Affiliations
University of Michigan Health System
Given name(s)
Sarah
Family name
Krein
Degrees
PhD, RN

Focused Ethnography of Diagnosis in Academic Medical Centers

Article Type
Changed
Fri, 12/06/2019 - 12:31

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.

METHODS

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).

RESULTS

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)

DISCUSSION

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 slots28,29 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.

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References

1. National Academies of Sciences, Engineering, and Medicine. 2015. Improving Diagnosis in Health Care. Washington, DC: The National Academies Press. http://www.nap.edu/21794. Accessed November 1; 2016:2015. https://doi.org/10.17226/21794.
2. Schiff GD, Hasan O, Kim S, et al. Diagnostic error in medicine: analysis of 583 physician-reported errors. Arch Intern Med. 2009;169(20):1881-1887. http://dx.doi.org/10.1001/archinternmed.2009.333. PubMed
3. Sonderegger-Iseli K, Burger S, Muntwyler J, Salomon F. Diagnostic errors in three medical eras: A necropsy study. Lancet. 2000;355(9220):2027-2031. http://dx.doi.org/10.1016/S0140-6736(00)02349-7PubMed
4. Winters B, Custer J, Galvagno SM Jr, et al. Diagnostic errors in the intensive care unit: a systematic review of autopsy studies. BMJ Qual Saf. 2012;21(11):894-902. http://dx.doi.org/10.1136/bmjqs-2012-000803. PubMed
5. Saber Tehrani AS, Lee H, Mathews SC, et al. 25-Year summary of US malpractice claims for diagnostic errors 1986-2010: an analysis from the National Practitioner Data Bank. BMJ Qual Saf. 2013;22(8):672-680. http://dx.doi.org/10.1136/bmjqs-2012-001550PubMed
6. Graber M, Gordon R, Franklin N. Reducing diagnostic errors in medicine: what’s the goal? Acad Med. 2002;77(10):981-992. http://dx.doi.org/10.1097/00001888-200210000-00009PubMed
7. Gupta A, Snyder A, Kachalia A, Flanders S, Saint S, Chopra V. Malpractice claims related to diagnostic errors in the hospital. BMJ Qual Saf. 2018;27(1):53-60. 10.1136/bmjqs-2017-006774. PubMed
8. van Noord I, Eikens MP, Hamersma AM, de Bruijne MC. Application of root cause analysis on malpractice claim files related to diagnostic failures. Qual Saf Health Care. 2010;19(6):e21. http://dx.doi.org/10.1136/qshc.2008.029801PubMed
9. Croskerry P, Petrie DA, Reilly JB, Tait G. Deciding about fast and slow decisions. Acad Med. 2014;89(2):197-200. 10.1097/ACM.0000000000000121. PubMed
10. Higginbottom GM, Pillay JJ, Boadu NY. Guidance on performing focused ethnographies with an emphasis on healthcare research. Qual Rep. 2013;18(9):1-6. https://doi.org/10.7939/R35M6287P. 
11. Savage J. Participative observation: standing in the shoes of others? Qual Health Res. 2000;10(3):324-339. http://dx.doi.org/10.1177/104973200129118471PubMed
12. Patton MQ. Qualitative Research and Evaluation Methods. 3rd ed. Thousand Oaks, CA: SAGE Publications; 2002. 
13. Harrod M, Weston LE, Robinson C, Tremblay A, Greenstone CL, Forman J. “It goes beyond good camaraderie”: A qualitative study of the process of becoming an interprofessional healthcare “teamlet.” J Interprof Care. 2016;30(3):295-300. http://dx.doi.org/10.3109/13561820.2015.1130028PubMed
14. Houchens N, Harrod M, Moody S, Fowler KE, Saint S. Techniques and behaviors associated with exemplary inpatient general medicine teaching: an exploratory qualitative study. J Hosp Med. 2017;12(7):503-509. http://dx.doi.org/10.12788/jhm.2763PubMed
15. Mulhall A. In the field: notes on observation in qualitative research. J Adv Nurs. 2003;41(3):306-313. http://dx.doi.org/10.1046/j.1365-2648.2003.02514.xPubMed
16. Zwaan L, Monteiro S, Sherbino J, Ilgen J, Howey B, Norman G. Is bias in the eye of the beholder? A vignette study to assess recognition of cognitive biases in clinical case workups. BMJ Qual Saf. 2017;26(2):104-110. http://dx.doi.org/10.1136/bmjqs-2015-005014PubMed
17. Singh H, Graber ML. Improving diagnosis in health care--the next imperative for patient safety. N Engl J Med. 2015;373(26):2493-2495. http://dx.doi.org/10.1056/NEJMp1512241PubMed
18. Croskerry P. From mindless to mindful practice--cognitive bias and clinical decision making. N Engl J Med. 2013;368(26):2445-2448. http://dx.doi.org/10.1056/NEJMp1303712PubMed
19. van den Berge K, Mamede S. Cognitive diagnostic error in internal medicine. Eur J Intern Med. 2013;24(6):525-529. http://dx.doi.org/10.1016/j.ejim.2013.03.006PubMed
20. Norman G, Sherbino J, Dore K, et al. The etiology of diagnostic errors: A controlled trial of system 1 versus system 2 reasoning. Acad Med. 2014;89(2):277-284. 10.1097/ACM.0000000000000105 PubMed
21. Dhaliwal G. Premature closure? Not so fast. BMJ Qual Saf. 2017;26(2):87-89. http://dx.doi.org/10.1136/bmjqs-2016-005267PubMed
22. Croskerry P, Singhal G, Mamede S. Cognitive debiasing 1: Origins of bias and theory of debiasing. BMJ Qual Saf. 2013;22(suppl 2):ii58-iiii64. http://dx.doi.org/10.1136/bmjqs-2012-001712PubMed
23. Croskerry P, Singhal G, Mamede S. Cognitive debiasing 2: Impediments to and strategies for change. BMJ Qual Saf. 2013;22(suppl 2):ii65-iiii72. http://dx.doi.org/10.1136/bmjqs-2012-001713PubMed
24. Reilly JB, Ogdie AR, Von Feldt JM, Myers JS. Teaching about how doctors think: a longitudinal curriculum in cognitive bias and diagnostic error for residents. BMJ Qual Saf. 2013;22(12):1044-1050. http://dx.doi.org/10.1136/bmjqs-2013-001987PubMed
25. Schmidt HG, Mamede S, van den Berge K, van Gog T, van Saase JL, Rikers RM. Exposure to media information about a disease can cause doctors to misdiagnose similar-looking clinical cases. Acad Med. 2014;89(2):285-291. http://dx.doi.org/10.1097/ACM.0000000000000107PubMed
26. Hess BJ, Lipner RS, Thompson V, Holmboe ES, Graber ML. Blink or think: can further reflection improve initial diagnostic impressions? Acad Med. 2015;90(1):112-118. http://dx.doi.org/10.1097/ACM.0000000000000550PubMed
27. Lambe KA, O’Reilly G, Kelly BD, Curristan S. Dual-process cognitive interventions to enhance diagnostic reasoning: A systematic review. BMJ Qual Saf. 2016;25(10):808-820. http://dx.doi.org/10.1136/bmjqs-2015-004417PubMed
28. Graber ML, Kissam S, Payne VL, et al. Cognitive interventions to reduce diagnostic error: a narrative review. BMJ Qual Saf. 2012;21(7):535-557. http://dx.doi.org/10.1136/bmjqs-2011-000149PubMed
29. McDonald KM, Matesic B, Contopoulos-Ioannidis DG, et al. Patient safety strategies targeted at diagnostic errors: a systematic review. Ann Intern Med. 2013;158(5 Pt 2):381-389. http://dx.doi.org/10.7326/0003-4819-158-5-201303051-00004PubMed
30. Wray CM, Chaudhry S, Pincavage A, et al. Resident shift handoff strategies in US internal medicine residency programs. JAMA. 2016;316(21):2273-2275. http://dx.doi.org/10.1001/jama.2016.17786PubMed
31. Choo KJ, Arora VM, Barach P, Johnson JK, Farnan JM. How do supervising physicians decide to entrust residents with unsupervised tasks? A qualitative analysis. J Hosp Med. 2014;9(3):169-175. http://dx.doi.org/10.1002/jhm.2150PubMed
32. Carayon P, Wood KE. Patient safety - the role of human factors and systems engineering. Stud Health Technol Inform. 2010;153:23-46.

 

 

 

.http://dx.doi.org/10.1001/jama.2015.13453  PubMed

34. McGlynn EA, McDonald KM, Cassel CK. Measurement is essential for improving diagnosis and reducing diagnostic error: A report from the Institute of Medicine. JAMA. 2015;314(23):2501-2502.
.http://dx.doi.org/10.1136/bmjqs-2013-001812 PubMed

33. Carayon P, Xie A, Kianfar S. Human factors and ergonomics as a patient safety practice. BMJ Qual Saf. 2014;23(3):196-205. PubMed

 

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Related Articles

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.

METHODS

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).

RESULTS

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)

DISCUSSION

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 slots28,29 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.

METHODS

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).

RESULTS

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)

DISCUSSION

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 slots28,29 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.

