; additional analyses indicated that 1 or 2 units of RBCs were associated with increased postoperative morbidity [10]. In addition, our previous research indicated that the probability of infection increased considerably between 1 and 2 RBC units, with a more gradual increase beyond 2 units [11]. With this evidence in mind, some studies at single sites have reported that there was a dramatic decline from 2 RBC units before initiation of patient blood management programs to 1 unit after the programs were implemented [12,13].

Medical patients who received a transfusion were often admitted for reason of anemia, cancer, organ failure, or pneumonia. Some researchers are now reporting that blood use, at certain sites, is becoming more common in medical rather than surgical patients, which may be due to an expansion of patient blood management procedures in surgery [16]. There are a substantial number of patient blood management programs among surgical specialties and their adoption has expanded [17]. Although there are fewer patient blood management programs in the nonsurgical setting, some have been targeted to internal medicine physicians and specifically, to hospitalists [1,18]. For example, a toolkit from the Society of Hospital Medicine centers on anemia management and includes anemia assessment, treatment, evaluation of RBC transfusion risk, blood conservation, optimization of coagulation, and patient-centered decision-making [19]. Additionally, bundling of patient blood management strategies has been launched to help encourage a wider adoption of such programs [20].

While guidelines regarding use of RBCs are becoming increasingly recognized, recommendations for the use of platelets and plasma are hampered by the paucity of evidence from randomized controlled trials [21,22]. There is moderate-quality evidence for the use of platelets with therapy-induced hypoproliferative thrombocytopenia in hospitalized patients [21], but low quality evidence for other uses. Moreover, a recent review of plasma transfusion in bleeding patients found no randomized controlled trials on plasma use in hospitalized patients, although several trials were currently underway [22].

Our findings need to be considered in the context of the following limitations. The data were from 3 VA hospitals, so the results may not reflect patterns of usage at other hospitals. However, AABB reports that there has been a general decrease in transfusion of allogeneic whole blood and RBC units since 2008 at the AABB-affiliated sites in the United States [2]; this is similar to the pattern that we observed in surgical patients. In addition, we report an overall view of trends without having details regarding which specific factors influenced changes in transfusion during this 11-year period. It is possible that the severity of hospitalized patients may have changed with time which could have influenced decisions regarding the need for transfusion.

In conclusion, the use of blood products decreased in surgical patients since 2002 but remained the same in medical patients in this VA population. Transfusions increased over time for patients who were admitted to the hospital for reason of infection, but decreased since 2002 for those admitted for cardiovascular disease or cancer. The number of RBC units per hospitalization decreased over time. Additional surveillance is needed to determine whether recent evidence regarding blood management has been incorporated into clinical practice for medical patients, as we strive to deliver optimal care to our veterans.

Corresponding author: Mary A.M. Rogers, PhD, MS, Dept. of Internal Medicine, Univ. of Michigan, 016-422W NCRC, Ann Arbor, MI 48109-2800, maryroge@umich.edu.

Funding/support: Department of Veterans Affairs, Clinical Sciences Research & Development Service Merit Review Award (EPID-011-11S). The contents do not represent the views of the U.S. Department of Veterans Affairs or the U.S. Government.

Financial disclosures: None.

Author contributions: conception and design, MAMR, SS; analysis and interpretation of data, MAMR, JDB, DR, LK, SS; drafting of article, MAMR; critical revision of the article, MAMR, MTG, DR, LK, SS, VC; statistical expertise, MAMR, DR; obtaining of funding, MTG, SS, VC; administrative or technical support, MTG, LK, SS, VC; collection and assembly of data, JDB, LK.

A 57-year-old woman presented to the emergency department of a community hospital with a 2-week history of dizziness, blurred vision, and poor coordination following a flu-like illness. Symptoms were initially attributed to complications from a presumed viral illness, but when they persisted for 2 weeks, she underwent magnetic resonance imaging (MRI) of the brain, which was reported as showing a 2.4 x 2.3 x 1.9 cm right frontal lobe mass with mild mass effect and contrast enhancement (Figure 1). She was discharged home at her request with plans for outpatient follow-up.

Brain masses are usually neoplastic, infectious, or less commonly, inflammatory. The isolated lesion in the right frontal lobe is unlikely to explain her symptoms, which are more suggestive of multifocal disease or elevated intracranial pressure. Although the frontal eye fields could be affected by the mass, such lesions usually cause tonic eye deviation, not blurry vision; furthermore, coordination, which is impaired here, is not governed by the frontal lobe.

Two weeks later, she returned to the same emergency department with worsening symptoms and new bilateral upper extremity dystonia, confusion, and visual hallucinations. Cerebrospinal fluid (CSF) analysis revealed clear, nonxanthochromic fluid with 4 nucleated cells (a differential was not performed), 113 red blood cells, glucose of 80 mg/dL (normal range, 50-80 mg/dL), and protein of 52 mg/dL (normal range, 15-45 mg/dL).

Confusion is generally caused by a metabolic, infectious, structural, or toxic etiology. Standard CSF test results are usually normal with most toxic or metabolic encephalopathies. The absence of significant CSF inflammation argues against infectious encephalitis; paraneoplastic and autoimmune encephalitis, however, are still possible. The CSF red blood cells were likely due to a mildly traumatic tap, but also may have arisen from the frontal lobe mass or a more diffuse invasive process, although the lack of xanthochromia argues against this. Delirium and red blood cells in the CSF should trigger consideration of herpes simplex virus (HSV) encephalitis, although the time course is a bit too protracted and the reported MRI findings do not suggest typical medial temporal lobe involvement.

The disparate neurologic findings suggest a multifocal process, perhaps embolic (eg, endocarditis), ischemic (eg, intravascular lymphoma), infiltrative (eg, malignancy, neurosarcoidosis), or demyelinating (eg, postinfectious acute disseminated encephalomyelitis, multiple sclerosis). However, most of these would have been detected on the initial MRI. Upper extremity dystonia would likely localize to the basal ganglia, whereas confusion and visual hallucinations are more global. The combination of a movement disorder and visual hallucinations is seen in Lewy body dementia, but this tempo is not typical.

Although the CSF does not have pleocytosis, her original symptoms were flu-like; therefore, CSF testing for viruses (eg, enterovirus) is reasonable. Bacterial, mycobacteria, and fungal studies are apt to be unrevealing, but CSF cytology, IgG index, and oligoclonal bands may be useful. Should the encephalopathy progress further and the general medical evaluation prove to be normal, then tests for autoimmune disorders (eg, antinuclear antibodies, NMDAR, paraneoplastic disorders) and rare causes of rapidly progressive dementias (eg, prion diseases) should be sent.

Additional CSF studies including HSV polymerase chain reaction (PCR), West Nile PCR, Lyme antibody, paraneoplastic antibodies, and cytology were sent. Intravenous acyclovir was administered. The above studies, as well as Gram stain, acid-fast bacillus stain, fungal stain, and cultures, were negative. She was started on levetiracetam for seizure prevention due to the mass lesion. An electroencephalogram (EEG) was reported as showing diffuse background slowing with superimposed semiperiodic sharp waves with a right hemispheric emphasis. Intravenous immunoglobulin (IVIG) 0.4 mg/kg/day over 5 days was administered with no improvement. The patient was transferred to an academic medical center for further evaluation.

The EEG reflects encephalopathy without pointing to a specific diagnosis. Prophylactic antiepileptic medications are not indicated for CNS mass lesions without clinical or electrophysiologic seizure activity. IVIG is often administered when an autoimmune encephalitis is suspected, but the lack of response does not rule out an autoimmune condition.

Her medical history included bilateral cataract extraction, right leg fracture, tonsillectomy, and total abdominal hysterectomy. She had a 25-year smoking history and a family history of lung cancer. She had no history of drug or alcohol use. On examination, her temperature was 37.9°C, blood pressure of 144/98 mm Hg, respiratory rate of 18 breaths per minute, a heart rate of 121 beats per minute, and oxygen saturation of 97% on ambient air. Her eyes were open but she was nonverbal. Her chest was clear to auscultation. Heart sounds were distinct and rhythm was regular. Abdomen was soft and nontender with no organomegaly. Skin examination revealed no rash. Her pupils were equal, round, and reactive to light. She did not follow verbal or gestural commands and intermittently tracked with her eyes, but not consistently enough to characterize extraocular movements. Her face was symmetric. She had a normal gag and blink reflex and an increased jaw jerk reflex. Her arms were flexed with increased tone. She had a positive palmo-mental reflex. She had spontaneous movement of all extremities. She had symmetric, 3+ reflexes of the patella and Achilles tendon with a bilateral Babinski’s sign. Sensation was intact only to withdrawal from noxious stimuli.

The physical exam does not localize to a specific brain region, but suggests a diffuse brain process. There are multiple signs of upper motor neuron involvement, including increased tone, hyperreflexia, and Babinski (plantar flexion) reflexes. A palmo-mental reflex signifies pathology in the cerebrum. Although cranial nerve testing is limited, there are no features of cranial neuropathy; similarly, no pyramidal weakness or sensory deficit has been demonstrated on limited testing. The differential diagnosis of her rapidly progressive encephalopathy includes autoimmune or paraneoplastic encephalitis, diffuse infiltrative malignancy, metabolic diseases (eg, porphyria, heavy metal intoxication), and prion disease.

Her family history of lung cancer and her smoking increases the possibility of paraneoplastic encephalitis, which often has subacute behavioral changes that precede complete neurologic impairment. Inflammatory or hemorrhagic CSF is seen with Balamuthia amoebic infection, which causes a granulomatous encephalitis and is characteristically associated with a mass lesion. Toxoplasmosis causes encephalitis that can be profound, but patients are usually immunocompromised and there are typically multiple lesions.

Laboratory results showed a normal white blood cell count and differential, basic metabolic profile and liver function tests, and C-reactive protein. Human immunodeficiency virus antibody testing was negative. Chest radiography and computed tomography of chest, abdomen, and pelvis were normal. A repeat MRI of the brain with contrast was reported as showing a 2.4 x 2.3 x 1.9 cm heterogeneously enhancing mass in the right frontal lobe with an enhancing dural tail and underlying hyperostosis consistent with a meningioma, and blooming within the mass consistent with prior hemorrhage. No mass effect was present.

The meningioma was resected 3 days after admission but her symptoms did not improve. Routine postoperative MRI was reported to show expected postsurgical changes but no infarct. Brain biopsy at the time of the operation was reported as meningioma and mild gliosis without encephalitis.

The reported MRI findings showing unchanged size and overall appearance of the mass, its connection to the dura and skull, and the pathology results all suggest that the mass is a meningioma. There is no evidence of disease outside of the CNS. Some cancers that provoke a paraneoplastic response can be quite small yet may incite an immune encephalitis; anti-NMDAR-mediated encephalitis can occur with malignancy (often ovarian), although it also arises in the absence of any tumor. Any inclination to definitively exclude conditions not seen on the brain biopsy must be tempered by the limited sensitivity of brain histology examination. Still, what was not seen warrants mention: vascular inflammation suggestive of CNS vasculitis, granulomas that might point to neurosarcoidosis, malignant cells of an infiltrating lymphoma or glioma, or inflammatory cells suggestive of encephalitis. Prion encephalopathy remains possible.

The patient remained unresponsive. A repeat EEG showed bilateral generalized periodic epileptiform discharges with accompanying twitching of the head, face, and left arm, which were suppressed with intravenous propofol and levetiracetam. Three weeks following meningioma resection, a new MRI was read as showing new abnormal signal in the right basal ganglia, abnormality of the cortex on the diffusion weighted images, and progressive generalized volume loss.