References

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2. Schiff GD, Hasan O, Kim S, et al. Diagnostic error in medicine: analysis of 583 physician-reported errors. Arch Intern Med. 2009;169(20):1881-1887. http://dx.doi.org/10.1001/archinternmed.2009.333. PubMed
3. Sonderegger-Iseli K, Burger S, Muntwyler J, Salomon F. Diagnostic errors in three medical eras: A necropsy study. Lancet. 2000;355(9220):2027-2031. http://dx.doi.org/10.1016/S0140-6736(00)02349-7PubMed
4. Winters B, Custer J, Galvagno SM Jr, et al. Diagnostic errors in the intensive care unit: a systematic review of autopsy studies. BMJ Qual Saf. 2012;21(11):894-902. http://dx.doi.org/10.1136/bmjqs-2012-000803. PubMed
5. Saber Tehrani AS, Lee H, Mathews SC, et al. 25-Year summary of US malpractice claims for diagnostic errors 1986-2010: an analysis from the National Practitioner Data Bank. BMJ Qual Saf. 2013;22(8):672-680. http://dx.doi.org/10.1136/bmjqs-2012-001550PubMed
6. Graber M, Gordon R, Franklin N. Reducing diagnostic errors in medicine: what’s the goal? Acad Med. 2002;77(10):981-992. http://dx.doi.org/10.1097/00001888-200210000-00009PubMed
7. Gupta A, Snyder A, Kachalia A, Flanders S, Saint S, Chopra V. Malpractice claims related to diagnostic errors in the hospital. BMJ Qual Saf. 2018;27(1):53-60. 10.1136/bmjqs-2017-006774. PubMed
8. van Noord I, Eikens MP, Hamersma AM, de Bruijne MC. Application of root cause analysis on malpractice claim files related to diagnostic failures. Qual Saf Health Care. 2010;19(6):e21. http://dx.doi.org/10.1136/qshc.2008.029801PubMed
9. Croskerry P, Petrie DA, Reilly JB, Tait G. Deciding about fast and slow decisions. Acad Med. 2014;89(2):197-200. 10.1097/ACM.0000000000000121. PubMed
10. Higginbottom GM, Pillay JJ, Boadu NY. Guidance on performing focused ethnographies with an emphasis on healthcare research. Qual Rep. 2013;18(9):1-6. https://doi.org/10.7939/R35M6287P. 
11. Savage J. Participative observation: standing in the shoes of others? Qual Health Res. 2000;10(3):324-339. http://dx.doi.org/10.1177/104973200129118471PubMed
12. Patton MQ. Qualitative Research and Evaluation Methods. 3rd ed. Thousand Oaks, CA: SAGE Publications; 2002. 
13. Harrod M, Weston LE, Robinson C, Tremblay A, Greenstone CL, Forman J. “It goes beyond good camaraderie”: A qualitative study of the process of becoming an interprofessional healthcare “teamlet.” J Interprof Care. 2016;30(3):295-300. http://dx.doi.org/10.3109/13561820.2015.1130028PubMed
14. Houchens N, Harrod M, Moody S, Fowler KE, Saint S. Techniques and behaviors associated with exemplary inpatient general medicine teaching: an exploratory qualitative study. J Hosp Med. 2017;12(7):503-509. http://dx.doi.org/10.12788/jhm.2763PubMed
15. Mulhall A. In the field: notes on observation in qualitative research. J Adv Nurs. 2003;41(3):306-313. http://dx.doi.org/10.1046/j.1365-2648.2003.02514.xPubMed
16. Zwaan L, Monteiro S, Sherbino J, Ilgen J, Howey B, Norman G. Is bias in the eye of the beholder? A vignette study to assess recognition of cognitive biases in clinical case workups. BMJ Qual Saf. 2017;26(2):104-110. http://dx.doi.org/10.1136/bmjqs-2015-005014PubMed
17. Singh H, Graber ML. Improving diagnosis in health care--the next imperative for patient safety. N Engl J Med. 2015;373(26):2493-2495. http://dx.doi.org/10.1056/NEJMp1512241PubMed
18. Croskerry P. From mindless to mindful practice--cognitive bias and clinical decision making. N Engl J Med. 2013;368(26):2445-2448. http://dx.doi.org/10.1056/NEJMp1303712PubMed
19. van den Berge K, Mamede S. Cognitive diagnostic error in internal medicine. Eur J Intern Med. 2013;24(6):525-529. http://dx.doi.org/10.1016/j.ejim.2013.03.006PubMed
20. Norman G, Sherbino J, Dore K, et al. The etiology of diagnostic errors: A controlled trial of system 1 versus system 2 reasoning. Acad Med. 2014;89(2):277-284. 10.1097/ACM.0000000000000105 PubMed
21. Dhaliwal G. Premature closure? Not so fast. BMJ Qual Saf. 2017;26(2):87-89. http://dx.doi.org/10.1136/bmjqs-2016-005267PubMed
22. Croskerry P, Singhal G, Mamede S. Cognitive debiasing 1: Origins of bias and theory of debiasing. BMJ Qual Saf. 2013;22(suppl 2):ii58-iiii64. http://dx.doi.org/10.1136/bmjqs-2012-001712PubMed
23. Croskerry P, Singhal G, Mamede S. Cognitive debiasing 2: Impediments to and strategies for change. BMJ Qual Saf. 2013;22(suppl 2):ii65-iiii72. http://dx.doi.org/10.1136/bmjqs-2012-001713PubMed
24. Reilly JB, Ogdie AR, Von Feldt JM, Myers JS. Teaching about how doctors think: a longitudinal curriculum in cognitive bias and diagnostic error for residents. BMJ Qual Saf. 2013;22(12):1044-1050. http://dx.doi.org/10.1136/bmjqs-2013-001987PubMed
25. Schmidt HG, Mamede S, van den Berge K, van Gog T, van Saase JL, Rikers RM. Exposure to media information about a disease can cause doctors to misdiagnose similar-looking clinical cases. Acad Med. 2014;89(2):285-291. http://dx.doi.org/10.1097/ACM.0000000000000107PubMed
26. Hess BJ, Lipner RS, Thompson V, Holmboe ES, Graber ML. Blink or think: can further reflection improve initial diagnostic impressions? Acad Med. 2015;90(1):112-118. http://dx.doi.org/10.1097/ACM.0000000000000550PubMed
27. Lambe KA, O’Reilly G, Kelly BD, Curristan S. Dual-process cognitive interventions to enhance diagnostic reasoning: A systematic review. BMJ Qual Saf. 2016;25(10):808-820. http://dx.doi.org/10.1136/bmjqs-2015-004417PubMed
28. Graber ML, Kissam S, Payne VL, et al. Cognitive interventions to reduce diagnostic error: a narrative review. BMJ Qual Saf. 2012;21(7):535-557. http://dx.doi.org/10.1136/bmjqs-2011-000149PubMed
29. McDonald KM, Matesic B, Contopoulos-Ioannidis DG, et al. Patient safety strategies targeted at diagnostic errors: a systematic review. Ann Intern Med. 2013;158(5 Pt 2):381-389. http://dx.doi.org/10.7326/0003-4819-158-5-201303051-00004PubMed
30. Wray CM, Chaudhry S, Pincavage A, et al. Resident shift handoff strategies in US internal medicine residency programs. JAMA. 2016;316(21):2273-2275. http://dx.doi.org/10.1001/jama.2016.17786PubMed
31. Choo KJ, Arora VM, Barach P, Johnson JK, Farnan JM. How do supervising physicians decide to entrust residents with unsupervised tasks? A qualitative analysis. J Hosp Med. 2014;9(3):169-175. http://dx.doi.org/10.1002/jhm.2150PubMed
32. Carayon P, Wood KE. Patient safety - the role of human factors and systems engineering. Stud Health Technol Inform. 2010;153:23-46.

 

 

 

.http://dx.doi.org/10.1001/jama.2015.13453  PubMed

34. McGlynn EA, McDonald KM, Cassel CK. Measurement is essential for improving diagnosis and reducing diagnostic error: A report from the Institute of Medicine. JAMA. 2015;314(23):2501-2502.
.http://dx.doi.org/10.1136/bmjqs-2013-001812 PubMed

33. Carayon P, Xie A, Kianfar S. Human factors and ergonomics as a patient safety practice. BMJ Qual Saf. 2014;23(3):196-205. PubMed

 

References

1. National Academies of Sciences, Engineering, and Medicine. 2015. Improving Diagnosis in Health Care. Washington, DC: The National Academies Press. http://www.nap.edu/21794. Accessed November 1; 2016:2015. https://doi.org/10.17226/21794.
2. Schiff GD, Hasan O, Kim S, et al. Diagnostic error in medicine: analysis of 583 physician-reported errors. Arch Intern Med. 2009;169(20):1881-1887. http://dx.doi.org/10.1001/archinternmed.2009.333. PubMed
3. Sonderegger-Iseli K, Burger S, Muntwyler J, Salomon F. Diagnostic errors in three medical eras: A necropsy study. Lancet. 2000;355(9220):2027-2031. http://dx.doi.org/10.1016/S0140-6736(00)02349-7PubMed
4. Winters B, Custer J, Galvagno SM Jr, et al. Diagnostic errors in the intensive care unit: a systematic review of autopsy studies. BMJ Qual Saf. 2012;21(11):894-902. http://dx.doi.org/10.1136/bmjqs-2012-000803. PubMed
5. Saber Tehrani AS, Lee H, Mathews SC, et al. 25-Year summary of US malpractice claims for diagnostic errors 1986-2010: an analysis from the National Practitioner Data Bank. BMJ Qual Saf. 2013;22(8):672-680. http://dx.doi.org/10.1136/bmjqs-2012-001550PubMed
6. Graber M, Gordon R, Franklin N. Reducing diagnostic errors in medicine: what’s the goal? Acad Med. 2002;77(10):981-992. http://dx.doi.org/10.1097/00001888-200210000-00009PubMed
7. Gupta A, Snyder A, Kachalia A, Flanders S, Saint S, Chopra V. Malpractice claims related to diagnostic errors in the hospital. BMJ Qual Saf. 2018;27(1):53-60. 10.1136/bmjqs-2017-006774. PubMed
8. van Noord I, Eikens MP, Hamersma AM, de Bruijne MC. Application of root cause analysis on malpractice claim files related to diagnostic failures. Qual Saf Health Care. 2010;19(6):e21. http://dx.doi.org/10.1136/qshc.2008.029801PubMed
9. Croskerry P, Petrie DA, Reilly JB, Tait G. Deciding about fast and slow decisions. Acad Med. 2014;89(2):197-200. 10.1097/ACM.0000000000000121. PubMed
10. Higginbottom GM, Pillay JJ, Boadu NY. Guidance on performing focused ethnographies with an emphasis on healthcare research. Qual Rep. 2013;18(9):1-6. https://doi.org/10.7939/R35M6287P. 
11. Savage J. Participative observation: standing in the shoes of others? Qual Health Res. 2000;10(3):324-339. http://dx.doi.org/10.1177/104973200129118471PubMed
12. Patton MQ. Qualitative Research and Evaluation Methods. 3rd ed. Thousand Oaks, CA: SAGE Publications; 2002. 
13. Harrod M, Weston LE, Robinson C, Tremblay A, Greenstone CL, Forman J. “It goes beyond good camaraderie”: A qualitative study of the process of becoming an interprofessional healthcare “teamlet.” J Interprof Care. 2016;30(3):295-300. http://dx.doi.org/10.3109/13561820.2015.1130028PubMed
14. Houchens N, Harrod M, Moody S, Fowler KE, Saint S. Techniques and behaviors associated with exemplary inpatient general medicine teaching: an exploratory qualitative study. J Hosp Med. 2017;12(7):503-509. http://dx.doi.org/10.12788/jhm.2763PubMed
15. Mulhall A. In the field: notes on observation in qualitative research. J Adv Nurs. 2003;41(3):306-313. http://dx.doi.org/10.1046/j.1365-2648.2003.02514.xPubMed
16. Zwaan L, Monteiro S, Sherbino J, Ilgen J, Howey B, Norman G. Is bias in the eye of the beholder? A vignette study to assess recognition of cognitive biases in clinical case workups. BMJ Qual Saf. 2017;26(2):104-110. http://dx.doi.org/10.1136/bmjqs-2015-005014PubMed
17. Singh H, Graber ML. Improving diagnosis in health care--the next imperative for patient safety. N Engl J Med. 2015;373(26):2493-2495. http://dx.doi.org/10.1056/NEJMp1512241PubMed
18. Croskerry P. From mindless to mindful practice--cognitive bias and clinical decision making. N Engl J Med. 2013;368(26):2445-2448. http://dx.doi.org/10.1056/NEJMp1303712PubMed
19. van den Berge K, Mamede S. Cognitive diagnostic error in internal medicine. Eur J Intern Med. 2013;24(6):525-529. http://dx.doi.org/10.1016/j.ejim.2013.03.006PubMed
20. Norman G, Sherbino J, Dore K, et al. The etiology of diagnostic errors: A controlled trial of system 1 versus system 2 reasoning. Acad Med. 2014;89(2):277-284. 10.1097/ACM.0000000000000105 PubMed
21. Dhaliwal G. Premature closure? Not so fast. BMJ Qual Saf. 2017;26(2):87-89. http://dx.doi.org/10.1136/bmjqs-2016-005267PubMed
22. Croskerry P, Singhal G, Mamede S. Cognitive debiasing 1: Origins of bias and theory of debiasing. BMJ Qual Saf. 2013;22(suppl 2):ii58-iiii64. http://dx.doi.org/10.1136/bmjqs-2012-001712PubMed
23. Croskerry P, Singhal G, Mamede S. Cognitive debiasing 2: Impediments to and strategies for change. BMJ Qual Saf. 2013;22(suppl 2):ii65-iiii72. http://dx.doi.org/10.1136/bmjqs-2012-001713PubMed
24. Reilly JB, Ogdie AR, Von Feldt JM, Myers JS. Teaching about how doctors think: a longitudinal curriculum in cognitive bias and diagnostic error for residents. BMJ Qual Saf. 2013;22(12):1044-1050. http://dx.doi.org/10.1136/bmjqs-2013-001987PubMed
25. Schmidt HG, Mamede S, van den Berge K, van Gog T, van Saase JL, Rikers RM. Exposure to media information about a disease can cause doctors to misdiagnose similar-looking clinical cases. Acad Med. 2014;89(2):285-291. http://dx.doi.org/10.1097/ACM.0000000000000107PubMed
26. Hess BJ, Lipner RS, Thompson V, Holmboe ES, Graber ML. Blink or think: can further reflection improve initial diagnostic impressions? Acad Med. 2015;90(1):112-118. http://dx.doi.org/10.1097/ACM.0000000000000550PubMed
27. Lambe KA, O’Reilly G, Kelly BD, Curristan S. Dual-process cognitive interventions to enhance diagnostic reasoning: A systematic review. BMJ Qual Saf. 2016;25(10):808-820. http://dx.doi.org/10.1136/bmjqs-2015-004417PubMed
28. Graber ML, Kissam S, Payne VL, et al. Cognitive interventions to reduce diagnostic error: a narrative review. BMJ Qual Saf. 2012;21(7):535-557. http://dx.doi.org/10.1136/bmjqs-2011-000149PubMed
29. McDonald KM, Matesic B, Contopoulos-Ioannidis DG, et al. Patient safety strategies targeted at diagnostic errors: a systematic review. Ann Intern Med. 2013;158(5 Pt 2):381-389. http://dx.doi.org/10.7326/0003-4819-158-5-201303051-00004PubMed
30. Wray CM, Chaudhry S, Pincavage A, et al. Resident shift handoff strategies in US internal medicine residency programs. JAMA. 2016;316(21):2273-2275. http://dx.doi.org/10.1001/jama.2016.17786PubMed
31. Choo KJ, Arora VM, Barach P, Johnson JK, Farnan JM. How do supervising physicians decide to entrust residents with unsupervised tasks? A qualitative analysis. J Hosp Med. 2014;9(3):169-175. http://dx.doi.org/10.1002/jhm.2150PubMed
32. Carayon P, Wood KE. Patient safety - the role of human factors and systems engineering. Stud Health Technol Inform. 2010;153:23-46.

 

 

 

.http://dx.doi.org/10.1001/jama.2015.13453  PubMed

34. McGlynn EA, McDonald KM, Cassel CK. Measurement is essential for improving diagnosis and reducing diagnostic error: A report from the Institute of Medicine. JAMA. 2015;314(23):2501-2502.
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33. Carayon P, Xie A, Kianfar S. Human factors and ergonomics as a patient safety practice. BMJ Qual Saf. 2014;23(3):196-205. PubMed

 

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Addressing the Needs of Patients With Chronic Pain

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A novel interdisciplinary team approach within a primary care setting may be a promising model for delivering effective comprehensive treatment options for patients with chronic pain.

Chronic pain is a common health care problem that remains a significant burden for the VHA.1,2 Some reports indicate that nearly 50% of VA patients report chronic pain.3,4 Both within and outside the VHA, primary care providers (PCPs) generally manage patients with chronic pain.5,6 Historically, a biomedical approach to chronic pain also included the use of opioid medications, which may have contributed to increased opioid-related morbidity and mortality especially among the veteran patient population.7-9 The use of opioids also is controversial due to concerns about adverse effects (AEs), long-term efficacy, functional outcomes, and the potential for drug abuse and addiction.10 Consequently, alternative treatment options that incorporate an interdisciplinary approach have gained significant interest among pain care providers.11 Interdisciplinary programs have been shown to improve functional status and psychological well-being and to reduce pain severity and opioid use.12-14 These benefits may persist for a decade or longer.15

Background

The Stepped Care Model for Pain Management (SCM-PM) is a specific pain treatment approach promoted by the VA National Pain Management Directive.16 This systematically adjusted approach is associated with improved patient satisfaction and health outcomes for pain and depression.17,18 At its core, the model promotes engaging patients as active participants in their care along with a team of doctors who can offer an integrated, evidence-based, multimodal, interdisciplinary treatment plan.

To successfully implement this strategy at the VA, patient aligned care teams (PACT) assess and manage patients with common pain conditions through collaboration with mental health, complementary and integrative health services, physical therapy, and other programs, such as opioid renewal clinics and pain schools.19 This collaborative care approach, which the PCP initiates, is step 1 of the SCM-PM. If initial treatment is not successful and patients are not improving as expected, specialty care consultation and collaborative comanagement through interdisciplinary pain specialty teams are sought (step 2). Finally, step 3 involves tertiary, interdisciplinary care, including access to advanced diagnostic and pain rehabilitation programs accredited by the Commission for Accreditation of Rehabilitation Facilities (CARF).

Although the advantages of interdisciplinary pain programs are clear, resource limitations as well as challenges related to competencies of the PCPs, nurses, and associated health care professionals in pain assessment and management can make implementation of these programs, including the SCM-PM, difficult for many clinics and facilities. Thus, identifying effective chronic pain models and strategies, incorporating the philosophy and key elements of interdisciplinary programs, and accounting for facility resources and capacity are all important.

At the Ann Arbor VAMC, development of a comprehensive interdisciplinary team started with the implementation of joint sessions with a clinical pharmacist and health psychologist embedded in primary care to enhance access to behavioral pain management interventions.20 This program was subsequently expanded to include a pain physician, 2 pain-focused physical therapists (PTs) and a pain nurse.

This article describes a novel team approach for providing more comprehensive, interdisciplinary care for patients with chronic pain along with the initial results for the patients who were part of an outpatient pain group program (OPGP).

Methods

Developing a more interdisciplinary pain management program included integrating different services and creating a strategy for comprehensive evaluation and management of patients with chronic pain. After patients were referred to the interdisciplinary pain clinic by their PCP, they received a systematically structured multidimensional assessment. The primary focus of this assessment was to create an individually directed treatment approach based on the patient’s responses to previous treatments and information collected from several questionnaires administered prior to evaluation. This information helped guide individual patient decision making and actively engaged patients in their care, thus following one of the central tenants of the SCM-PM model. Moreover, functional restoration was at the core of each patient’s evaluation and management. The primary focus was on nonpharmacologic treatment options that included psychological, physical, and occupational therapy; self-management; education; and complementary and alternative therapies. These modalities were offered either individually or in a group setting.

The first step after referral was an evaluation that followed the main core principles for complex disease management described by Tauben and Theodore.21 All new patients were asked to complete a 2-question pain intensity and pain interference measure, the 4-question Patient Health Questionnaire (PHQ-4), 4-question Primary Care-PTSD screening tool (PC-PTSD), and the STOP-BANG questionnaire to assess the risk for obstructive sleep apnea.22-24 Each measure allowed the physician to identify specific problem areas and formulate a treatment plan that would incorporate PTs or occupational therapists, psychologists and/or clinical specialists, and pharmacists if needed.

Patients who were found to have or expressed significant disability because of pain and who wished to learn pain self-management strategies could participate in an 8-week OPGP. This program included the use of cognitive behavioral therapy (CBT) strategies along with group physical therapy classes. Some patients also received individual therapies concurrently with the 8-week OPGP. Patients were excluded from participating in the OPGP only if their current medical or psychiatric status precluded them from full engagement and maximum benefit as determined by the pain physician and psychologist.

 

 

Participants and Intervention

Program participants were patients with a chronic pain diagnosis who enrolled in the interdisciplinary pain team OPGP between April 2016 and April 2017. Most patients were referred by their PCPs due to chronic low back, neck, joint or neuropathic pain, although many presented with multiple pain areas. The onset of pain often was a result of a service-related injury or overuse, or the etiology was unknown.

A board-certified pain physician, licensed clinical psychologist, 2 licensed PTs, and a clinical pharmacist led the OPGP sessions. The program was composed of 3-hour-long sessions held weekly for 8 consecutive weeks. Each week, a member of the team covered a specific topic (Table 1).

The team psychologist provided a CBT approach for managing chronic pain, which included an introduction to a proactive model of coping with chronic pain; cognitive restructuring and ways to promote healthy thinking; relaxation techniques and mindfulness; and strategies to improve communication with family and providers related to chronic pain. Other team members presented information from their discipline.

These sessions focused on the importance of exercise, movement, and physical therapy; appropriate use of medications for managing chronic pain; pacing activities and body mechanics; and the medical approach to managing chronic pain. In addition to didactic presentations, interaction and therapeutic dialogue was encouraged among patients. The education portion of each weekly session lasted about 90 minutes, including a short break. Then, following another short break, patients proceeded to the physical therapy area and engaged in an individualized, monitored exercise program, conducted by the team PTs. Patients also were issued pedometers and encouraged to track their steps each day. Education in improving posture and body mechanics was a key component of the exercise portion of the program so patients could resume their normal daily activities and regain enjoyment in their life. Pain outcomemeasures were collected at admission and immediately before discharge.

Medication management also was an important part of the program for some patients and included tapering off opioids and other drugs and implementing trials of adjuvant pain medications shown to help chronic pain. For some patients, this medication management continued after the patient completed the program.

Measures

The Pain Outcome Questionnaire (POQ) is a 19-item, self-report measure of pain treatment outcomes. Pain rating, mobility, activities of daily living, vitality, negative effect, and fear are the functioning domains evaluated, and the subscale scores are added to produce a total score. The POQ was developed from samples of veterans undergoing inpatient or outpatient pain treatment at VA facilities. For each of the subscales and the total score, higher values indicate poorer outcomes. In normative outpatient VA samples, a total score of 71 is at the 25th percentile, and 120 is at the 75th percentile. The POQ has been shown to have good reliability and validity among veterans in an outpatient setting.25

The Pain Catastrophizing Scale (PCS) is a 13-item scale designed to measure various levels of pain catastrophizing.26 Each item is rated on a 5-point Likert-type scale, from 0 (not at all) to 4 (all the time). The PCS consists of 3 subscale domains: rumination, 4 items; magnification, 3 items; and helplessness, 6 items. Responses to all items also can be added to produce a total score from 0 to 52, with higher scores indicating a higher level of catastrophic thinking related to pain. This project evaluated both the total score and the 3 subscale scores.