Among the aforementioned diagnoses, focal or diffuse periodic epileptiform discharges at 1-2 hertz are most characteristic of prion disease. Striatal and cortical transverse relaxation time (T2)-weighted and diffusion-weighted imaging (DWI) hyperintensities with corresponding restricted diffusion is characteristic of Creutzfeldt-Jakob disease (CJD), although metabolic disorders, seizures, and encephalitis can very rarely show similar MRI findings. The clinical course, the MRI and EEG findings, and nondiagnostic biopsy results, which were initially not assessed for prion disease, collectively point to prion disease. Detection of abnormal prion protein in the brain tissue by immunohistochemistry or molecular methods would confirm the diagnosis.

Review of the original right frontal cortex biopsy specimen at the National Prion Disease Pathology Surveillance Center, including immunostaining with 3F4, a monoclonal antibody to the prion protein, revealed granular deposits typical of prion disease. This finding established a diagnosis of prion disease, likely sporadic CJD. The patient was transitioned to palliative care and died shortly thereafter.

Brain autopsy showed regions with transcortical vacuolation (spongiform change), other cortical regions with varying degrees of vacuolation, abundant reactive astrocytes, paucity of neurons, and dark shrunken neurons. Vacuolation and gliosis were observed in the striatum and were most pronounced in the thalamus. There was no evidence of an inflammatory infiltrate or a neoplastic process. These findings with the positive 3F4 immunohistochemistry and positive Western blot from brain autopsy, as well as the absence of a mutation in the prion protein gene, were diagnostic for CJD.

An investigation was initiated to track the nondisposable surgical instruments used in the meningioma resection that may have been subsequently used in other patients. It was determined that 52 neurosurgical patients may have been exposed to prion-contaminated instruments. The instruments were subsequently processed specifically for prion decontamination. After 7 years, no cases of CJD have been diagnosed in the potentially exposed patients.

CJD is a rare neurodegenerative condition¹ classified as one of the transmissible spongiform encephalopathies, so called because of the characteristic spongiform pattern (vacuolation) seen on histology, as well as the presence of neuronal loss, reactive gliosis in the gray matter, and the accumulation of the abnormal isoform of the cellular prion protein.² It affects about one person in every one million people per year worldwide; in the United States there are about 300 cases per year. The most common form of human prion disease, sporadic CJD, is relentlessly progressive and invariably fatal, and in most cases, death occurs less than 5 months from onset.³ There is no cure, although temporizing treatments for symptoms can be helpful.

Sporadic CJD, which accounts for approximately 85% of all cases of prion disease in humans, typically manifests with rapidly progressive dementia and myoclonus after a prolonged incubation period in persons between 55 and 75 years of age. Genetic forms account for approximately 15% and acquired forms less than 1% of human prion diseases.¹ Prion diseases have a broad spectrum of clinical manifestations, including dementia, ataxia, parkinsonism, myoclonus, insomnia, paresthesias, and abnormal or changed behavior.⁴ Given the protean clinical manifestations of prion diseases and rarity, the diagnosis is challenging to make antemortem. One recent study showed that most patients receive about 4 misdiagnoses and are often two-thirds of the way through their disease course before the correct diagnosis of sporadic CJD is made.⁵

• Rapidly progressive dementias (RPD) are characterized by cognitive decline over weeks to months. The RPD differential diagnosis includes fulminant forms of common neurodegenerative disorders (eg, Alzheimer’s disease, dementia with Lewy bodies, frontotemporal dementia spectrum), autoimmune encephalidites, CNS cancers, and prion disease.
• Sporadic CJD is the most common human prion disease. It is a rare neurodegenerative condition with onset usually between the ages of 50 and 70 years, and most commonly manifests with rapidly progressive dementia, ataxia, and myoclonus.
• Because of its protean manifestations, the diagnosis of CJD is difficult to make antemortem, and diagnosis is often delayed. Specialist evaluation of brain MRI DWI sequences and new CSF diagnostic tests may allow for earlier diagnosis, which has management and infection control implications.

Disclosure

Dr. Dhaliwal reports receiving honoraria from ISMIE Mutual Insurance Company and Physicians’ Reciprocal Insurers. Dr Geschwind’s institution has received R01 grant funding from NIH/NIA; and Alliance Biosecure and the Michael J Homer Family Fund as paid money to his institution, Dr Geschwind has received consulting fees or honoraria from Best Doctors, Kendall Brill & Kelly, CJD Foundation, and Tau Consortium; Dr Geschwind is a consultant for Gerson Lehrman Group, Biohaven Pharmaceuticals, and Advance Medical, outside the submitted work; has grants/grantspending with Quest, Cure PSP, and Tau Consortium, and received payment for lectures from Multiple Grand Rounds Lectures, outside the submitted work. Dr Saint is on a medical advisory board of Doximity, has received honorarium for being a member of the medical advisory board; he is also on the scientifice advisory board of Jvion. Dr Safdar’s institution has received a grant from the VA Patient Safety Center.

A 57-year-old woman presented to the emergency department of a community hospital with a 2-week history of dizziness, blurred vision, and poor coordination following a flu-like illness. Symptoms were initially attributed to complications from a presumed viral illness, but when they persisted for 2 weeks, she underwent magnetic resonance imaging (MRI) of the brain, which was reported as showing a 2.4 x 2.3 x 1.9 cm right frontal lobe mass with mild mass effect and contrast enhancement (Figure 1). She was discharged home at her request with plans for outpatient follow-up.

Brain masses are usually neoplastic, infectious, or less commonly, inflammatory. The isolated lesion in the right frontal lobe is unlikely to explain her symptoms, which are more suggestive of multifocal disease or elevated intracranial pressure. Although the frontal eye fields could be affected by the mass, such lesions usually cause tonic eye deviation, not blurry vision; furthermore, coordination, which is impaired here, is not governed by the frontal lobe.

Two weeks later, she returned to the same emergency department with worsening symptoms and new bilateral upper extremity dystonia, confusion, and visual hallucinations. Cerebrospinal fluid (CSF) analysis revealed clear, nonxanthochromic fluid with 4 nucleated cells (a differential was not performed), 113 red blood cells, glucose of 80 mg/dL (normal range, 50-80 mg/dL), and protein of 52 mg/dL (normal range, 15-45 mg/dL).

Confusion is generally caused by a metabolic, infectious, structural, or toxic etiology. Standard CSF test results are usually normal with most toxic or metabolic encephalopathies. The absence of significant CSF inflammation argues against infectious encephalitis; paraneoplastic and autoimmune encephalitis, however, are still possible. The CSF red blood cells were likely due to a mildly traumatic tap, but also may have arisen from the frontal lobe mass or a more diffuse invasive process, although the lack of xanthochromia argues against this. Delirium and red blood cells in the CSF should trigger consideration of herpes simplex virus (HSV) encephalitis, although the time course is a bit too protracted and the reported MRI findings do not suggest typical medial temporal lobe involvement.

The disparate neurologic findings suggest a multifocal process, perhaps embolic (eg, endocarditis), ischemic (eg, intravascular lymphoma), infiltrative (eg, malignancy, neurosarcoidosis), or demyelinating (eg, postinfectious acute disseminated encephalomyelitis, multiple sclerosis). However, most of these would have been detected on the initial MRI. Upper extremity dystonia would likely localize to the basal ganglia, whereas confusion and visual hallucinations are more global. The combination of a movement disorder and visual hallucinations is seen in Lewy body dementia, but this tempo is not typical.

Although the CSF does not have pleocytosis, her original symptoms were flu-like; therefore, CSF testing for viruses (eg, enterovirus) is reasonable. Bacterial, mycobacteria, and fungal studies are apt to be unrevealing, but CSF cytology, IgG index, and oligoclonal bands may be useful. Should the encephalopathy progress further and the general medical evaluation prove to be normal, then tests for autoimmune disorders (eg, antinuclear antibodies, NMDAR, paraneoplastic disorders) and rare causes of rapidly progressive dementias (eg, prion diseases) should be sent.

Additional CSF studies including HSV polymerase chain reaction (PCR), West Nile PCR, Lyme antibody, paraneoplastic antibodies, and cytology were sent. Intravenous acyclovir was administered. The above studies, as well as Gram stain, acid-fast bacillus stain, fungal stain, and cultures, were negative. She was started on levetiracetam for seizure prevention due to the mass lesion. An electroencephalogram (EEG) was reported as showing diffuse background slowing with superimposed semiperiodic sharp waves with a right hemispheric emphasis. Intravenous immunoglobulin (IVIG) 0.4 mg/kg/day over 5 days was administered with no improvement. The patient was transferred to an academic medical center for further evaluation.

The EEG reflects encephalopathy without pointing to a specific diagnosis. Prophylactic antiepileptic medications are not indicated for CNS mass lesions without clinical or electrophysiologic seizure activity. IVIG is often administered when an autoimmune encephalitis is suspected, but the lack of response does not rule out an autoimmune condition.

Her medical history included bilateral cataract extraction, right leg fracture, tonsillectomy, and total abdominal hysterectomy. She had a 25-year smoking history and a family history of lung cancer. She had no history of drug or alcohol use. On examination, her temperature was 37.9°C, blood pressure of 144/98 mm Hg, respiratory rate of 18 breaths per minute, a heart rate of 121 beats per minute, and oxygen saturation of 97% on ambient air. Her eyes were open but she was nonverbal. Her chest was clear to auscultation. Heart sounds were distinct and rhythm was regular. Abdomen was soft and nontender with no organomegaly. Skin examination revealed no rash. Her pupils were equal, round, and reactive to light. She did not follow verbal or gestural commands and intermittently tracked with her eyes, but not consistently enough to characterize extraocular movements. Her face was symmetric. She had a normal gag and blink reflex and an increased jaw jerk reflex. Her arms were flexed with increased tone. She had a positive palmo-mental reflex. She had spontaneous movement of all extremities. She had symmetric, 3+ reflexes of the patella and Achilles tendon with a bilateral Babinski’s sign. Sensation was intact only to withdrawal from noxious stimuli.

The physical exam does not localize to a specific brain region, but suggests a diffuse brain process. There are multiple signs of upper motor neuron involvement, including increased tone, hyperreflexia, and Babinski (plantar flexion) reflexes. A palmo-mental reflex signifies pathology in the cerebrum. Although cranial nerve testing is limited, there are no features of cranial neuropathy; similarly, no pyramidal weakness or sensory deficit has been demonstrated on limited testing. The differential diagnosis of her rapidly progressive encephalopathy includes autoimmune or paraneoplastic encephalitis, diffuse infiltrative malignancy, metabolic diseases (eg, porphyria, heavy metal intoxication), and prion disease.

Her family history of lung cancer and her smoking increases the possibility of paraneoplastic encephalitis, which often has subacute behavioral changes that precede complete neurologic impairment. Inflammatory or hemorrhagic CSF is seen with Balamuthia amoebic infection, which causes a granulomatous encephalitis and is characteristically associated with a mass lesion. Toxoplasmosis causes encephalitis that can be profound, but patients are usually immunocompromised and there are typically multiple lesions.

Laboratory results showed a normal white blood cell count and differential, basic metabolic profile and liver function tests, and C-reactive protein. Human immunodeficiency virus antibody testing was negative. Chest radiography and computed tomography of chest, abdomen, and pelvis were normal. A repeat MRI of the brain with contrast was reported as showing a 2.4 x 2.3 x 1.9 cm heterogeneously enhancing mass in the right frontal lobe with an enhancing dural tail and underlying hyperostosis consistent with a meningioma, and blooming within the mass consistent with prior hemorrhage. No mass effect was present.