The Pain Self-Efficacy Questionnaire (PSEQ) is a 10-item questionnaire that assesses confidence in an individual’s ability to cope or to perform activities despite the pain.27 The PSEQ covers a range of functions, including household chores, socializing, work, as well as coping with pain without medications. Each question has a 7-point Likert scale response: 0 = not at all confident, and 7 = completely confident, to produce a total score from 0 to 60. Higher scores indicate stronger pain self-efficacy, which has been shown to be associated with return to work and maintenance of functional gains.

The Patient Health Questionnaire-4 (PHQ-4) is a 4-item instrument used to screen for depression and anxiety in outpatient medical settings.22 Patients indicate how often they have been bothered by certain problems on a 4-point Likert scale, from 0 (not at all) to 3 (nearly every day). The PHQ-4 provides a total score (0-12) with scores of 6 to 8 indicating moderate and 9 to 12 indicating severe psychological distress; 2 subscale scores, 1 for anxiety (2 questions) and 1 for depression (2 questions). For this analysis, the total PHQ-4 score has been dichotomized with 1 indicating a score in the moderate or severe range vs 0 for a score of mild or no psychological distress. Likewise, each of the subscale scores have been dichotomized with 1 indicating a score of 3 or greater, which is considered a positive screen.

The 6-minute walk test (6MWT) measures the distance (in feet) an individual can walk over a total of 6 minutes on a hard, flat surface.28 Even though the individual can walk at a self-selected pace and rest if needed during the test, the goal is for the patient to walk as far as possible over the course of 6 minutes. The 6MWT provides information regarding functional capacity, response to therapy, and prognosis across a range of chronic conditions, including pain.

 

 

Data Analysis

Data analysis included the use of both descriptive and comparative statistics. A descriptive analysis was conducted to examine the characteristics of patients who did and did not complete the OPGP. Specific outcomes for those individuals who completed the program, and thus had complete pre- and post-OPGP information, then were compared. Paired t tests were used to compare differences in continuous measures between baseline (pre-OPGP) and the 8-week follow-up (post-OPGP). Comparisons involving dichotomous measures were made using the Fisher exact test. A 2-sided α with a P value .05 was considered statistically significant. All statistical analyses were conducted using STATA version 14.1 (StataCorp, College Station, TX).

Results

A total of 36 patients enrolled, and 28 (77%) completed the OPGP. Patients who did not complete the program (n = 8) either self-discharged due to lack of interest or had difficulty in consistently making their appointments and decided not to continue (Table 2).

Most of the participants who completed the program were male (75%) compared with those who did not complete (37.5%). Both groups were predominantly white, with a mean age of 51.8 years for completers and 55.8 years for noncompleters.

Outcomes for OPGP Completers

Improvements were observed for all outcome domains among patients who completed the program (eTable).

There were statistically significant reductions in POQ scores (110.8 pre-OPGP to 85.9 post-OPGP, P < .01) and the PCS overall score (31.6 pre-OPGP to 20.3 post-OPGP, P < .01), including reductions in each of the pain catastrophizing subscale domains. The rumination subscale decreased from 10.8 to 7.2 (P < .01);magnification decreased from 6.8 to 4.3 (P < .01);and helplessness decreased from 13.8 pre-OPGP to 8.7 post-OPGP (P < .01). Participants who reported pain self-efficacy also showed a statistically significant improvement with scores increasing from 23.5 pre-OPGP to 24.8 post-OPGP (P < .01). The percentage of patients scoring in the moderate/severe distress range on the PHQ-4 and likewise those screening positive for anxiety or depression also decreased, but none of the differences were statistically significant. Finally, an objective measure of functional capacity, significantly improved from an average of 1,140 feet to 1,377 feet pre- and post-OPGP, respectively.

 

Discussion

This report describes the novel model for improving delivery of chronic pain management services implemented at the Ann Arbor VAMC through the development of a multidisciplinary pain PACT. The program included using a systematically structured multidimensional approach to identify appropriate treatments and delivery of interdisciplinary care for patients with chronic pain through an OPGP. The authors’ findings establish the feasibility and acceptability of the OPGP. More than 75% of those enrolled completed the program, indicating the promising potential of this approach with significant improvements observed for several pain-related outcomes among those who completed the 8-week program.

Stepped care is a well-established approach to managing complex chronic pain conditions. The approach adds increased levels of treatment intensity when there is no improvement after initial, simple measures are instituted (eg, over-the-counter pain medications, physical therapy, life style changes). Understanding the complexity of the pain experience while treating the patient and not simply the pain has the highest likelihood of helping patients with chronic pain. Given the prevalence of chronic pain among patients in primary care nationally, measurement-based pain care potentially could result in an earlier referral to appropriate care well before pain becomes intractable and chronic.

Growing evidence shows that multidisciplinary treatments reduce pain symptoms and intensity, medication, health care provider use, and improve quality of life.11-15,29,30 A systematic review by van Tulder and colleagues, for example, noted improvements in physical parameters, such as range of motion and flexibility and behavioral health parameters, including anxiety, depression, and cognition.29 Similarly, the cohort of patients who participated in the OPGP showed statistically significant improvements in several domains of pain-related distress and functioning following treatment, including pain catastrophizing, pain self-efficacy, and the multicomponent pain outcomes questionnaires. Functional improvement also was observed by comparing the distance walked in 6 minutes before and after program completion.

There is significant variation in duration of rehabilitation programs lasting from 2 weeks to 12 weeks or longer. These sessions consist of half days, daily sessions, weekly sessions, and monthly sessions. Inconsistencies also exist among programs that use 3 to 280 professional contact hours. Although it has been shown that programs with more than 100 hours of professional contact tended to have better outcomes than did those with less than 30 hours of contact, Stratton and colleagues reported that a 6-week group program was equivalent or better than a 12- and 10-week group program among veterans.11,31 These findings along with staffing and resource constraints led to the implementation of the 8-week OPGP with fewer than 30 hours of contact time per group. These results have important practical implications, as shorter treatments may offer comparable therapeutic impact than do longer, more time-intensive protocols.

Limitations

These findings were derived from a quality improvement project within one institution, and several limitations exist. Although the broader purpose of the article was to show how the fundamentals of creating a cohesive multidisciplinary chronic pain team can be implemented within the VA setting, the highlighted outcomes were primarily from participants in the OPGP Since this was not a controlled or experimental study and given potential sample size and selections issues as well as the lack of longer-term follow-up information, further study is needed to draw definitive conclusions about program effectiveness, despite promising preliminary results. In addition, medication use, such as opioids either before or after completion of the program, was not included as part of this evaluation. As previously discussed, medication management for some patients continued beyond the 8-week time frame of the OPGP. Nonetheless, understanding the impact of this team approach on opioid use also is an important topic for future research.

Despite these limitations, the described model could be a feasible option for improving pain management in outpatient practices not only within the VA but in community settings.

Conclusion

These results suggest that the use of short-term, structured therapeutic protocols could be a potentially effective strategy for the behavioral treatment of chronic pain conditions among veterans. The development and implementation of effective, innovative, evidence-based practice to address the needs of patients with chronic pain is an important priority for maximizing clinical service delivery and meeting the needs of the nation’s veterans.

Acknowledgments
The authors thank the previous Associate Chief of Staff, Ambulatory Care, Clinton Greenstone, MD, and Director of Primary Care Adam Tremblay, MD, for their vision, leadership, and support of the team and its efforts.

This work was supported in part through a Department of Veterans Affairs Health Services Research and Development Service Research Career Scientist Award (RCS 11-222) awarded to Sarah Krein, PhD.

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29. van Tulder MW, Ostelo R, Vlaeyen JW, Linton SJ, Morley SJ, Assendelft WJ. Behavioral treatment for chronic low back pain: a systematic review within the framework of the Cochrane back review group. Spine (Phila Pa 1976). 2000;25(20):2688-2699.

30. Sanders SH, Harden RN, Vicente PJ. Evidence-based clinical practice guidelines for interdisciplinary rehabilitation of chronic nonmalignant pain syndrome patients. Pain Pract. 2005;5(4):303-315.

31. Stratton KJ, Bender MC, Cameron JJ, Pickett TC. Development and evaluation of a behavioral pain management treatment program in a veterans affairs medical center. Mil Med. 2015;180(3):263-268.

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Dr. Dadabayev is an Anesthesiologist, Pain Medicine Physician, and PACT pain lead; Dr. Hausman is an Anesthesiologist, Critical Care Physician, Associate Chief of Staff for Ambulatory Care, and Service Chief of Anesthesiology and Perioperative care; Dr. Coy is a Clinical Psychologist; Dr. Franchina is a Clinical Pharmacist; Dr. Krein is a Research Career Scientist; and Mr. Bailey and Mr. Grzesiak are Physical Therapists, all at VA Ann Arbor Healthcare System in Michigan. Dr. Dadabayev also is a Clinical Lecturer; Dr. Hausman is an Assistant Clinical Professor, and Dr. Krein is a Research Professor; all at the University of Michigan in Ann Arbor.
Correspondence: Dr. Dadabayev (alisher. dadabayev@va.gov)

Author disclosures
The authors report no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the authors and do not necessarily reflect those of
Federal Practitioner, Frontline Medical Communications Inc., the U.S. Government, or any of its agencies.

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Dr. Dadabayev is an Anesthesiologist, Pain Medicine Physician, and PACT pain lead; Dr. Hausman is an Anesthesiologist, Critical Care Physician, Associate Chief of Staff for Ambulatory Care, and Service Chief of Anesthesiology and Perioperative care; Dr. Coy is a Clinical Psychologist; Dr. Franchina is a Clinical Pharmacist; Dr. Krein is a Research Career Scientist; and Mr. Bailey and Mr. Grzesiak are Physical Therapists, all at VA Ann Arbor Healthcare System in Michigan. Dr. Dadabayev also is a Clinical Lecturer; Dr. Hausman is an Assistant Clinical Professor, and Dr. Krein is a Research Professor; all at the University of Michigan in Ann Arbor.
Correspondence: Dr. Dadabayev (alisher. dadabayev@va.gov)

Author disclosures
The authors report no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the authors and do not necessarily reflect those of
Federal Practitioner, Frontline Medical Communications Inc., the U.S. Government, or any of its agencies.

Author and Disclosure Information

Dr. Dadabayev is an Anesthesiologist, Pain Medicine Physician, and PACT pain lead; Dr. Hausman is an Anesthesiologist, Critical Care Physician, Associate Chief of Staff for Ambulatory Care, and Service Chief of Anesthesiology and Perioperative care; Dr. Coy is a Clinical Psychologist; Dr. Franchina is a Clinical Pharmacist; Dr. Krein is a Research Career Scientist; and Mr. Bailey and Mr. Grzesiak are Physical Therapists, all at VA Ann Arbor Healthcare System in Michigan. Dr. Dadabayev also is a Clinical Lecturer; Dr. Hausman is an Assistant Clinical Professor, and Dr. Krein is a Research Professor; all at the University of Michigan in Ann Arbor.
Correspondence: Dr. Dadabayev (alisher. dadabayev@va.gov)

Author disclosures
The authors report no actual or potential conflicts of interest with regard to this article.

Disclaimer
The opinions expressed herein are those of the authors and do not necessarily reflect those of
Federal Practitioner, Frontline Medical Communications Inc., the U.S. Government, or any of its agencies.