The meningioma was resected 3 days after admission but her symptoms did not improve. Routine postoperative MRI was reported to show expected postsurgical changes but no infarct. Brain biopsy at the time of the operation was reported as meningioma and mild gliosis without encephalitis.

The reported MRI findings showing unchanged size and overall appearance of the mass, its connection to the dura and skull, and the pathology results all suggest that the mass is a meningioma. There is no evidence of disease outside of the CNS. Some cancers that provoke a paraneoplastic response can be quite small yet may incite an immune encephalitis; anti-NMDAR-mediated encephalitis can occur with malignancy (often ovarian), although it also arises in the absence of any tumor. Any inclination to definitively exclude conditions not seen on the brain biopsy must be tempered by the limited sensitivity of brain histology examination. Still, what was not seen warrants mention: vascular inflammation suggestive of CNS vasculitis, granulomas that might point to neurosarcoidosis, malignant cells of an infiltrating lymphoma or glioma, or inflammatory cells suggestive of encephalitis. Prion encephalopathy remains possible.

The patient remained unresponsive. A repeat EEG showed bilateral generalized periodic epileptiform discharges with accompanying twitching of the head, face, and left arm, which were suppressed with intravenous propofol and levetiracetam. Three weeks following meningioma resection, a new MRI was read as showing new abnormal signal in the right basal ganglia, abnormality of the cortex on the diffusion weighted images, and progressive generalized volume loss.

Among the aforementioned diagnoses, focal or diffuse periodic epileptiform discharges at 1-2 hertz are most characteristic of prion disease. Striatal and cortical transverse relaxation time (T2)-weighted and diffusion-weighted imaging (DWI) hyperintensities with corresponding restricted diffusion is characteristic of Creutzfeldt-Jakob disease (CJD), although metabolic disorders, seizures, and encephalitis can very rarely show similar MRI findings. The clinical course, the MRI and EEG findings, and nondiagnostic biopsy results, which were initially not assessed for prion disease, collectively point to prion disease. Detection of abnormal prion protein in the brain tissue by immunohistochemistry or molecular methods would confirm the diagnosis.

Review of the original right frontal cortex biopsy specimen at the National Prion Disease Pathology Surveillance Center, including immunostaining with 3F4, a monoclonal antibody to the prion protein, revealed granular deposits typical of prion disease. This finding established a diagnosis of prion disease, likely sporadic CJD. The patient was transitioned to palliative care and died shortly thereafter.

Brain autopsy showed regions with transcortical vacuolation (spongiform change), other cortical regions with varying degrees of vacuolation, abundant reactive astrocytes, paucity of neurons, and dark shrunken neurons. Vacuolation and gliosis were observed in the striatum and were most pronounced in the thalamus. There was no evidence of an inflammatory infiltrate or a neoplastic process. These findings with the positive 3F4 immunohistochemistry and positive Western blot from brain autopsy, as well as the absence of a mutation in the prion protein gene, were diagnostic for CJD.

An investigation was initiated to track the nondisposable surgical instruments used in the meningioma resection that may have been subsequently used in other patients. It was determined that 52 neurosurgical patients may have been exposed to prion-contaminated instruments. The instruments were subsequently processed specifically for prion decontamination. After 7 years, no cases of CJD have been diagnosed in the potentially exposed patients.

CJD is a rare neurodegenerative condition¹ classified as one of the transmissible spongiform encephalopathies, so called because of the characteristic spongiform pattern (vacuolation) seen on histology, as well as the presence of neuronal loss, reactive gliosis in the gray matter, and the accumulation of the abnormal isoform of the cellular prion protein.² It affects about one person in every one million people per year worldwide; in the United States there are about 300 cases per year. The most common form of human prion disease, sporadic CJD, is relentlessly progressive and invariably fatal, and in most cases, death occurs less than 5 months from onset.³ There is no cure, although temporizing treatments for symptoms can be helpful.

Sporadic CJD, which accounts for approximately 85% of all cases of prion disease in humans, typically manifests with rapidly progressive dementia and myoclonus after a prolonged incubation period in persons between 55 and 75 years of age. Genetic forms account for approximately 15% and acquired forms less than 1% of human prion diseases.¹ Prion diseases have a broad spectrum of clinical manifestations, including dementia, ataxia, parkinsonism, myoclonus, insomnia, paresthesias, and abnormal or changed behavior.⁴ Given the protean clinical manifestations of prion diseases and rarity, the diagnosis is challenging to make antemortem. One recent study showed that most patients receive about 4 misdiagnoses and are often two-thirds of the way through their disease course before the correct diagnosis of sporadic CJD is made.⁵

• Rapidly progressive dementias (RPD) are characterized by cognitive decline over weeks to months. The RPD differential diagnosis includes fulminant forms of common neurodegenerative disorders (eg, Alzheimer’s disease, dementia with Lewy bodies, frontotemporal dementia spectrum), autoimmune encephalidites, CNS cancers, and prion disease.
• Sporadic CJD is the most common human prion disease. It is a rare neurodegenerative condition with onset usually between the ages of 50 and 70 years, and most commonly manifests with rapidly progressive dementia, ataxia, and myoclonus.
• Because of its protean manifestations, the diagnosis of CJD is difficult to make antemortem, and diagnosis is often delayed. Specialist evaluation of brain MRI DWI sequences and new CSF diagnostic tests may allow for earlier diagnosis, which has management and infection control implications.

Disclosure

Dr. Dhaliwal reports receiving honoraria from ISMIE Mutual Insurance Company and Physicians’ Reciprocal Insurers. Dr Geschwind’s institution has received R01 grant funding from NIH/NIA; and Alliance Biosecure and the Michael J Homer Family Fund as paid money to his institution, Dr Geschwind has received consulting fees or honoraria from Best Doctors, Kendall Brill & Kelly, CJD Foundation, and Tau Consortium; Dr Geschwind is a consultant for Gerson Lehrman Group, Biohaven Pharmaceuticals, and Advance Medical, outside the submitted work; has grants/grantspending with Quest, Cure PSP, and Tau Consortium, and received payment for lectures from Multiple Grand Rounds Lectures, outside the submitted work. Dr Saint is on a medical advisory board of Doximity, has received honorarium for being a member of the medical advisory board; he is also on the scientifice advisory board of Jvion. Dr Safdar’s institution has received a grant from the VA Patient Safety Center.

A 57-year-old woman presented to the emergency department of a community hospital with a 2-week history of dizziness, blurred vision, and poor coordination following a flu-like illness. Symptoms were initially attributed to complications from a presumed viral illness, but when they persisted for 2 weeks, she underwent magnetic resonance imaging (MRI) of the brain, which was reported as showing a 2.4 x 2.3 x 1.9 cm right frontal lobe mass with mild mass effect and contrast enhancement (Figure 1). She was discharged home at her request with plans for outpatient follow-up.

Brain masses are usually neoplastic, infectious, or less commonly, inflammatory. The isolated lesion in the right frontal lobe is unlikely to explain her symptoms, which are more suggestive of multifocal disease or elevated intracranial pressure. Although the frontal eye fields could be affected by the mass, such lesions usually cause tonic eye deviation, not blurry vision; furthermore, coordination, which is impaired here, is not governed by the frontal lobe.

Two weeks later, she returned to the same emergency department with worsening symptoms and new bilateral upper extremity dystonia, confusion, and visual hallucinations. Cerebrospinal fluid (CSF) analysis revealed clear, nonxanthochromic fluid with 4 nucleated cells (a differential was not performed), 113 red blood cells, glucose of 80 mg/dL (normal range, 50-80 mg/dL), and protein of 52 mg/dL (normal range, 15-45 mg/dL).

Confusion is generally caused by a metabolic, infectious, structural, or toxic etiology. Standard CSF test results are usually normal with most toxic or metabolic encephalopathies. The absence of significant CSF inflammation argues against infectious encephalitis; paraneoplastic and autoimmune encephalitis, however, are still possible. The CSF red blood cells were likely due to a mildly traumatic tap, but also may have arisen from the frontal lobe mass or a more diffuse invasive process, although the lack of xanthochromia argues against this. Delirium and red blood cells in the CSF should trigger consideration of herpes simplex virus (HSV) encephalitis, although the time course is a bit too protracted and the reported MRI findings do not suggest typical medial temporal lobe involvement.

The disparate neurologic findings suggest a multifocal process, perhaps embolic (eg, endocarditis), ischemic (eg, intravascular lymphoma), infiltrative (eg, malignancy, neurosarcoidosis), or demyelinating (eg, postinfectious acute disseminated encephalomyelitis, multiple sclerosis). However, most of these would have been detected on the initial MRI. Upper extremity dystonia would likely localize to the basal ganglia, whereas confusion and visual hallucinations are more global. The combination of a movement disorder and visual hallucinations is seen in Lewy body dementia, but this tempo is not typical.

Although the CSF does not have pleocytosis, her original symptoms were flu-like; therefore, CSF testing for viruses (eg, enterovirus) is reasonable. Bacterial, mycobacteria, and fungal studies are apt to be unrevealing, but CSF cytology, IgG index, and oligoclonal bands may be useful. Should the encephalopathy progress further and the general medical evaluation prove to be normal, then tests for autoimmune disorders (eg, antinuclear antibodies, NMDAR, paraneoplastic disorders) and rare causes of rapidly progressive dementias (eg, prion diseases) should be sent.

Additional CSF studies including HSV polymerase chain reaction (PCR), West Nile PCR, Lyme antibody, paraneoplastic antibodies, and cytology were sent. Intravenous acyclovir was administered. The above studies, as well as Gram stain, acid-fast bacillus stain, fungal stain, and cultures, were negative. She was started on levetiracetam for seizure prevention due to the mass lesion. An electroencephalogram (EEG) was reported as showing diffuse background slowing with superimposed semiperiodic sharp waves with a right hemispheric emphasis. Intravenous immunoglobulin (IVIG) 0.4 mg/kg/day over 5 days was administered with no improvement. The patient was transferred to an academic medical center for further evaluation.

The EEG reflects encephalopathy without pointing to a specific diagnosis. Prophylactic antiepileptic medications are not indicated for CNS mass lesions without clinical or electrophysiologic seizure activity. IVIG is often administered when an autoimmune encephalitis is suspected, but the lack of response does not rule out an autoimmune condition.

Her medical history included bilateral cataract extraction, right leg fracture, tonsillectomy, and total abdominal hysterectomy. She had a 25-year smoking history and a family history of lung cancer. She had no history of drug or alcohol use. On examination, her temperature was 37.9°C, blood pressure of 144/98 mm Hg, respiratory rate of 18 breaths per minute, a heart rate of 121 beats per minute, and oxygen saturation of 97% on ambient air. Her eyes were open but she was nonverbal. Her chest was clear to auscultation. Heart sounds were distinct and rhythm was regular. Abdomen was soft and nontender with no organomegaly. Skin examination revealed no rash. Her pupils were equal, round, and reactive to light. She did not follow verbal or gestural commands and intermittently tracked with her eyes, but not consistently enough to characterize extraocular movements. Her face was symmetric. She had a normal gag and blink reflex and an increased jaw jerk reflex. Her arms were flexed with increased tone. She had a positive palmo-mental reflex. She had spontaneous movement of all extremities. She had symmetric, 3+ reflexes of the patella and Achilles tendon with a bilateral Babinski’s sign. Sensation was intact only to withdrawal from noxious stimuli.