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Related Articles
A novel interdisciplinary team approach within a primary care setting may be a promising model for delivering effective comprehensive treatment options for patients with chronic pain.
A novel interdisciplinary team approach within a primary care setting may be a promising model for delivering effective comprehensive treatment options for patients with chronic pain.

Chronic pain is a common health care problem that remains a significant burden for the VHA.1,2 Some reports indicate that nearly 50% of VA patients report chronic pain.3,4 Both within and outside the VHA, primary care providers (PCPs) generally manage patients with chronic pain.5,6 Historically, a biomedical approach to chronic pain also included the use of opioid medications, which may have contributed to increased opioid-related morbidity and mortality especially among the veteran patient population.7-9 The use of opioids also is controversial due to concerns about adverse effects (AEs), long-term efficacy, functional outcomes, and the potential for drug abuse and addiction.10 Consequently, alternative treatment options that incorporate an interdisciplinary approach have gained significant interest among pain care providers.11 Interdisciplinary programs have been shown to improve functional status and psychological well-being and to reduce pain severity and opioid use.12-14 These benefits may persist for a decade or longer.15

Background

The Stepped Care Model for Pain Management (SCM-PM) is a specific pain treatment approach promoted by the VA National Pain Management Directive.16 This systematically adjusted approach is associated with improved patient satisfaction and health outcomes for pain and depression.17,18 At its core, the model promotes engaging patients as active participants in their care along with a team of doctors who can offer an integrated, evidence-based, multimodal, interdisciplinary treatment plan.

To successfully implement this strategy at the VA, patient aligned care teams (PACT) assess and manage patients with common pain conditions through collaboration with mental health, complementary and integrative health services, physical therapy, and other programs, such as opioid renewal clinics and pain schools.19 This collaborative care approach, which the PCP initiates, is step 1 of the SCM-PM. If initial treatment is not successful and patients are not improving as expected, specialty care consultation and collaborative comanagement through interdisciplinary pain specialty teams are sought (step 2). Finally, step 3 involves tertiary, interdisciplinary care, including access to advanced diagnostic and pain rehabilitation programs accredited by the Commission for Accreditation of Rehabilitation Facilities (CARF).

Although the advantages of interdisciplinary pain programs are clear, resource limitations as well as challenges related to competencies of the PCPs, nurses, and associated health care professionals in pain assessment and management can make implementation of these programs, including the SCM-PM, difficult for many clinics and facilities. Thus, identifying effective chronic pain models and strategies, incorporating the philosophy and key elements of interdisciplinary programs, and accounting for facility resources and capacity are all important.

At the Ann Arbor VAMC, development of a comprehensive interdisciplinary team started with the implementation of joint sessions with a clinical pharmacist and health psychologist embedded in primary care to enhance access to behavioral pain management interventions.20 This program was subsequently expanded to include a pain physician, 2 pain-focused physical therapists (PTs) and a pain nurse.

This article describes a novel team approach for providing more comprehensive, interdisciplinary care for patients with chronic pain along with the initial results for the patients who were part of an outpatient pain group program (OPGP).

Methods

Developing a more interdisciplinary pain management program included integrating different services and creating a strategy for comprehensive evaluation and management of patients with chronic pain. After patients were referred to the interdisciplinary pain clinic by their PCP, they received a systematically structured multidimensional assessment. The primary focus of this assessment was to create an individually directed treatment approach based on the patient’s responses to previous treatments and information collected from several questionnaires administered prior to evaluation. This information helped guide individual patient decision making and actively engaged patients in their care, thus following one of the central tenants of the SCM-PM model. Moreover, functional restoration was at the core of each patient’s evaluation and management. The primary focus was on nonpharmacologic treatment options that included psychological, physical, and occupational therapy; self-management; education; and complementary and alternative therapies. These modalities were offered either individually or in a group setting.

The first step after referral was an evaluation that followed the main core principles for complex disease management described by Tauben and Theodore.21 All new patients were asked to complete a 2-question pain intensity and pain interference measure, the 4-question Patient Health Questionnaire (PHQ-4), 4-question Primary Care-PTSD screening tool (PC-PTSD), and the STOP-BANG questionnaire to assess the risk for obstructive sleep apnea.22-24 Each measure allowed the physician to identify specific problem areas and formulate a treatment plan that would incorporate PTs or occupational therapists, psychologists and/or clinical specialists, and pharmacists if needed.

Patients who were found to have or expressed significant disability because of pain and who wished to learn pain self-management strategies could participate in an 8-week OPGP. This program included the use of cognitive behavioral therapy (CBT) strategies along with group physical therapy classes. Some patients also received individual therapies concurrently with the 8-week OPGP. Patients were excluded from participating in the OPGP only if their current medical or psychiatric status precluded them from full engagement and maximum benefit as determined by the pain physician and psychologist.

 

 

Participants and Intervention

Program participants were patients with a chronic pain diagnosis who enrolled in the interdisciplinary pain team OPGP between April 2016 and April 2017. Most patients were referred by their PCPs due to chronic low back, neck, joint or neuropathic pain, although many presented with multiple pain areas. The onset of pain often was a result of a service-related injury or overuse, or the etiology was unknown.

A board-certified pain physician, licensed clinical psychologist, 2 licensed PTs, and a clinical pharmacist led the OPGP sessions. The program was composed of 3-hour-long sessions held weekly for 8 consecutive weeks. Each week, a member of the team covered a specific topic (Table 1).

The team psychologist provided a CBT approach for managing chronic pain, which included an introduction to a proactive model of coping with chronic pain; cognitive restructuring and ways to promote healthy thinking; relaxation techniques and mindfulness; and strategies to improve communication with family and providers related to chronic pain. Other team members presented information from their discipline.

These sessions focused on the importance of exercise, movement, and physical therapy; appropriate use of medications for managing chronic pain; pacing activities and body mechanics; and the medical approach to managing chronic pain. In addition to didactic presentations, interaction and therapeutic dialogue was encouraged among patients. The education portion of each weekly session lasted about 90 minutes, including a short break. Then, following another short break, patients proceeded to the physical therapy area and engaged in an individualized, monitored exercise program, conducted by the team PTs. Patients also were issued pedometers and encouraged to track their steps each day. Education in improving posture and body mechanics was a key component of the exercise portion of the program so patients could resume their normal daily activities and regain enjoyment in their life. Pain outcomemeasures were collected at admission and immediately before discharge.

Medication management also was an important part of the program for some patients and included tapering off opioids and other drugs and implementing trials of adjuvant pain medications shown to help chronic pain. For some patients, this medication management continued after the patient completed the program.

Measures

The Pain Outcome Questionnaire (POQ) is a 19-item, self-report measure of pain treatment outcomes. Pain rating, mobility, activities of daily living, vitality, negative effect, and fear are the functioning domains evaluated, and the subscale scores are added to produce a total score. The POQ was developed from samples of veterans undergoing inpatient or outpatient pain treatment at VA facilities. For each of the subscales and the total score, higher values indicate poorer outcomes. In normative outpatient VA samples, a total score of 71 is at the 25th percentile, and 120 is at the 75th percentile. The POQ has been shown to have good reliability and validity among veterans in an outpatient setting.25

The Pain Catastrophizing Scale (PCS) is a 13-item scale designed to measure various levels of pain catastrophizing.26 Each item is rated on a 5-point Likert-type scale, from 0 (not at all) to 4 (all the time). The PCS consists of 3 subscale domains: rumination, 4 items; magnification, 3 items; and helplessness, 6 items. Responses to all items also can be added to produce a total score from 0 to 52, with higher scores indicating a higher level of catastrophic thinking related to pain. This project evaluated both the total score and the 3 subscale scores.

The Pain Self-Efficacy Questionnaire (PSEQ) is a 10-item questionnaire that assesses confidence in an individual’s ability to cope or to perform activities despite the pain.27 The PSEQ covers a range of functions, including household chores, socializing, work, as well as coping with pain without medications. Each question has a 7-point Likert scale response: 0 = not at all confident, and 7 = completely confident, to produce a total score from 0 to 60. Higher scores indicate stronger pain self-efficacy, which has been shown to be associated with return to work and maintenance of functional gains.

The Patient Health Questionnaire-4 (PHQ-4) is a 4-item instrument used to screen for depression and anxiety in outpatient medical settings.22 Patients indicate how often they have been bothered by certain problems on a 4-point Likert scale, from 0 (not at all) to 3 (nearly every day). The PHQ-4 provides a total score (0-12) with scores of 6 to 8 indicating moderate and 9 to 12 indicating severe psychological distress; 2 subscale scores, 1 for anxiety (2 questions) and 1 for depression (2 questions). For this analysis, the total PHQ-4 score has been dichotomized with 1 indicating a score in the moderate or severe range vs 0 for a score of mild or no psychological distress. Likewise, each of the subscale scores have been dichotomized with 1 indicating a score of 3 or greater, which is considered a positive screen.

The 6-minute walk test (6MWT) measures the distance (in feet) an individual can walk over a total of 6 minutes on a hard, flat surface.28 Even though the individual can walk at a self-selected pace and rest if needed during the test, the goal is for the patient to walk as far as possible over the course of 6 minutes. The 6MWT provides information regarding functional capacity, response to therapy, and prognosis across a range of chronic conditions, including pain.

 

 

Data Analysis

Data analysis included the use of both descriptive and comparative statistics. A descriptive analysis was conducted to examine the characteristics of patients who did and did not complete the OPGP. Specific outcomes for those individuals who completed the program, and thus had complete pre- and post-OPGP information, then were compared. Paired t tests were used to compare differences in continuous measures between baseline (pre-OPGP) and the 8-week follow-up (post-OPGP). Comparisons involving dichotomous measures were made using the Fisher exact test. A 2-sided α with a P value .05 was considered statistically significant. All statistical analyses were conducted using STATA version 14.1 (StataCorp, College Station, TX).

Results

A total of 36 patients enrolled, and 28 (77%) completed the OPGP. Patients who did not complete the program (n = 8) either self-discharged due to lack of interest or had difficulty in consistently making their appointments and decided not to continue (Table 2).

Most of the participants who completed the program were male (75%) compared with those who did not complete (37.5%). Both groups were predominantly white, with a mean age of 51.8 years for completers and 55.8 years for noncompleters.

Outcomes for OPGP Completers

Improvements were observed for all outcome domains among patients who completed the program (eTable).

There were statistically significant reductions in POQ scores (110.8 pre-OPGP to 85.9 post-OPGP, P < .01) and the PCS overall score (31.6 pre-OPGP to 20.3 post-OPGP, P < .01), including reductions in each of the pain catastrophizing subscale domains. The rumination subscale decreased from 10.8 to 7.2 (P < .01);magnification decreased from 6.8 to 4.3 (P < .01);and helplessness decreased from 13.8 pre-OPGP to 8.7 post-OPGP (P < .01). Participants who reported pain self-efficacy also showed a statistically significant improvement with scores increasing from 23.5 pre-OPGP to 24.8 post-OPGP (P < .01). The percentage of patients scoring in the moderate/severe distress range on the PHQ-4 and likewise those screening positive for anxiety or depression also decreased, but none of the differences were statistically significant. Finally, an objective measure of functional capacity, significantly improved from an average of 1,140 feet to 1,377 feet pre- and post-OPGP, respectively.

 

Discussion

This report describes the novel model for improving delivery of chronic pain management services implemented at the Ann Arbor VAMC through the development of a multidisciplinary pain PACT. The program included using a systematically structured multidimensional approach to identify appropriate treatments and delivery of interdisciplinary care for patients with chronic pain through an OPGP. The authors’ findings establish the feasibility and acceptability of the OPGP. More than 75% of those enrolled completed the program, indicating the promising potential of this approach with significant improvements observed for several pain-related outcomes among those who completed the 8-week program.

Stepped care is a well-established approach to managing complex chronic pain conditions. The approach adds increased levels of treatment intensity when there is no improvement after initial, simple measures are instituted (eg, over-the-counter pain medications, physical therapy, life style changes). Understanding the complexity of the pain experience while treating the patient and not simply the pain has the highest likelihood of helping patients with chronic pain. Given the prevalence of chronic pain among patients in primary care nationally, measurement-based pain care potentially could result in an earlier referral to appropriate care well before pain becomes intractable and chronic.

Growing evidence shows that multidisciplinary treatments reduce pain symptoms and intensity, medication, health care provider use, and improve quality of life.11-15,29,30 A systematic review by van Tulder and colleagues, for example, noted improvements in physical parameters, such as range of motion and flexibility and behavioral health parameters, including anxiety, depression, and cognition.29 Similarly, the cohort of patients who participated in the OPGP showed statistically significant improvements in several domains of pain-related distress and functioning following treatment, including pain catastrophizing, pain self-efficacy, and the multicomponent pain outcomes questionnaires. Functional improvement also was observed by comparing the distance walked in 6 minutes before and after program completion.

There is significant variation in duration of rehabilitation programs lasting from 2 weeks to 12 weeks or longer. These sessions consist of half days, daily sessions, weekly sessions, and monthly sessions. Inconsistencies also exist among programs that use 3 to 280 professional contact hours. Although it has been shown that programs with more than 100 hours of professional contact tended to have better outcomes than did those with less than 30 hours of contact, Stratton and colleagues reported that a 6-week group program was equivalent or better than a 12- and 10-week group program among veterans.11,31 These findings along with staffing and resource constraints led to the implementation of the 8-week OPGP with fewer than 30 hours of contact time per group. These results have important practical implications, as shorter treatments may offer comparable therapeutic impact than do longer, more time-intensive protocols.

Limitations

These findings were derived from a quality improvement project within one institution, and several limitations exist. Although the broader purpose of the article was to show how the fundamentals of creating a cohesive multidisciplinary chronic pain team can be implemented within the VA setting, the highlighted outcomes were primarily from participants in the OPGP Since this was not a controlled or experimental study and given potential sample size and selections issues as well as the lack of longer-term follow-up information, further study is needed to draw definitive conclusions about program effectiveness, despite promising preliminary results. In addition, medication use, such as opioids either before or after completion of the program, was not included as part of this evaluation. As previously discussed, medication management for some patients continued beyond the 8-week time frame of the OPGP. Nonetheless, understanding the impact of this team approach on opioid use also is an important topic for future research.

Despite these limitations, the described model could be a feasible option for improving pain management in outpatient practices not only within the VA but in community settings.

Conclusion

These results suggest that the use of short-term, structured therapeutic protocols could be a potentially effective strategy for the behavioral treatment of chronic pain conditions among veterans. The development and implementation of effective, innovative, evidence-based practice to address the needs of patients with chronic pain is an important priority for maximizing clinical service delivery and meeting the needs of the nation’s veterans.

Acknowledgments
The authors thank the previous Associate Chief of Staff, Ambulatory Care, Clinton Greenstone, MD, and Director of Primary Care Adam Tremblay, MD, for their vision, leadership, and support of the team and its efforts.

This work was supported in part through a Department of Veterans Affairs Health Services Research and Development Service Research Career Scientist Award (RCS 11-222) awarded to Sarah Krein, PhD.

Chronic pain is a common health care problem that remains a significant burden for the VHA.1,2 Some reports indicate that nearly 50% of VA patients report chronic pain.3,4 Both within and outside the VHA, primary care providers (PCPs) generally manage patients with chronic pain.5,6 Historically, a biomedical approach to chronic pain also included the use of opioid medications, which may have contributed to increased opioid-related morbidity and mortality especially among the veteran patient population.7-9 The use of opioids also is controversial due to concerns about adverse effects (AEs), long-term efficacy, functional outcomes, and the potential for drug abuse and addiction.10 Consequently, alternative treatment options that incorporate an interdisciplinary approach have gained significant interest among pain care providers.11 Interdisciplinary programs have been shown to improve functional status and psychological well-being and to reduce pain severity and opioid use.12-14 These benefits may persist for a decade or longer.15

Background

The Stepped Care Model for Pain Management (SCM-PM) is a specific pain treatment approach promoted by the VA National Pain Management Directive.16 This systematically adjusted approach is associated with improved patient satisfaction and health outcomes for pain and depression.17,18 At its core, the model promotes engaging patients as active participants in their care along with a team of doctors who can offer an integrated, evidence-based, multimodal, interdisciplinary treatment plan.

To successfully implement this strategy at the VA, patient aligned care teams (PACT) assess and manage patients with common pain conditions through collaboration with mental health, complementary and integrative health services, physical therapy, and other programs, such as opioid renewal clinics and pain schools.19 This collaborative care approach, which the PCP initiates, is step 1 of the SCM-PM. If initial treatment is not successful and patients are not improving as expected, specialty care consultation and collaborative comanagement through interdisciplinary pain specialty teams are sought (step 2). Finally, step 3 involves tertiary, interdisciplinary care, including access to advanced diagnostic and pain rehabilitation programs accredited by the Commission for Accreditation of Rehabilitation Facilities (CARF).

Although the advantages of interdisciplinary pain programs are clear, resource limitations as well as challenges related to competencies of the PCPs, nurses, and associated health care professionals in pain assessment and management can make implementation of these programs, including the SCM-PM, difficult for many clinics and facilities. Thus, identifying effective chronic pain models and strategies, incorporating the philosophy and key elements of interdisciplinary programs, and accounting for facility resources and capacity are all important.

At the Ann Arbor VAMC, development of a comprehensive interdisciplinary team started with the implementation of joint sessions with a clinical pharmacist and health psychologist embedded in primary care to enhance access to behavioral pain management interventions.20 This program was subsequently expanded to include a pain physician, 2 pain-focused physical therapists (PTs) and a pain nurse.

This article describes a novel team approach for providing more comprehensive, interdisciplinary care for patients with chronic pain along with the initial results for the patients who were part of an outpatient pain group program (OPGP).

Methods

Developing a more interdisciplinary pain management program included integrating different services and creating a strategy for comprehensive evaluation and management of patients with chronic pain. After patients were referred to the interdisciplinary pain clinic by their PCP, they received a systematically structured multidimensional assessment. The primary focus of this assessment was to create an individually directed treatment approach based on the patient’s responses to previous treatments and information collected from several questionnaires administered prior to evaluation. This information helped guide individual patient decision making and actively engaged patients in their care, thus following one of the central tenants of the SCM-PM model. Moreover, functional restoration was at the core of each patient’s evaluation and management. The primary focus was on nonpharmacologic treatment options that included psychological, physical, and occupational therapy; self-management; education; and complementary and alternative therapies. These modalities were offered either individually or in a group setting.

The first step after referral was an evaluation that followed the main core principles for complex disease management described by Tauben and Theodore.21 All new patients were asked to complete a 2-question pain intensity and pain interference measure, the 4-question Patient Health Questionnaire (PHQ-4), 4-question Primary Care-PTSD screening tool (PC-PTSD), and the STOP-BANG questionnaire to assess the risk for obstructive sleep apnea.22-24 Each measure allowed the physician to identify specific problem areas and formulate a treatment plan that would incorporate PTs or occupational therapists, psychologists and/or clinical specialists, and pharmacists if needed.

Patients who were found to have or expressed significant disability because of pain and who wished to learn pain self-management strategies could participate in an 8-week OPGP. This program included the use of cognitive behavioral therapy (CBT) strategies along with group physical therapy classes. Some patients also received individual therapies concurrently with the 8-week OPGP. Patients were excluded from participating in the OPGP only if their current medical or psychiatric status precluded them from full engagement and maximum benefit as determined by the pain physician and psychologist.

 

 

Participants and Intervention

Program participants were patients with a chronic pain diagnosis who enrolled in the interdisciplinary pain team OPGP between April 2016 and April 2017. Most patients were referred by their PCPs due to chronic low back, neck, joint or neuropathic pain, although many presented with multiple pain areas. The onset of pain often was a result of a service-related injury or overuse, or the etiology was unknown.

A board-certified pain physician, licensed clinical psychologist, 2 licensed PTs, and a clinical pharmacist led the OPGP sessions. The program was composed of 3-hour-long sessions held weekly for 8 consecutive weeks. Each week, a member of the team covered a specific topic (Table 1).

The team psychologist provided a CBT approach for managing chronic pain, which included an introduction to a proactive model of coping with chronic pain; cognitive restructuring and ways to promote healthy thinking; relaxation techniques and mindfulness; and strategies to improve communication with family and providers related to chronic pain. Other team members presented information from their discipline.

These sessions focused on the importance of exercise, movement, and physical therapy; appropriate use of medications for managing chronic pain; pacing activities and body mechanics; and the medical approach to managing chronic pain. In addition to didactic presentations, interaction and therapeutic dialogue was encouraged among patients. The education portion of each weekly session lasted about 90 minutes, including a short break. Then, following another short break, patients proceeded to the physical therapy area and engaged in an individualized, monitored exercise program, conducted by the team PTs. Patients also were issued pedometers and encouraged to track their steps each day. Education in improving posture and body mechanics was a key component of the exercise portion of the program so patients could resume their normal daily activities and regain enjoyment in their life. Pain outcomemeasures were collected at admission and immediately before discharge.

Medication management also was an important part of the program for some patients and included tapering off opioids and other drugs and implementing trials of adjuvant pain medications shown to help chronic pain. For some patients, this medication management continued after the patient completed the program.

Measures

The Pain Outcome Questionnaire (POQ) is a 19-item, self-report measure of pain treatment outcomes. Pain rating, mobility, activities of daily living, vitality, negative effect, and fear are the functioning domains evaluated, and the subscale scores are added to produce a total score. The POQ was developed from samples of veterans undergoing inpatient or outpatient pain treatment at VA facilities. For each of the subscales and the total score, higher values indicate poorer outcomes. In normative outpatient VA samples, a total score of 71 is at the 25th percentile, and 120 is at the 75th percentile. The POQ has been shown to have good reliability and validity among veterans in an outpatient setting.25

The Pain Catastrophizing Scale (PCS) is a 13-item scale designed to measure various levels of pain catastrophizing.26 Each item is rated on a 5-point Likert-type scale, from 0 (not at all) to 4 (all the time). The PCS consists of 3 subscale domains: rumination, 4 items; magnification, 3 items; and helplessness, 6 items. Responses to all items also can be added to produce a total score from 0 to 52, with higher scores indicating a higher level of catastrophic thinking related to pain. This project evaluated both the total score and the 3 subscale scores.