The physical exam does not localize to a specific brain region, but suggests a diffuse brain process. There are multiple signs of upper motor neuron involvement, including increased tone, hyperreflexia, and Babinski (plantar flexion) reflexes. A palmo-mental reflex signifies pathology in the cerebrum. Although cranial nerve testing is limited, there are no features of cranial neuropathy; similarly, no pyramidal weakness or sensory deficit has been demonstrated on limited testing. The differential diagnosis of her rapidly progressive encephalopathy includes autoimmune or paraneoplastic encephalitis, diffuse infiltrative malignancy, metabolic diseases (eg, porphyria, heavy metal intoxication), and prion disease.

Her family history of lung cancer and her smoking increases the possibility of paraneoplastic encephalitis, which often has subacute behavioral changes that precede complete neurologic impairment. Inflammatory or hemorrhagic CSF is seen with Balamuthia amoebic infection, which causes a granulomatous encephalitis and is characteristically associated with a mass lesion. Toxoplasmosis causes encephalitis that can be profound, but patients are usually immunocompromised and there are typically multiple lesions.

Laboratory results showed a normal white blood cell count and differential, basic metabolic profile and liver function tests, and C-reactive protein. Human immunodeficiency virus antibody testing was negative. Chest radiography and computed tomography of chest, abdomen, and pelvis were normal. A repeat MRI of the brain with contrast was reported as showing a 2.4 x 2.3 x 1.9 cm heterogeneously enhancing mass in the right frontal lobe with an enhancing dural tail and underlying hyperostosis consistent with a meningioma, and blooming within the mass consistent with prior hemorrhage. No mass effect was present.

The meningioma was resected 3 days after admission but her symptoms did not improve. Routine postoperative MRI was reported to show expected postsurgical changes but no infarct. Brain biopsy at the time of the operation was reported as meningioma and mild gliosis without encephalitis.

The reported MRI findings showing unchanged size and overall appearance of the mass, its connection to the dura and skull, and the pathology results all suggest that the mass is a meningioma. There is no evidence of disease outside of the CNS. Some cancers that provoke a paraneoplastic response can be quite small yet may incite an immune encephalitis; anti-NMDAR-mediated encephalitis can occur with malignancy (often ovarian), although it also arises in the absence of any tumor. Any inclination to definitively exclude conditions not seen on the brain biopsy must be tempered by the limited sensitivity of brain histology examination. Still, what was not seen warrants mention: vascular inflammation suggestive of CNS vasculitis, granulomas that might point to neurosarcoidosis, malignant cells of an infiltrating lymphoma or glioma, or inflammatory cells suggestive of encephalitis. Prion encephalopathy remains possible.

The patient remained unresponsive. A repeat EEG showed bilateral generalized periodic epileptiform discharges with accompanying twitching of the head, face, and left arm, which were suppressed with intravenous propofol and levetiracetam. Three weeks following meningioma resection, a new MRI was read as showing new abnormal signal in the right basal ganglia, abnormality of the cortex on the diffusion weighted images, and progressive generalized volume loss.

Among the aforementioned diagnoses, focal or diffuse periodic epileptiform discharges at 1-2 hertz are most characteristic of prion disease. Striatal and cortical transverse relaxation time (T2)-weighted and diffusion-weighted imaging (DWI) hyperintensities with corresponding restricted diffusion is characteristic of Creutzfeldt-Jakob disease (CJD), although metabolic disorders, seizures, and encephalitis can very rarely show similar MRI findings. The clinical course, the MRI and EEG findings, and nondiagnostic biopsy results, which were initially not assessed for prion disease, collectively point to prion disease. Detection of abnormal prion protein in the brain tissue by immunohistochemistry or molecular methods would confirm the diagnosis.

Review of the original right frontal cortex biopsy specimen at the National Prion Disease Pathology Surveillance Center, including immunostaining with 3F4, a monoclonal antibody to the prion protein, revealed granular deposits typical of prion disease. This finding established a diagnosis of prion disease, likely sporadic CJD. The patient was transitioned to palliative care and died shortly thereafter.

Brain autopsy showed regions with transcortical vacuolation (spongiform change), other cortical regions with varying degrees of vacuolation, abundant reactive astrocytes, paucity of neurons, and dark shrunken neurons. Vacuolation and gliosis were observed in the striatum and were most pronounced in the thalamus. There was no evidence of an inflammatory infiltrate or a neoplastic process. These findings with the positive 3F4 immunohistochemistry and positive Western blot from brain autopsy, as well as the absence of a mutation in the prion protein gene, were diagnostic for CJD.

An investigation was initiated to track the nondisposable surgical instruments used in the meningioma resection that may have been subsequently used in other patients. It was determined that 52 neurosurgical patients may have been exposed to prion-contaminated instruments. The instruments were subsequently processed specifically for prion decontamination. After 7 years, no cases of CJD have been diagnosed in the potentially exposed patients.

CJD is a rare neurodegenerative condition¹ classified as one of the transmissible spongiform encephalopathies, so called because of the characteristic spongiform pattern (vacuolation) seen on histology, as well as the presence of neuronal loss, reactive gliosis in the gray matter, and the accumulation of the abnormal isoform of the cellular prion protein.² It affects about one person in every one million people per year worldwide; in the United States there are about 300 cases per year. The most common form of human prion disease, sporadic CJD, is relentlessly progressive and invariably fatal, and in most cases, death occurs less than 5 months from onset.³ There is no cure, although temporizing treatments for symptoms can be helpful.

Sporadic CJD, which accounts for approximately 85% of all cases of prion disease in humans, typically manifests with rapidly progressive dementia and myoclonus after a prolonged incubation period in persons between 55 and 75 years of age. Genetic forms account for approximately 15% and acquired forms less than 1% of human prion diseases.¹ Prion diseases have a broad spectrum of clinical manifestations, including dementia, ataxia, parkinsonism, myoclonus, insomnia, paresthesias, and abnormal or changed behavior.⁴ Given the protean clinical manifestations of prion diseases and rarity, the diagnosis is challenging to make antemortem. One recent study showed that most patients receive about 4 misdiagnoses and are often two-thirds of the way through their disease course before the correct diagnosis of sporadic CJD is made.⁵

• Rapidly progressive dementias (RPD) are characterized by cognitive decline over weeks to months. The RPD differential diagnosis includes fulminant forms of common neurodegenerative disorders (eg, Alzheimer’s disease, dementia with Lewy bodies, frontotemporal dementia spectrum), autoimmune encephalidites, CNS cancers, and prion disease.
• Sporadic CJD is the most common human prion disease. It is a rare neurodegenerative condition with onset usually between the ages of 50 and 70 years, and most commonly manifests with rapidly progressive dementia, ataxia, and myoclonus.
• Because of its protean manifestations, the diagnosis of CJD is difficult to make antemortem, and diagnosis is often delayed. Specialist evaluation of brain MRI DWI sequences and new CSF diagnostic tests may allow for earlier diagnosis, which has management and infection control implications.

Disclosure

Dr. Dhaliwal reports receiving honoraria from ISMIE Mutual Insurance Company and Physicians’ Reciprocal Insurers. Dr Geschwind’s institution has received R01 grant funding from NIH/NIA; and Alliance Biosecure and the Michael J Homer Family Fund as paid money to his institution, Dr Geschwind has received consulting fees or honoraria from Best Doctors, Kendall Brill & Kelly, CJD Foundation, and Tau Consortium; Dr Geschwind is a consultant for Gerson Lehrman Group, Biohaven Pharmaceuticals, and Advance Medical, outside the submitted work; has grants/grantspending with Quest, Cure PSP, and Tau Consortium, and received payment for lectures from Multiple Grand Rounds Lectures, outside the submitted work. Dr Saint is on a medical advisory board of Doximity, has received honorarium for being a member of the medical advisory board; he is also on the scientifice advisory board of Jvion. Dr Safdar’s institution has received a grant from the VA Patient Safety Center.

Clinician educators face numerous obstacles to their joint mission of facilitating learning while also ensuring high-quality and patient-centered care. Time constraints, including the institution of house officer duty hour limitations,¹ shorter lengths of stay for hospitalized patients,² and competing career responsibilities, combine to create a dynamic learning environment. Additionally, clinician educators must balance the autonomy of their learners with the safety of their patients. They must teach to multiple learning levels and work collaboratively with multiple disciplines to foster an effective team-based approach to patient care. Yet, many clinician educators have no formal training in pedagogical methods.³ Such challenges necessitate increased attention to the work of excellent clinician educators and their respective teaching approaches.

Many studies of clinical teaching rely primarily on survey data of attributes of good clinical teachers.^3-7 While some studies have incorporated direct observations of teaching^8,9 or interviews with clinician educators or learners,^10,11 few have incorporated multiple perspectives from the current team and from former learners in order to provide a comprehensive picture of team-based learning.¹²

The goal of this study was to gain a thorough understanding, through multiple perspectives, of the techniques and behaviors used by exemplary educators within actual clinical environments. We studied attitudes, behaviors, and approaches of 12 such inpatient clinician educators.

Study Design and Sampling

This was a multisite study using an exploratory qualitative approach to inquiry. This approach was used to study the techniques and behaviors of excellent attendings during inpatient general medicine rounds. A modified snowball sampling approach¹³ was used, meaning individuals known to one member of the research team (SS) were initially contacted and asked to identify clinician educators (also referred to as attendings) for potential inclusion in the study. In an effort to identify attendings from a broad range of medical schools, the “2015 U.S. News and World Report Top Medical Schools: Research” rankings¹⁴ were also reviewed, with priority given to the top 25, as these are widely used to represent the best US hospitals. In an attempt to invite attendings from diverse institutions, additional medical schools not in the top 25 as well as historically black medical schools were also included. Division chiefs and chairs of internal medicine and/or directors of internal medicine residency programs at these schools were contacted and asked for recommendations of attendings, both within and outside their institutions, who they considered to be great inpatient teachers. In addition, key experts who have won teaching awards or were known to be specialists in the field of medical education were asked to nominate one or two other outstanding attendings.

By using this sampling method, 59 potential participants were identified. An internet search was conducted to obtain information about the potential participants and their institutions. Organizational characteristics such as geographic location, hospital size and affiliation, and patient population, as well as individual characteristics such as gender, medical education and training, and educational awards received were considered so that a diversity of organizations and backgrounds was represented. The list was narrowed down to 16 attendings who were contacted via e-mail and asked to participate. Interested participants were asked for a list of their current team members and 6 to 10 former learners to contact for interviews and focus groups. Former learners were included in an effort to better understand lasting effects on learners from their exemplary teaching attendings. A total of 12 attending physicians agreed to participate (Table 1). Literature on field methods has shown that 12 interviews are found to be adequate in accomplishing data saturation.¹⁵ Although 2 attendings were located at the same institution, we decided to include them given that both are recognized as master clinician educators and were each recommended by several individuals from various institutions. Hospitals were located throughout the US and included both university-affiliated hospitals and Veterans Affairs medical centers. Despite efforts to include physicians from historically black colleges and universities, only one attending was identified, and they declined the request to participate.

Data Collection

Observations. The one-day site visits were mainly conducted by two research team members, a physician (SS) and a medical anthropologist (MH), both of whom have extensive experience in qualitative methods. Teams were not uniform but were generally comprised of 1 attending, 1 senior medical resident, 1 to 2 interns, and approximately 2 medical students. Occasionally, a pharmacist, clinical assistant, or other health professional accompanied the team on rounds. Not infrequently, the bedside nurse would explicitly be included in the discussion regarding his or her specific patient. Each site visit began with observing attendings (N = 12) and current learners (N = 57) during rounds. Each research team member recorded their own observations via handwritten field notes, paying particular attention to group interactions, teaching approach, conversations occurring within and peripheral to the team, patient-team interactions, and the physical environment. By standing outside of the medical team circle and remaining silent during rounds, research team members remained unobtrusive to the discussion and process of rounds. Materials the attendings used during their teaching rounds were also documented and collected. Rounds generally lasted 2 to 3 hours. After each site visit, the research team met to compare and combine field notes.