The Pain Self-Efficacy Questionnaire (PSEQ) is a 10-item questionnaire that assesses confidence in an individual’s ability to cope or to perform activities despite the pain.27 The PSEQ covers a range of functions, including household chores, socializing, work, as well as coping with pain without medications. Each question has a 7-point Likert scale response: 0 = not at all confident, and 7 = completely confident, to produce a total score from 0 to 60. Higher scores indicate stronger pain self-efficacy, which has been shown to be associated with return to work and maintenance of functional gains.

The Patient Health Questionnaire-4 (PHQ-4) is a 4-item instrument used to screen for depression and anxiety in outpatient medical settings.22 Patients indicate how often they have been bothered by certain problems on a 4-point Likert scale, from 0 (not at all) to 3 (nearly every day). The PHQ-4 provides a total score (0-12) with scores of 6 to 8 indicating moderate and 9 to 12 indicating severe psychological distress; 2 subscale scores, 1 for anxiety (2 questions) and 1 for depression (2 questions). For this analysis, the total PHQ-4 score has been dichotomized with 1 indicating a score in the moderate or severe range vs 0 for a score of mild or no psychological distress. Likewise, each of the subscale scores have been dichotomized with 1 indicating a score of 3 or greater, which is considered a positive screen.

The 6-minute walk test (6MWT) measures the distance (in feet) an individual can walk over a total of 6 minutes on a hard, flat surface.28 Even though the individual can walk at a self-selected pace and rest if needed during the test, the goal is for the patient to walk as far as possible over the course of 6 minutes. The 6MWT provides information regarding functional capacity, response to therapy, and prognosis across a range of chronic conditions, including pain.

 

 

Data Analysis

Data analysis included the use of both descriptive and comparative statistics. A descriptive analysis was conducted to examine the characteristics of patients who did and did not complete the OPGP. Specific outcomes for those individuals who completed the program, and thus had complete pre- and post-OPGP information, then were compared. Paired t tests were used to compare differences in continuous measures between baseline (pre-OPGP) and the 8-week follow-up (post-OPGP). Comparisons involving dichotomous measures were made using the Fisher exact test. A 2-sided α with a P value .05 was considered statistically significant. All statistical analyses were conducted using STATA version 14.1 (StataCorp, College Station, TX).

Results

A total of 36 patients enrolled, and 28 (77%) completed the OPGP. Patients who did not complete the program (n = 8) either self-discharged due to lack of interest or had difficulty in consistently making their appointments and decided not to continue (Table 2).

Most of the participants who completed the program were male (75%) compared with those who did not complete (37.5%). Both groups were predominantly white, with a mean age of 51.8 years for completers and 55.8 years for noncompleters.

Outcomes for OPGP Completers

Improvements were observed for all outcome domains among patients who completed the program (eTable).

There were statistically significant reductions in POQ scores (110.8 pre-OPGP to 85.9 post-OPGP, P < .01) and the PCS overall score (31.6 pre-OPGP to 20.3 post-OPGP, P < .01), including reductions in each of the pain catastrophizing subscale domains. The rumination subscale decreased from 10.8 to 7.2 (P < .01);magnification decreased from 6.8 to 4.3 (P < .01);and helplessness decreased from 13.8 pre-OPGP to 8.7 post-OPGP (P < .01). Participants who reported pain self-efficacy also showed a statistically significant improvement with scores increasing from 23.5 pre-OPGP to 24.8 post-OPGP (P < .01). The percentage of patients scoring in the moderate/severe distress range on the PHQ-4 and likewise those screening positive for anxiety or depression also decreased, but none of the differences were statistically significant. Finally, an objective measure of functional capacity, significantly improved from an average of 1,140 feet to 1,377 feet pre- and post-OPGP, respectively.

 

Discussion

This report describes the novel model for improving delivery of chronic pain management services implemented at the Ann Arbor VAMC through the development of a multidisciplinary pain PACT. The program included using a systematically structured multidimensional approach to identify appropriate treatments and delivery of interdisciplinary care for patients with chronic pain through an OPGP. The authors’ findings establish the feasibility and acceptability of the OPGP. More than 75% of those enrolled completed the program, indicating the promising potential of this approach with significant improvements observed for several pain-related outcomes among those who completed the 8-week program.

Stepped care is a well-established approach to managing complex chronic pain conditions. The approach adds increased levels of treatment intensity when there is no improvement after initial, simple measures are instituted (eg, over-the-counter pain medications, physical therapy, life style changes). Understanding the complexity of the pain experience while treating the patient and not simply the pain has the highest likelihood of helping patients with chronic pain. Given the prevalence of chronic pain among patients in primary care nationally, measurement-based pain care potentially could result in an earlier referral to appropriate care well before pain becomes intractable and chronic.

Growing evidence shows that multidisciplinary treatments reduce pain symptoms and intensity, medication, health care provider use, and improve quality of life.11-15,29,30 A systematic review by van Tulder and colleagues, for example, noted improvements in physical parameters, such as range of motion and flexibility and behavioral health parameters, including anxiety, depression, and cognition.29 Similarly, the cohort of patients who participated in the OPGP showed statistically significant improvements in several domains of pain-related distress and functioning following treatment, including pain catastrophizing, pain self-efficacy, and the multicomponent pain outcomes questionnaires. Functional improvement also was observed by comparing the distance walked in 6 minutes before and after program completion.

There is significant variation in duration of rehabilitation programs lasting from 2 weeks to 12 weeks or longer. These sessions consist of half days, daily sessions, weekly sessions, and monthly sessions. Inconsistencies also exist among programs that use 3 to 280 professional contact hours. Although it has been shown that programs with more than 100 hours of professional contact tended to have better outcomes than did those with less than 30 hours of contact, Stratton and colleagues reported that a 6-week group program was equivalent or better than a 12- and 10-week group program among veterans.11,31 These findings along with staffing and resource constraints led to the implementation of the 8-week OPGP with fewer than 30 hours of contact time per group. These results have important practical implications, as shorter treatments may offer comparable therapeutic impact than do longer, more time-intensive protocols.

Limitations

These findings were derived from a quality improvement project within one institution, and several limitations exist. Although the broader purpose of the article was to show how the fundamentals of creating a cohesive multidisciplinary chronic pain team can be implemented within the VA setting, the highlighted outcomes were primarily from participants in the OPGP Since this was not a controlled or experimental study and given potential sample size and selections issues as well as the lack of longer-term follow-up information, further study is needed to draw definitive conclusions about program effectiveness, despite promising preliminary results. In addition, medication use, such as opioids either before or after completion of the program, was not included as part of this evaluation. As previously discussed, medication management for some patients continued beyond the 8-week time frame of the OPGP. Nonetheless, understanding the impact of this team approach on opioid use also is an important topic for future research.

Despite these limitations, the described model could be a feasible option for improving pain management in outpatient practices not only within the VA but in community settings.

Conclusion

These results suggest that the use of short-term, structured therapeutic protocols could be a potentially effective strategy for the behavioral treatment of chronic pain conditions among veterans. The development and implementation of effective, innovative, evidence-based practice to address the needs of patients with chronic pain is an important priority for maximizing clinical service delivery and meeting the needs of the nation’s veterans.

Acknowledgments
The authors thank the previous Associate Chief of Staff, Ambulatory Care, Clinton Greenstone, MD, and Director of Primary Care Adam Tremblay, MD, for their vision, leadership, and support of the team and its efforts.

This work was supported in part through a Department of Veterans Affairs Health Services Research and Development Service Research Career Scientist Award (RCS 11-222) awarded to Sarah Krein, PhD.

References

1. Kerns RD, Otis J, Rosenberg R, Reid MC. Veterans’ reports of pain and associations with ratings of health, health-risk behaviors, affective distress, and use of the healthcare system. J Rehabil Res Dev. 2003;40(5):371-379.

2. Yu W, Ravelo A, Wagner TH, et al. Prevalence and cost of chronic conditions in the VA health care system. Med Care Res Rev. 2003;60(suppl 3):146S-167S.

3. Gironda RJ, Clark ME, Massengale JP, Walker RL. Pain among veterans of operations Enduring Freedom and Iraqi Freedom. Pain Med. 2006;7(4):339-343.

4. Cifu DX, Taylor BC, Carne WF, et al. Traumatic brain injury, posttraumatic stress disorder, and pain diagnoses in OIF/OEF/OND veterans. J Rehabil Res Dev. 2013;50(9):1169-1176.

5. Breuer B, Cruciani R, Portenoy RK. Pain management by primary care physicians, pain physicians, chiropractors, and acupuncturists: a national survey. South Med J. 2010;103(8):738-747.

6. Bergman AA, Matthias MS, Coffing JM, Krebs EE. Contrasting tensions between patients and PCPs in chronic pain management: a qualitative study. Pain Med. 2013;14(11):1689-1697.

7. Caudill-Slosberg MA, Schwartz LM, Woloshin S. Office visits and analgesic prescriptions for musculoskeletal pain in US: 1980 vs. 2000. Pain. 2004;109(3):514-519.

8. Zedler B, Xie L, Wang L, et al. Risk factors for serious prescription opioid-related toxicity or overdose among Veterans Health Administration patients. Pain Med. 2014;15(11):1911-1929.

9. Bohnert AS, Valenstein M, Bair MJ, et al. Association between opioid prescribing patterns and opioid overdose-related deaths. JAMA. 2011;305(13):1315-1321.

10. Chou R, Clark E, Helfand M. Comparative efficacy and safety of long-acting oral opioids for chronic non-cancer pain: a systematic review. J Pain Symptom Manage. 2003;26(5):1026-1048.

11. Guzmán J, Esmail R, Karjalainen K, Malmivaara A, Irvin E, Bombardier C. Multidisciplinary rehabilitation for chronic low back pain: systematic review. BMJ. 2001;322(7301):1511-1516.

12. Gatchel RJ, Okifuji A. Evidence-based scientific data documenting the treatment and cost-effectiveness of comprehensive pain programs for chronic nonmalignant pain. J Pain. 2006;7(11):779-793.

13. Flor H, Fydrich T, Turk DC. Efficacy of multidisciplinary pain treatment centers: a meta-analytic review. Pain. 1992;49(2):221-230.

14. Scascighini L, Toma V, Dober-Spielmann S, Sprott H. Multidisciplinary treatment for chronic pain: a systematic review of interventions and outcomes. Rheumatology (Oxford). 2008;47(5):670-678.

15. Patrick LE, Altmaier EM, Found EM. Long-term outcomes in multidisciplinary treatment of chronic low back pain: results of a 13-year follow-up. Spine (Phila Pa 1976). 2004;29(8):850-855.

16. Moore BA, Anderson D, Dorflinger L, et al. Stepped care model for pain management and quality of pain care in long-term opioid therapy. J Rehabil Res Dev. 2016;53(1):137-146.

17. Anderson DR, Zlateva I, Coman EN, Khatri K, Tian T, Kerns RD. Improving pain care through implementation of the stepped care model at a multisite community health center. J Pain Res. 2016;9:1021-1029.

18. Scott EL, Kroenke K, Wu J, Yu Z. Beneficial effects of improvement in depression, pain catastrophizing, and anxiety on pain outcomes: a 12-month longitudinal analysis. J Pain. 2016;17(2):215-222.