Interviews and Focus Groups. The research team then conducted individual, semi-structured interviews with the attendings, focus groups with their current team (N = 46), and interviews or focus groups with their former learners (N = 26; Supplement 1). Eleven of the current team members observed during rounds were unable to participate in the focus groups due to clinical duties. Because the current learners who participated in the focus groups were also observed during rounds, the research team was able to ask them open-ended questions regarding teaching rounds and their roles as learners within this environment. Former learners who were still at the hospital participated in separate focus groups or interviews. Former learners who were no longer present at the hospital were contacted by telephone and individually interviewed by one research team member (MH). All interviews and focus groups were audio-recorded and transcribed.

This study was determined to be exempt by the University of Michigan Institutional Review Board. All participants were informed that their participation was completely voluntary and that they could terminate their involvement at any time.

Data Analysis

Data were analyzed using a thematic analysis approach.¹⁶ Thematic analysis entails reading through the data to identify patterns (and create codes) that relate to behaviors, experiences, meanings, and activities. Once patterns have been identified, they are grouped according to similarity into themes, which help to further explain the findings.¹⁷

After the first site visit was completed, the research team members that participated (SS and MH) met to develop initial ideas about meanings and possible patterns. All transcripts were read by one team member (MH) and, based on review of the data, codes were developed, defined, and documented in a codebook. This process was repeated after every site visit using the codebook to expand or combine codes and refine definitions as necessary. If a new code was added, the previously coded data were reviewed to apply the new code. NVivo® 10 software (QSR International; Melbourne, Australia) was used to manage the data.

Once all field notes and transcripts were coded (MH), the code reports, which list all data described within a specific code, were run to ensure consistency and identify relationships between codes. Once coding was verified, codes were grouped based on similarities and relationships into salient themes by 3 members of the research team (NH, MH, and SM). Themes, along with their supporting codes, were then further defined to understand how these attendings worked to facilitate excellent teaching in clinical settings.

The coded interview data and field notes were categorized into broad, overlapping themes. Three of these major themes include (1) fostering positive relationships, (2) patient-centered teaching, and (3) collaboration and coaching. Table 2 lists each theme, salient behaviors, examples, and selected quotes that further elucidate its meaning.

Fostering Positive Relationships

Attending physicians took observable steps to develop positive relationships with their team members, which in turn created a safe learning environment. For instance, attendings used learners’ first names, demonstrated interest in their well-being, deployed humor, and generally displayed informal actions—uncrossed arms, “fist bump” when recognizing learners’ success, standing outside the circle of team members and leaning in to listen—during learner interactions. Attendings also made it a priority to get to know individuals on a personal level. As one current learner put it, “He asks about where we are from. He will try to find some kind of connection that he can establish with not only each of the team members but also with each of the patients.”

Additionally, attendings built positive relationships with their learners by responding thoughtfully to their input, even when learners’ evaluations of patients required modification. In turn, learners reported feeling safe to ask questions, admit uncertainty, and respectfully disagree with their attendings. As one attending reflected, “If I can get them into a place where they feel like the learning environment is someplace where they can make a mistake and know that that mistake does not necessarily mean that it’s going to cost them in their evaluation part, then I feel like that’s why it’s important.”

To build rapport and create a safe learning environment, attendings used a number of strategies to position themselves as learners alongside their team members. For instance, attendings indicated that they wanted their ideas questioned because they saw it as an opportunity to learn. Moreover, in conversations with learners, attendings demonstrated humility, admitting when they did not know something. One former learner noted, “There have been times when he has asked [a] question…nobody knows and then he admits that he doesn’t know either. So everybody goes and looks it up…The whole thing turns out to be a fun learning experience.”

Attendings demonstrated respect for their team members’ time by reading about patients before rounds, identifying learning opportunities during rounds, and integrating teaching points into the daily work of patient care. Teaching was not relegated exclusively to the conference room or confined to the traditional “chalk talk” before or after rounds but rather was assimilated into daily workflow. They appeared to be responsive to the needs of individual patients and the team, which allowed attendings to both directly oversee their patients’ care and overcome the challenges of multiple competing demands for time. The importance of this approach was made clear by one current learner who stated “…she does prepare before, especially you know on call days, she does prepare for the new patients before coming in to staff, which is really appreciated… it saves a lot of time on rounds.”

Attendings also included other health professionals in team discussions. Attendings used many of the same relationship-building techniques with these professionals as they did with learners and patients. They consistently asked these professionals to provide insight and direction in patients’ plans of care. A former learner commented, “He always asks the [nurse] what is her impression of the patient...he truly values the [nurse’s] opinion of the patient.” One attending reiterated this approach, stating “I don’t want them to think that anything I have to say is more valuable than our pharmacist or the [nurse].”

Patient-Centered Teaching

Attending physicians modeled numerous teaching techniques that focused learning around the patient. Attendings knew their patients well through review of the medical records, discussion with the patient, and personal examination. This preparation allowed attendings to focus on key teaching points in the context of the patient. One former learner noted, “He tended to bring up a variety of things that really fit well into the clinical scenario. So whether that is talking about what is the differential for a new symptom that just came up for this patient or kind of here is a new paper talking about this condition or maybe some other pearl of physical exam for a patient that has a certain physical condition.”

Attendings served as effective role models by being directly involved in examining and talking with patients as well as demonstrating excellent physical examination and communication techniques. One current learner articulated the importance of learning these skills by observing them done well: “I think he teaches by example and by doing, again, those little things: being attentive to the patients and being very careful during exams…I think those are things that you teach people by doing them, not by saying you need to do this better during the patient encounter.”

Collaboration and Coaching

Attending physicians used varied collaboration and coaching techniques to facilitate learning across the entire care team. During rounds, attendings utilized visual aids to reinforce key concepts and simplify complex topics. They also collaborated by using discussion rather than lecture to engage with team members. For instance, attendings used Socratic questioning, asking questions that lead learners through critical thinking and allow them to solve problems themselves, to guide learners’ decision-making. One former learner reported, “He never gives you the answer, and he always asks your opinion; ‘So what are your thoughts on this?’”

Coaching for success, rather than directing the various team members, was emphasized. Attendings did not wish to be seen as the “leaders” of the team. During rounds, one attending was noted to explain his role in ensuring that the team was building connections with others: “When we have a bad outcome, if it feels like your soul has been ripped out, then you’ve done something right. You’ve made that connection with the patient. My job, as your coach, was to build communication between all of us so we feel vested in each other and our patients.”

Attendings also fostered clinical reasoning skills in their learners by encouraging them to verbalize their thought processes aloud in order to clarify and check for understanding. Attendings also placed emphasis not simply on memorizing content but rather prioritization of the patient’s problems and thinking step by step through individual medical problems. One current learner applauded an attending who could “come up with schematics of how to approach problems rather than feeding us factual information of this paper or this trial.”

Additionally, attendings facilitated learning across the entire care team by differentiating their teaching to meet the needs of multiple learning levels. While the entire team was explicitly included in the learning process, attendings encouraged learners to play various roles, execute tasks, and answer questions depending on their educational level. Attendings positioned learners as leaders of the team by allowing them to talk without interruption and by encouraging them to take ownership of their patients’ care. One former learner stated, “She set expectations…we would be the ones who would be running the team, that you know it would very much be our team and that she is there to advise us and provide supervision but also safety for the patients as well.”

This study reveals the complex ways effective attendings build rapport, create a safe learning environment, utilize patient-centered teaching strategies, and engage in collaboration and coaching with all members of the team. These findings provide a framework of shared themes and their salient behaviors that may influence the success of inpatient general medicine clinician educators (Table 3).

There is a broad and voluminous literature on the subject of outstanding clinical teaching characteristics, much of which has shaped various faculty development curricula for decades. This study sought not to identify novel approaches of inpatient teaching necessarily but rather to closely examine the techniques and behaviors of clinician educators identified as exemplary. The findings affirm and reinforce the numerous, well-documented lists of personal attributes, techniques, and behaviors that resonate with learners, including creating a positive environment, demonstrating enthusiasm and interest in the learner, reading facial expressions, being student-centered, maintaining a high level of clinical knowledge, and utilizing effective communication skills.^18-24 The strengths of this study lie within the nuanced and rich observations and discussions that move beyond learners’ Likert scale evaluations and responses.^3-7,12 Input was sought from multiple perspectives on the care team, which provided detail from key stakeholders. Out of these comprehensive data arose several conclusions that extend the research literature on medical education.

In their seminal review, Sutkin et al.¹⁸ demonstrate that two thirds of characteristics of outstanding clinical teachers are “noncognitive” and that, “Perhaps what makes a clinical educator truly great depends less on the acquisition of cognitive skills such as medical knowledge and formulating learning objectives, and more on inherent, relationship-based, noncognitive attributes. Whereas cognitive abilities generally involve skills that may be taught and learned, albeit with difficulty, noncognitive abilities represent personal attributes, such as relationship skills, personality types, and emotional states, which are more difficult to develop and teach.”¹⁸ Our study, thus, adds to the literature by (1) highlighting examples of techniques and behaviors that encompass the crucial “noncognitive” arena and (2) informing best practices in teaching clinical medicine, especially those that resonate with learners, for future faculty development.

The findings highlight the role that relationships play in the teaching and learning of team-based medicine. Building rapport and sustaining successful relationships are cornerstones of effective teaching.¹⁸ For the attendings in this study, this manifested in observable, tangible behaviors such as greeting others by name, joking, using physical touch, and actively involving all team members, regardless of role or level of education. Previous literature has highlighted the importance of showing interest in learners.^7,19,25-27 This study provides multiple and varied examples of ways in which interest might be displayed.

For patients, the critical role of relationships was evidenced through rapport building and attention to patients as people outside their acute hospitalization. For instance, attendings regularly put patients’ medical issues into context and anticipated future outpatient challenges. To the authors’ knowledge, previous scholarship has not significantly emphasized this form of contextualized medicine, which involves the mindful consideration of the ongoing needs patients may experience upon transitions of care.

Several participants highlighted humility as an important characteristic of effective clinician educators. Attendings recognized that the field produces more new knowledge than can possibly be assimilated and that uncertainty is a mainstay of modern medical care. Attendings frequently utilized self-deprecation to acknowledge doubt, a technique that created a collaborative environment in which learners also felt safe to ask questions. These findings support the viewpoints by Reilly and Beckman that humility and an appreciation for questions and push-back from learners encourage lifelong learning through role modeling.^19,23 In responding to the interviewer’s question “And what happens when [the attending] is wrong?” one learner simply stated, “He makes fun of himself.”

This study has several limitations. First, it was conducted in a limited number of US based healthcare systems. The majority of institutions represented were larger, research intensive hospitals. While these hospitals were purposefully selected to provide a range in geography, size, type, and access to resources, the findings may differ in other settings. Second, it was conducted with a limited number of attendings and learners, which may limit the study’s generalizability. However, enough interviews were conducted to reach data saturation.¹⁵ Because evidence for a causal relationship between quality teaching and student and patient outcomes is lacking,¹⁸ we must rely on imperfect proxies for teaching excellence, including awards and recognition. This study attempted to identify exemplary educators through various means, but it is recognized that bias is likely. Third, because attendings provided lists of former learners, selection and recall biases may have been introduced, as attendings may have more readily identified former learners with whom they formed strong relationships. Fourth, focus was placed exclusively on teaching and learning within general medicine rounds. This was because there would be ample opportunity for teaching on this service, the structure of the teams and the types of patients would be comparable across sites, and the principal investigator was also a general medicine attending and would have a frame of reference for these types of rounds. Due to this narrow focus, the findings may not be generalizable to other subspecialties. Fifth, attendings were selected through a nonexhaustive method. However, the multisite design, the modified snowball sampling, and the inclusion of several types of institutions in the final participant pool introduced diversity to the final list. Finally, although we cannot discount the potential role of a Hawthorne effect on our data collection, the research team did attempt to mitigate this by standing apart from the care teams and remaining unobtrusive during observations.

Using a combination of interviews, focus group discussions, and direct observation, we identified consistent techniques and behaviors of excellent teaching attendings during inpatient general medicine rounds. We hope that all levels of clinician educators may use them to elevate their own teaching.

Disclosure

Dr. Saint is on a medical advisory board of Doximity, a new social networking site for physicians, and receives an honorarium. He is also on the scientific advisory board of Jvion, a healthcare technology company. Drs. Houchens, Harrod, Moody, and Ms. Fowler have no conflicts of interest.

Clinician educators face numerous obstacles to their joint mission of facilitating learning while also ensuring high-quality and patient-centered care. Time constraints, including the institution of house officer duty hour limitations,¹ shorter lengths of stay for hospitalized patients,² and competing career responsibilities, combine to create a dynamic learning environment. Additionally, clinician educators must balance the autonomy of their learners with the safety of their patients. They must teach to multiple learning levels and work collaboratively with multiple disciplines to foster an effective team-based approach to patient care. Yet, many clinician educators have no formal training in pedagogical methods.³ Such challenges necessitate increased attention to the work of excellent clinician educators and their respective teaching approaches.

Many studies of clinical teaching rely primarily on survey data of attributes of good clinical teachers.^3-7 While some studies have incorporated direct observations of teaching^8,9 or interviews with clinician educators or learners,^10,11 few have incorporated multiple perspectives from the current team and from former learners in order to provide a comprehensive picture of team-based learning.¹²

The goal of this study was to gain a thorough understanding, through multiple perspectives, of the techniques and behaviors used by exemplary educators within actual clinical environments. We studied attitudes, behaviors, and approaches of 12 such inpatient clinician educators.

Study Design and Sampling

This was a multisite study using an exploratory qualitative approach to inquiry. This approach was used to study the techniques and behaviors of excellent attendings during inpatient general medicine rounds. A modified snowball sampling approach¹³ was used, meaning individuals known to one member of the research team (SS) were initially contacted and asked to identify clinician educators (also referred to as attendings) for potential inclusion in the study. In an effort to identify attendings from a broad range of medical schools, the “2015 U.S. News and World Report Top Medical Schools: Research” rankings¹⁴ were also reviewed, with priority given to the top 25, as these are widely used to represent the best US hospitals. In an attempt to invite attendings from diverse institutions, additional medical schools not in the top 25 as well as historically black medical schools were also included. Division chiefs and chairs of internal medicine and/or directors of internal medicine residency programs at these schools were contacted and asked for recommendations of attendings, both within and outside their institutions, who they considered to be great inpatient teachers. In addition, key experts who have won teaching awards or were known to be specialists in the field of medical education were asked to nominate one or two other outstanding attendings.

By using this sampling method, 59 potential participants were identified. An internet search was conducted to obtain information about the potential participants and their institutions. Organizational characteristics such as geographic location, hospital size and affiliation, and patient population, as well as individual characteristics such as gender, medical education and training, and educational awards received were considered so that a diversity of organizations and backgrounds was represented. The list was narrowed down to 16 attendings who were contacted via e-mail and asked to participate. Interested participants were asked for a list of their current team members and 6 to 10 former learners to contact for interviews and focus groups. Former learners were included in an effort to better understand lasting effects on learners from their exemplary teaching attendings. A total of 12 attending physicians agreed to participate (Table 1). Literature on field methods has shown that 12 interviews are found to be adequate in accomplishing data saturation.¹⁵ Although 2 attendings were located at the same institution, we decided to include them given that both are recognized as master clinician educators and were each recommended by several individuals from various institutions. Hospitals were located throughout the US and included both university-affiliated hospitals and Veterans Affairs medical centers. Despite efforts to include physicians from historically black colleges and universities, only one attending was identified, and they declined the request to participate.

Data Collection

Observations. The one-day site visits were mainly conducted by two research team members, a physician (SS) and a medical anthropologist (MH), both of whom have extensive experience in qualitative methods. Teams were not uniform but were generally comprised of 1 attending, 1 senior medical resident, 1 to 2 interns, and approximately 2 medical students. Occasionally, a pharmacist, clinical assistant, or other health professional accompanied the team on rounds. Not infrequently, the bedside nurse would explicitly be included in the discussion regarding his or her specific patient. Each site visit began with observing attendings (N = 12) and current learners (N = 57) during rounds. Each research team member recorded their own observations via handwritten field notes, paying particular attention to group interactions, teaching approach, conversations occurring within and peripheral to the team, patient-team interactions, and the physical environment. By standing outside of the medical team circle and remaining silent during rounds, research team members remained unobtrusive to the discussion and process of rounds. Materials the attendings used during their teaching rounds were also documented and collected. Rounds generally lasted 2 to 3 hours. After each site visit, the research team met to compare and combine field notes.

Interviews and Focus Groups. The research team then conducted individual, semi-structured interviews with the attendings, focus groups with their current team (N = 46), and interviews or focus groups with their former learners (N = 26; Supplement 1). Eleven of the current team members observed during rounds were unable to participate in the focus groups due to clinical duties. Because the current learners who participated in the focus groups were also observed during rounds, the research team was able to ask them open-ended questions regarding teaching rounds and their roles as learners within this environment. Former learners who were still at the hospital participated in separate focus groups or interviews. Former learners who were no longer present at the hospital were contacted by telephone and individually interviewed by one research team member (MH). All interviews and focus groups were audio-recorded and transcribed.

This study was determined to be exempt by the University of Michigan Institutional Review Board. All participants were informed that their participation was completely voluntary and that they could terminate their involvement at any time.

Data Analysis

Data were analyzed using a thematic analysis approach.¹⁶ Thematic analysis entails reading through the data to identify patterns (and create codes) that relate to behaviors, experiences, meanings, and activities. Once patterns have been identified, they are grouped according to similarity into themes, which help to further explain the findings.¹⁷

After the first site visit was completed, the research team members that participated (SS and MH) met to develop initial ideas about meanings and possible patterns. All transcripts were read by one team member (MH) and, based on review of the data, codes were developed, defined, and documented in a codebook. This process was repeated after every site visit using the codebook to expand or combine codes and refine definitions as necessary. If a new code was added, the previously coded data were reviewed to apply the new code. NVivo® 10 software (QSR International; Melbourne, Australia) was used to manage the data.

Once all field notes and transcripts were coded (MH), the code reports, which list all data described within a specific code, were run to ensure consistency and identify relationships between codes. Once coding was verified, codes were grouped based on similarities and relationships into salient themes by 3 members of the research team (NH, MH, and SM). Themes, along with their supporting codes, were then further defined to understand how these attendings worked to facilitate excellent teaching in clinical settings.

The coded interview data and field notes were categorized into broad, overlapping themes. Three of these major themes include (1) fostering positive relationships, (2) patient-centered teaching, and (3) collaboration and coaching. Table 2 lists each theme, salient behaviors, examples, and selected quotes that further elucidate its meaning.

Fostering Positive Relationships

Attending physicians took observable steps to develop positive relationships with their team members, which in turn created a safe learning environment. For instance, attendings used learners’ first names, demonstrated interest in their well-being, deployed humor, and generally displayed informal actions—uncrossed arms, “fist bump” when recognizing learners’ success, standing outside the circle of team members and leaning in to listen—during learner interactions. Attendings also made it a priority to get to know individuals on a personal level. As one current learner put it, “He asks about where we are from. He will try to find some kind of connection that he can establish with not only each of the team members but also with each of the patients.”

Additionally, attendings built positive relationships with their learners by responding thoughtfully to their input, even when learners’ evaluations of patients required modification. In turn, learners reported feeling safe to ask questions, admit uncertainty, and respectfully disagree with their attendings. As one attending reflected, “If I can get them into a place where they feel like the learning environment is someplace where they can make a mistake and know that that mistake does not necessarily mean that it’s going to cost them in their evaluation part, then I feel like that’s why it’s important.”

To build rapport and create a safe learning environment, attendings used a number of strategies to position themselves as learners alongside their team members. For instance, attendings indicated that they wanted their ideas questioned because they saw it as an opportunity to learn. Moreover, in conversations with learners, attendings demonstrated humility, admitting when they did not know something. One former learner noted, “There have been times when he has asked [a] question…nobody knows and then he admits that he doesn’t know either. So everybody goes and looks it up…The whole thing turns out to be a fun learning experience.”

Attendings demonstrated respect for their team members’ time by reading about patients before rounds, identifying learning opportunities during rounds, and integrating teaching points into the daily work of patient care. Teaching was not relegated exclusively to the conference room or confined to the traditional “chalk talk” before or after rounds but rather was assimilated into daily workflow. They appeared to be responsive to the needs of individual patients and the team, which allowed attendings to both directly oversee their patients’ care and overcome the challenges of multiple competing demands for time. The importance of this approach was made clear by one current learner who stated “…she does prepare before, especially you know on call days, she does prepare for the new patients before coming in to staff, which is really appreciated… it saves a lot of time on rounds.”

Attendings also included other health professionals in team discussions. Attendings used many of the same relationship-building techniques with these professionals as they did with learners and patients. They consistently asked these professionals to provide insight and direction in patients’ plans of care. A former learner commented, “He always asks the [nurse] what is her impression of the patient...he truly values the [nurse’s] opinion of the patient.” One attending reiterated this approach, stating “I don’t want them to think that anything I have to say is more valuable than our pharmacist or the [nurse].”

Patient-Centered Teaching

Attending physicians modeled numerous teaching techniques that focused learning around the patient. Attendings knew their patients well through review of the medical records, discussion with the patient, and personal examination. This preparation allowed attendings to focus on key teaching points in the context of the patient. One former learner noted, “He tended to bring up a variety of things that really fit well into the clinical scenario. So whether that is talking about what is the differential for a new symptom that just came up for this patient or kind of here is a new paper talking about this condition or maybe some other pearl of physical exam for a patient that has a certain physical condition.”

Attendings served as effective role models by being directly involved in examining and talking with patients as well as demonstrating excellent physical examination and communication techniques. One current learner articulated the importance of learning these skills by observing them done well: “I think he teaches by example and by doing, again, those little things: being attentive to the patients and being very careful during exams…I think those are things that you teach people by doing them, not by saying you need to do this better during the patient encounter.”

Collaboration and Coaching

Attending physicians used varied collaboration and coaching techniques to facilitate learning across the entire care team. During rounds, attendings utilized visual aids to reinforce key concepts and simplify complex topics. They also collaborated by using discussion rather than lecture to engage with team members. For instance, attendings used Socratic questioning, asking questions that lead learners through critical thinking and allow them to solve problems themselves, to guide learners’ decision-making. One former learner reported, “He never gives you the answer, and he always asks your opinion; ‘So what are your thoughts on this?’”

Coaching for success, rather than directing the various team members, was emphasized. Attendings did not wish to be seen as the “leaders” of the team. During rounds, one attending was noted to explain his role in ensuring that the team was building connections with others: “When we have a bad outcome, if it feels like your soul has been ripped out, then you’ve done something right. You’ve made that connection with the patient. My job, as your coach, was to build communication between all of us so we feel vested in each other and our patients.”

Attendings also fostered clinical reasoning skills in their learners by encouraging them to verbalize their thought processes aloud in order to clarify and check for understanding. Attendings also placed emphasis not simply on memorizing content but rather prioritization of the patient’s problems and thinking step by step through individual medical problems. One current learner applauded an attending who could “come up with schematics of how to approach problems rather than feeding us factual information of this paper or this trial.”

Additionally, attendings facilitated learning across the entire care team by differentiating their teaching to meet the needs of multiple learning levels. While the entire team was explicitly included in the learning process, attendings encouraged learners to play various roles, execute tasks, and answer questions depending on their educational level. Attendings positioned learners as leaders of the team by allowing them to talk without interruption and by encouraging them to take ownership of their patients’ care. One former learner stated, “She set expectations…we would be the ones who would be running the team, that you know it would very much be our team and that she is there to advise us and provide supervision but also safety for the patients as well.”

This study reveals the complex ways effective attendings build rapport, create a safe learning environment, utilize patient-centered teaching strategies, and engage in collaboration and coaching with all members of the team. These findings provide a framework of shared themes and their salient behaviors that may influence the success of inpatient general medicine clinician educators (Table 3).

There is a broad and voluminous literature on the subject of outstanding clinical teaching characteristics, much of which has shaped various faculty development curricula for decades. This study sought not to identify novel approaches of inpatient teaching necessarily but rather to closely examine the techniques and behaviors of clinician educators identified as exemplary. The findings affirm and reinforce the numerous, well-documented lists of personal attributes, techniques, and behaviors that resonate with learners, including creating a positive environment, demonstrating enthusiasm and interest in the learner, reading facial expressions, being student-centered, maintaining a high level of clinical knowledge, and utilizing effective communication skills.^18-24 The strengths of this study lie within the nuanced and rich observations and discussions that move beyond learners’ Likert scale evaluations and responses.^3-7,12 Input was sought from multiple perspectives on the care team, which provided detail from key stakeholders. Out of these comprehensive data arose several conclusions that extend the research literature on medical education.

In their seminal review, Sutkin et al.¹⁸ demonstrate that two thirds of characteristics of outstanding clinical teachers are “noncognitive” and that, “Perhaps what makes a clinical educator truly great depends less on the acquisition of cognitive skills such as medical knowledge and formulating learning objectives, and more on inherent, relationship-based, noncognitive attributes. Whereas cognitive abilities generally involve skills that may be taught and learned, albeit with difficulty, noncognitive abilities represent personal attributes, such as relationship skills, personality types, and emotional states, which are more difficult to develop and teach.”¹⁸ Our study, thus, adds to the literature by (1) highlighting examples of techniques and behaviors that encompass the crucial “noncognitive” arena and (2) informing best practices in teaching clinical medicine, especially those that resonate with learners, for future faculty development.

The findings highlight the role that relationships play in the teaching and learning of team-based medicine. Building rapport and sustaining successful relationships are cornerstones of effective teaching.¹⁸ For the attendings in this study, this manifested in observable, tangible behaviors such as greeting others by name, joking, using physical touch, and actively involving all team members, regardless of role or level of education. Previous literature has highlighted the importance of showing interest in learners.^7,19,25-27 This study provides multiple and varied examples of ways in which interest might be displayed.

For patients, the critical role of relationships was evidenced through rapport building and attention to patients as people outside their acute hospitalization. For instance, attendings regularly put patients’ medical issues into context and anticipated future outpatient challenges. To the authors’ knowledge, previous scholarship has not significantly emphasized this form of contextualized medicine, which involves the mindful consideration of the ongoing needs patients may experience upon transitions of care.

Several participants highlighted humility as an important characteristic of effective clinician educators. Attendings recognized that the field produces more new knowledge than can possibly be assimilated and that uncertainty is a mainstay of modern medical care. Attendings frequently utilized self-deprecation to acknowledge doubt, a technique that created a collaborative environment in which learners also felt safe to ask questions. These findings support the viewpoints by Reilly and Beckman that humility and an appreciation for questions and push-back from learners encourage lifelong learning through role modeling.^19,23 In responding to the interviewer’s question “And what happens when [the attending] is wrong?” one learner simply stated, “He makes fun of himself.”

This study has several limitations. First, it was conducted in a limited number of US based healthcare systems. The majority of institutions represented were larger, research intensive hospitals. While these hospitals were purposefully selected to provide a range in geography, size, type, and access to resources, the findings may differ in other settings. Second, it was conducted with a limited number of attendings and learners, which may limit the study’s generalizability. However, enough interviews were conducted to reach data saturation.¹⁵ Because evidence for a causal relationship between quality teaching and student and patient outcomes is lacking,¹⁸ we must rely on imperfect proxies for teaching excellence, including awards and recognition. This study attempted to identify exemplary educators through various means, but it is recognized that bias is likely. Third, because attendings provided lists of former learners, selection and recall biases may have been introduced, as attendings may have more readily identified former learners with whom they formed strong relationships. Fourth, focus was placed exclusively on teaching and learning within general medicine rounds. This was because there would be ample opportunity for teaching on this service, the structure of the teams and the types of patients would be comparable across sites, and the principal investigator was also a general medicine attending and would have a frame of reference for these types of rounds. Due to this narrow focus, the findings may not be generalizable to other subspecialties. Fifth, attendings were selected through a nonexhaustive method. However, the multisite design, the modified snowball sampling, and the inclusion of several types of institutions in the final participant pool introduced diversity to the final list. Finally, although we cannot discount the potential role of a Hawthorne effect on our data collection, the research team did attempt to mitigate this by standing apart from the care teams and remaining unobtrusive during observations.

Using a combination of interviews, focus group discussions, and direct observation, we identified consistent techniques and behaviors of excellent teaching attendings during inpatient general medicine rounds. We hope that all levels of clinician educators may use them to elevate their own teaching.

Disclosure

Dr. Saint is on a medical advisory board of Doximity, a new social networking site for physicians, and receives an honorarium. He is also on the scientific advisory board of Jvion, a healthcare technology company. Drs. Houchens, Harrod, Moody, and Ms. Fowler have no conflicts of interest.

Clinician educators face numerous obstacles to their joint mission of facilitating learning while also ensuring high-quality and patient-centered care. Time constraints, including the institution of house officer duty hour limitations,¹ shorter lengths of stay for hospitalized patients,² and competing career responsibilities, combine to create a dynamic learning environment. Additionally, clinician educators must balance the autonomy of their learners with the safety of their patients. They must teach to multiple learning levels and work collaboratively with multiple disciplines to foster an effective team-based approach to patient care. Yet, many clinician educators have no formal training in pedagogical methods.³ Such challenges necessitate increased attention to the work of excellent clinician educators and their respective teaching approaches.

Many studies of clinical teaching rely primarily on survey data of attributes of good clinical teachers.^3-7 While some studies have incorporated direct observations of teaching^8,9 or interviews with clinician educators or learners,^10,11 few have incorporated multiple perspectives from the current team and from former learners in order to provide a comprehensive picture of team-based learning.¹²

The goal of this study was to gain a thorough understanding, through multiple perspectives, of the techniques and behaviors used by exemplary educators within actual clinical environments. We studied attitudes, behaviors, and approaches of 12 such inpatient clinician educators.

Study Design and Sampling

This was a multisite study using an exploratory qualitative approach to inquiry. This approach was used to study the techniques and behaviors of excellent attendings during inpatient general medicine rounds. A modified snowball sampling approach¹³ was used, meaning individuals known to one member of the research team (SS) were initially contacted and asked to identify clinician educators (also referred to as attendings) for potential inclusion in the study. In an effort to identify attendings from a broad range of medical schools, the “2015 U.S. News and World Report Top Medical Schools: Research” rankings¹⁴ were also reviewed, with priority given to the top 25, as these are widely used to represent the best US hospitals. In an attempt to invite attendings from diverse institutions, additional medical schools not in the top 25 as well as historically black medical schools were also included. Division chiefs and chairs of internal medicine and/or directors of internal medicine residency programs at these schools were contacted and asked for recommendations of attendings, both within and outside their institutions, who they considered to be great inpatient teachers. In addition, key experts who have won teaching awards or were known to be specialists in the field of medical education were asked to nominate one or two other outstanding attendings.

By using this sampling method, 59 potential participants were identified. An internet search was conducted to obtain information about the potential participants and their institutions. Organizational characteristics such as geographic location, hospital size and affiliation, and patient population, as well as individual characteristics such as gender, medical education and training, and educational awards received were considered so that a diversity of organizations and backgrounds was represented. The list was narrowed down to 16 attendings who were contacted via e-mail and asked to participate. Interested participants were asked for a list of their current team members and 6 to 10 former learners to contact for interviews and focus groups. Former learners were included in an effort to better understand lasting effects on learners from their exemplary teaching attendings. A total of 12 attending physicians agreed to participate (Table 1). Literature on field methods has shown that 12 interviews are found to be adequate in accomplishing data saturation.¹⁵ Although 2 attendings were located at the same institution, we decided to include them given that both are recognized as master clinician educators and were each recommended by several individuals from various institutions. Hospitals were located throughout the US and included both university-affiliated hospitals and Veterans Affairs medical centers. Despite efforts to include physicians from historically black colleges and universities, only one attending was identified, and they declined the request to participate.

Data Collection

Observations. The one-day site visits were mainly conducted by two research team members, a physician (SS) and a medical anthropologist (MH), both of whom have extensive experience in qualitative methods. Teams were not uniform but were generally comprised of 1 attending, 1 senior medical resident, 1 to 2 interns, and approximately 2 medical students. Occasionally, a pharmacist, clinical assistant, or other health professional accompanied the team on rounds. Not infrequently, the bedside nurse would explicitly be included in the discussion regarding his or her specific patient. Each site visit began with observing attendings (N = 12) and current learners (N = 57) during rounds. Each research team member recorded their own observations via handwritten field notes, paying particular attention to group interactions, teaching approach, conversations occurring within and peripheral to the team, patient-team interactions, and the physical environment. By standing outside of the medical team circle and remaining silent during rounds, research team members remained unobtrusive to the discussion and process of rounds. Materials the attendings used during their teaching rounds were also documented and collected. Rounds generally lasted 2 to 3 hours. After each site visit, the research team met to compare and combine field notes.

Interviews and Focus Groups. The research team then conducted individual, semi-structured interviews with the attendings, focus groups with their current team (N = 46), and interviews or focus groups with their former learners (N = 26; Supplement 1). Eleven of the current team members observed during rounds were unable to participate in the focus groups due to clinical duties. Because the current learners who participated in the focus groups were also observed during rounds, the research team was able to ask them open-ended questions regarding teaching rounds and their roles as learners within this environment. Former learners who were still at the hospital participated in separate focus groups or interviews. Former learners who were no longer present at the hospital were contacted by telephone and individually interviewed by one research team member (MH). All interviews and focus groups were audio-recorded and transcribed.

This study was determined to be exempt by the University of Michigan Institutional Review Board. All participants were informed that their participation was completely voluntary and that they could terminate their involvement at any time.

Data Analysis

Data were analyzed using a thematic analysis approach.¹⁶ Thematic analysis entails reading through the data to identify patterns (and create codes) that relate to behaviors, experiences, meanings, and activities. Once patterns have been identified, they are grouped according to similarity into themes, which help to further explain the findings.¹⁷

After the first site visit was completed, the research team members that participated (SS and MH) met to develop initial ideas about meanings and possible patterns. All transcripts were read by one team member (MH) and, based on review of the data, codes were developed, defined, and documented in a codebook. This process was repeated after every site visit using the codebook to expand or combine codes and refine definitions as necessary. If a new code was added, the previously coded data were reviewed to apply the new code. NVivo® 10 software (QSR International; Melbourne, Australia) was used to manage the data.

Once all field notes and transcripts were coded (MH), the code reports, which list all data described within a specific code, were run to ensure consistency and identify relationships between codes. Once coding was verified, codes were grouped based on similarities and relationships into salient themes by 3 members of the research team (NH, MH, and SM). Themes, along with their supporting codes, were then further defined to understand how these attendings worked to facilitate excellent teaching in clinical settings.

The coded interview data and field notes were categorized into broad, overlapping themes. Three of these major themes include (1) fostering positive relationships, (2) patient-centered teaching, and (3) collaboration and coaching. Table 2 lists each theme, salient behaviors, examples, and selected quotes that further elucidate its meaning.

Fostering Positive Relationships

Attending physicians took observable steps to develop positive relationships with their team members, which in turn created a safe learning environment. For instance, attendings used learners’ first names, demonstrated interest in their well-being, deployed humor, and generally displayed informal actions—uncrossed arms, “fist bump” when recognizing learners’ success, standing outside the circle of team members and leaning in to listen—during learner interactions. Attendings also made it a priority to get to know individuals on a personal level. As one current learner put it, “He asks about where we are from. He will try to find some kind of connection that he can establish with not only each of the team members but also with each of the patients.”

Additionally, attendings built positive relationships with their learners by responding thoughtfully to their input, even when learners’ evaluations of patients required modification. In turn, learners reported feeling safe to ask questions, admit uncertainty, and respectfully disagree with their attendings. As one attending reflected, “If I can get them into a place where they feel like the learning environment is someplace where they can make a mistake and know that that mistake does not necessarily mean that it’s going to cost them in their evaluation part, then I feel like that’s why it’s important.”

To build rapport and create a safe learning environment, attendings used a number of strategies to position themselves as learners alongside their team members. For instance, attendings indicated that they wanted their ideas questioned because they saw it as an opportunity to learn. Moreover, in conversations with learners, attendings demonstrated humility, admitting when they did not know something. One former learner noted, “There have been times when he has asked [a] question…nobody knows and then he admits that he doesn’t know either. So everybody goes and looks it up…The whole thing turns out to be a fun learning experience.”

Attendings demonstrated respect for their team members’ time by reading about patients before rounds, identifying learning opportunities during rounds, and integrating teaching points into the daily work of patient care. Teaching was not relegated exclusively to the conference room or confined to the traditional “chalk talk” before or after rounds but rather was assimilated into daily workflow. They appeared to be responsive to the needs of individual patients and the team, which allowed attendings to both directly oversee their patients’ care and overcome the challenges of multiple competing demands for time. The importance of this approach was made clear by one current learner who stated “…she does prepare before, especially you know on call days, she does prepare for the new patients before coming in to staff, which is really appreciated… it saves a lot of time on rounds.”

Attendings also included other health professionals in team discussions. Attendings used many of the same relationship-building techniques with these professionals as they did with learners and patients. They consistently asked these professionals to provide insight and direction in patients’ plans of care. A former learner commented, “He always asks the [nurse] what is her impression of the patient...he truly values the [nurse’s] opinion of the patient.” One attending reiterated this approach, stating “I don’t want them to think that anything I have to say is more valuable than our pharmacist or the [nurse].”

Patient-Centered Teaching

Attending physicians modeled numerous teaching techniques that focused learning around the patient. Attendings knew their patients well through review of the medical records, discussion with the patient, and personal examination. This preparation allowed attendings to focus on key teaching points in the context of the patient. One former learner noted, “He tended to bring up a variety of things that really fit well into the clinical scenario. So whether that is talking about what is the differential for a new symptom that just came up for this patient or kind of here is a new paper talking about this condition or maybe some other pearl of physical exam for a patient that has a certain physical condition.”

Attendings served as effective role models by being directly involved in examining and talking with patients as well as demonstrating excellent physical examination and communication techniques. One current learner articulated the importance of learning these skills by observing them done well: “I think he teaches by example and by doing, again, those little things: being attentive to the patients and being very careful during exams…I think those are things that you teach people by doing them, not by saying you need to do this better during the patient encounter.”

Collaboration and Coaching

Attending physicians used varied collaboration and coaching techniques to facilitate learning across the entire care team. During rounds, attendings utilized visual aids to reinforce key concepts and simplify complex topics. They also collaborated by using discussion rather than lecture to engage with team members. For instance, attendings used Socratic questioning, asking questions that lead learners through critical thinking and allow them to solve problems themselves, to guide learners’ decision-making. One former learner reported, “He never gives you the answer, and he always asks your opinion; ‘So what are your thoughts on this?’”

Coaching for success, rather than directing the various team members, was emphasized. Attendings did not wish to be seen as the “leaders” of the team. During rounds, one attending was noted to explain his role in ensuring that the team was building connections with others: “When we have a bad outcome, if it feels like your soul has been ripped out, then you’ve done something right. You’ve made that connection with the patient. My job, as your coach, was to build communication between all of us so we feel vested in each other and our patients.”

Attendings also fostered clinical reasoning skills in their learners by encouraging them to verbalize their thought processes aloud in order to clarify and check for understanding. Attendings also placed emphasis not simply on memorizing content but rather prioritization of the patient’s problems and thinking step by step through individual medical problems. One current learner applauded an attending who could “come up with schematics of how to approach problems rather than feeding us factual information of this paper or this trial.”

Additionally, attendings facilitated learning across the entire care team by differentiating their teaching to meet the needs of multiple learning levels. While the entire team was explicitly included in the learning process, attendings encouraged learners to play various roles, execute tasks, and answer questions depending on their educational level. Attendings positioned learners as leaders of the team by allowing them to talk without interruption and by encouraging them to take ownership of their patients’ care. One former learner stated, “She set expectations…we would be the ones who would be running the team, that you know it would very much be our team and that she is there to advise us and provide supervision but also safety for the patients as well.”

This study reveals the complex ways effective attendings build rapport, create a safe learning environment, utilize patient-centered teaching strategies, and engage in collaboration and coaching with all members of the team. These findings provide a framework of shared themes and their salient behaviors that may influence the success of inpatient general medicine clinician educators (Table 3).

There is a broad and voluminous literature on the subject of outstanding clinical teaching characteristics, much of which has shaped various faculty development curricula for decades. This study sought not to identify novel approaches of inpatient teaching necessarily but rather to closely examine the techniques and behaviors of clinician educators identified as exemplary. The findings affirm and reinforce the numerous, well-documented lists of personal attributes, techniques, and behaviors that resonate with learners, including creating a positive environment, demonstrating enthusiasm and interest in the learner, reading facial expressions, being student-centered, maintaining a high level of clinical knowledge, and utilizing effective communication skills.^18-24 The strengths of this study lie within the nuanced and rich observations and discussions that move beyond learners’ Likert scale evaluations and responses.^3-7,12 Input was sought from multiple perspectives on the care team, which provided detail from key stakeholders. Out of these comprehensive data arose several conclusions that extend the research literature on medical education.

In their seminal review, Sutkin et al.¹⁸ demonstrate that two thirds of characteristics of outstanding clinical teachers are “noncognitive” and that, “Perhaps what makes a clinical educator truly great depends less on the acquisition of cognitive skills such as medical knowledge and formulating learning objectives, and more on inherent, relationship-based, noncognitive attributes. Whereas cognitive abilities generally involve skills that may be taught and learned, albeit with difficulty, noncognitive abilities represent personal attributes, such as relationship skills, personality types, and emotional states, which are more difficult to develop and teach.”¹⁸ Our study, thus, adds to the literature by (1) highlighting examples of techniques and behaviors that encompass the crucial “noncognitive” arena and (2) informing best practices in teaching clinical medicine, especially those that resonate with learners, for future faculty development.

The findings highlight the role that relationships play in the teaching and learning of team-based medicine. Building rapport and sustaining successful relationships are cornerstones of effective teaching.¹⁸ For the attendings in this study, this manifested in observable, tangible behaviors such as greeting others by name, joking, using physical touch, and actively involving all team members, regardless of role or level of education. Previous literature has highlighted the importance of showing interest in learners.^7,19,25-27 This study provides multiple and varied examples of ways in which interest might be displayed.

For patients, the critical role of relationships was evidenced through rapport building and attention to patients as people outside their acute hospitalization. For instance, attendings regularly put patients’ medical issues into context and anticipated future outpatient challenges. To the authors’ knowledge, previous scholarship has not significantly emphasized this form of contextualized medicine, which involves the mindful consideration of the ongoing needs patients may experience upon transitions of care.

Several participants highlighted humility as an important characteristic of effective clinician educators. Attendings recognized that the field produces more new knowledge than can possibly be assimilated and that uncertainty is a mainstay of modern medical care. Attendings frequently utilized self-deprecation to acknowledge doubt, a technique that created a collaborative environment in which learners also felt safe to ask questions. These findings support the viewpoints by Reilly and Beckman that humility and an appreciation for questions and push-back from learners encourage lifelong learning through role modeling.^19,23 In responding to the interviewer’s question “And what happens when [the attending] is wrong?” one learner simply stated, “He makes fun of himself.”

This study has several limitations. First, it was conducted in a limited number of US based healthcare systems. The majority of institutions represented were larger, research intensive hospitals. While these hospitals were purposefully selected to provide a range in geography, size, type, and access to resources, the findings may differ in other settings. Second, it was conducted with a limited number of attendings and learners, which may limit the study’s generalizability. However, enough interviews were conducted to reach data saturation.¹⁵ Because evidence for a causal relationship between quality teaching and student and patient outcomes is lacking,¹⁸ we must rely on imperfect proxies for teaching excellence, including awards and recognition. This study attempted to identify exemplary educators through various means, but it is recognized that bias is likely. Third, because attendings provided lists of former learners, selection and recall biases may have been introduced, as attendings may have more readily identified former learners with whom they formed strong relationships. Fourth, focus was placed exclusively on teaching and learning within general medicine rounds. This was because there would be ample opportunity for teaching on this service, the structure of the teams and the types of patients would be comparable across sites, and the principal investigator was also a general medicine attending and would have a frame of reference for these types of rounds. Due to this narrow focus, the findings may not be generalizable to other subspecialties. Fifth, attendings were selected through a nonexhaustive method. However, the multisite design, the modified snowball sampling, and the inclusion of several types of institutions in the final participant pool introduced diversity to the final list. Finally, although we cannot discount the potential role of a Hawthorne effect on our data collection, the research team did attempt to mitigate this by standing apart from the care teams and remaining unobtrusive during observations.

Using a combination of interviews, focus group discussions, and direct observation, we identified consistent techniques and behaviors of excellent teaching attendings during inpatient general medicine rounds. We hope that all levels of clinician educators may use them to elevate their own teaching.

Disclosure

Dr. Saint is on a medical advisory board of Doximity, a new social networking site for physicians, and receives an honorarium. He is also on the scientific advisory board of Jvion, a healthcare technology company. Drs. Houchens, Harrod, Moody, and Ms. Fowler have no conflicts of interest.