19. Kerns RD, Philip EJ, Lee AW, Rosenberger PH. Implementation of the Veterans Health Administration national pain management strategy. Transl Behav Med. 2011;1(4):635-643.

20. Bloor LE, Fisher C, Grix B, Zaleon CR, Wice S. Conjoint sessions with clinical pharmacy and health psychology for chronic pain. Fed Pract. 2017;34(4):35-41.

21. Tauben D, Theodore BR. Measurement-based stepped care approach to interdisciplinary chronic pain management. In: Benzon HT, Rathmell JP, Wu CL, et al, eds. Practical Management of Pain. 5th ed. Philadelphia, PA: Elsevier Mosby; 2013:37-46.

22. Kroenke K, Spitzer RL, Williams JB, Löwe B. An ultra-brief screening scale for anxiety and depression: the PHQ-4. Psychosomatics. 2009;50(6):613-621.

23. Ouimette P, Wade M, Prins A, Schohn M. Identifying PTSD in primary care: comparison of the primary care-PTSD screen (PC-PTSD) and the general health questionnaire-12 (GHQ). J Anxiety Disord. 2008;22(2):337-343.

24. Chung F, Yegneswaran B, Liao P, et al. STOP questionnaire: a tool to screen patients for obstructive sleep apnea. Anesthesiology. 2008;108(5):812-821.

25. Clark ME, Gironda RJ, Young RW. Development and validation of the pain outcomes questionnaire-VA. J Rehabil Res Dev. 2003;40(5):381-395.

26. Sullivan MJL, Bishop SR, Pivik J. The pain catastrophizing scale: development and validation. Psychol Assess. 1995;7(4):524-532.

27. Nicholas MK. The pain self-efficacy questionnaire: taking pain into account. Eur J Pain. 2007;11(2):153-163.

28. Peppin JF, Marcum S, Kirsh KL. The chronic pain patient and functional assessment: use of the 6-minute walk test in a multidisciplinary pain clinic. Curr Med Res Opin. 2014;30(3):361-365.

29. van Tulder MW, Ostelo R, Vlaeyen JW, Linton SJ, Morley SJ, Assendelft WJ. Behavioral treatment for chronic low back pain: a systematic review within the framework of the Cochrane back review group. Spine (Phila Pa 1976). 2000;25(20):2688-2699.

30. Sanders SH, Harden RN, Vicente PJ. Evidence-based clinical practice guidelines for interdisciplinary rehabilitation of chronic nonmalignant pain syndrome patients. Pain Pract. 2005;5(4):303-315.

31. Stratton KJ, Bender MC, Cameron JJ, Pickett TC. Development and evaluation of a behavioral pain management treatment program in a veterans affairs medical center. Mil Med. 2015;180(3):263-268.

References

1. Kerns RD, Otis J, Rosenberg R, Reid MC. Veterans’ reports of pain and associations with ratings of health, health-risk behaviors, affective distress, and use of the healthcare system. J Rehabil Res Dev. 2003;40(5):371-379.

2. Yu W, Ravelo A, Wagner TH, et al. Prevalence and cost of chronic conditions in the VA health care system. Med Care Res Rev. 2003;60(suppl 3):146S-167S.

3. Gironda RJ, Clark ME, Massengale JP, Walker RL. Pain among veterans of operations Enduring Freedom and Iraqi Freedom. Pain Med. 2006;7(4):339-343.

4. Cifu DX, Taylor BC, Carne WF, et al. Traumatic brain injury, posttraumatic stress disorder, and pain diagnoses in OIF/OEF/OND veterans. J Rehabil Res Dev. 2013;50(9):1169-1176.

5. Breuer B, Cruciani R, Portenoy RK. Pain management by primary care physicians, pain physicians, chiropractors, and acupuncturists: a national survey. South Med J. 2010;103(8):738-747.

6. Bergman AA, Matthias MS, Coffing JM, Krebs EE. Contrasting tensions between patients and PCPs in chronic pain management: a qualitative study. Pain Med. 2013;14(11):1689-1697.

7. Caudill-Slosberg MA, Schwartz LM, Woloshin S. Office visits and analgesic prescriptions for musculoskeletal pain in US: 1980 vs. 2000. Pain. 2004;109(3):514-519.

8. Zedler B, Xie L, Wang L, et al. Risk factors for serious prescription opioid-related toxicity or overdose among Veterans Health Administration patients. Pain Med. 2014;15(11):1911-1929.

9. Bohnert AS, Valenstein M, Bair MJ, et al. Association between opioid prescribing patterns and opioid overdose-related deaths. JAMA. 2011;305(13):1315-1321.

10. Chou R, Clark E, Helfand M. Comparative efficacy and safety of long-acting oral opioids for chronic non-cancer pain: a systematic review. J Pain Symptom Manage. 2003;26(5):1026-1048.

11. Guzmán J, Esmail R, Karjalainen K, Malmivaara A, Irvin E, Bombardier C. Multidisciplinary rehabilitation for chronic low back pain: systematic review. BMJ. 2001;322(7301):1511-1516.

12. Gatchel RJ, Okifuji A. Evidence-based scientific data documenting the treatment and cost-effectiveness of comprehensive pain programs for chronic nonmalignant pain. J Pain. 2006;7(11):779-793.

13. Flor H, Fydrich T, Turk DC. Efficacy of multidisciplinary pain treatment centers: a meta-analytic review. Pain. 1992;49(2):221-230.

14. Scascighini L, Toma V, Dober-Spielmann S, Sprott H. Multidisciplinary treatment for chronic pain: a systematic review of interventions and outcomes. Rheumatology (Oxford). 2008;47(5):670-678.

15. Patrick LE, Altmaier EM, Found EM. Long-term outcomes in multidisciplinary treatment of chronic low back pain: results of a 13-year follow-up. Spine (Phila Pa 1976). 2004;29(8):850-855.

16. Moore BA, Anderson D, Dorflinger L, et al. Stepped care model for pain management and quality of pain care in long-term opioid therapy. J Rehabil Res Dev. 2016;53(1):137-146.

17. Anderson DR, Zlateva I, Coman EN, Khatri K, Tian T, Kerns RD. Improving pain care through implementation of the stepped care model at a multisite community health center. J Pain Res. 2016;9:1021-1029.

18. Scott EL, Kroenke K, Wu J, Yu Z. Beneficial effects of improvement in depression, pain catastrophizing, and anxiety on pain outcomes: a 12-month longitudinal analysis. J Pain. 2016;17(2):215-222.

19. Kerns RD, Philip EJ, Lee AW, Rosenberger PH. Implementation of the Veterans Health Administration national pain management strategy. Transl Behav Med. 2011;1(4):635-643.

20. Bloor LE, Fisher C, Grix B, Zaleon CR, Wice S. Conjoint sessions with clinical pharmacy and health psychology for chronic pain. Fed Pract. 2017;34(4):35-41.

21. Tauben D, Theodore BR. Measurement-based stepped care approach to interdisciplinary chronic pain management. In: Benzon HT, Rathmell JP, Wu CL, et al, eds. Practical Management of Pain. 5th ed. Philadelphia, PA: Elsevier Mosby; 2013:37-46.

22. Kroenke K, Spitzer RL, Williams JB, Löwe B. An ultra-brief screening scale for anxiety and depression: the PHQ-4. Psychosomatics. 2009;50(6):613-621.

23. Ouimette P, Wade M, Prins A, Schohn M. Identifying PTSD in primary care: comparison of the primary care-PTSD screen (PC-PTSD) and the general health questionnaire-12 (GHQ). J Anxiety Disord. 2008;22(2):337-343.

24. Chung F, Yegneswaran B, Liao P, et al. STOP questionnaire: a tool to screen patients for obstructive sleep apnea. Anesthesiology. 2008;108(5):812-821.

25. Clark ME, Gironda RJ, Young RW. Development and validation of the pain outcomes questionnaire-VA. J Rehabil Res Dev. 2003;40(5):381-395.

26. Sullivan MJL, Bishop SR, Pivik J. The pain catastrophizing scale: development and validation. Psychol Assess. 1995;7(4):524-532.

27. Nicholas MK. The pain self-efficacy questionnaire: taking pain into account. Eur J Pain. 2007;11(2):153-163.

28. Peppin JF, Marcum S, Kirsh KL. The chronic pain patient and functional assessment: use of the 6-minute walk test in a multidisciplinary pain clinic. Curr Med Res Opin. 2014;30(3):361-365.

29. van Tulder MW, Ostelo R, Vlaeyen JW, Linton SJ, Morley SJ, Assendelft WJ. Behavioral treatment for chronic low back pain: a systematic review within the framework of the Cochrane back review group. Spine (Phila Pa 1976). 2000;25(20):2688-2699.

30. Sanders SH, Harden RN, Vicente PJ. Evidence-based clinical practice guidelines for interdisciplinary rehabilitation of chronic nonmalignant pain syndrome patients. Pain Pract. 2005;5(4):303-315.

31. Stratton KJ, Bender MC, Cameron JJ, Pickett TC. Development and evaluation of a behavioral pain management treatment program in a veterans affairs medical center. Mil Med. 2015;180(3):263-268.

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Hospitalist Experiences Regarding PICCs

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Hospitalist experiences, practice, opinions, and knowledge regarding peripherally inserted central catheters: A Michigan survey

Peripherally inserted central catheters (PICCs) have become among the most common central venous catheters (CVCs) used in contemporary medical practice.[1] Although they were originally developed for delivery of parenteral nutrition, the use of PICCs has expanded to include chemotherapy administration, long‐term intravenous (IV) antibiotic treatment, and venous access when obtaining peripheral veins is difficult (eg, occluded peripheral veins, unusual venous anatomies).[2] Despite these roles, little is known about PICC use in hospitalized patients. This knowledge gap is important, as PICCs are placed in inpatient settings for a variety of reasons. Some of these reasons may not be appropriate, and inappropriate PICC use may worsen outcomes and increase healthcare costs.[3] In addition, PICCs are not innocuous and are frequently associated with important complications including thrombophlebitis, central‐lineassociated bloodstream infection and venous thromboembolism.[4, 5, 6] Therefore, understanding patterns and knowledge associated with PICC use is also an important patient safety concern.

As the main providers of inpatient care, hospitalists frequently order the insertion of PICCs and treat PICC‐related complications. Unfortunately, to date, no study has surveyed hospitalists regarding management or use of PICCs. Understanding hospitalist experiences, practice, opinions, and knowledge related to PICCs is therefore of significant interest when examining present‐day PICC use. To bridge this important knowledge gap and better understand these practices, we conducted a Web‐based survey of hospitalists in 5 healthcare systems in the state of Michigan.

METHODS

A convenience sample of hospitalists (N=227) was assembled from 5 large healthcare systems (representing 10 hospitals) that participate in the Hospital Medicine Safety (HMS) Consortium, a Blue Cross/Blue Shield of Michiganfunded statewide collaborative quality initiative. Individuals engaged in research, quality improvement, or leadership at HMS sites were invited to serve as site principal investigators (site PIs). Site PIs were responsible for obtaining regulatory approval at their parent facilities and disseminating the survey to providers in their group. Participation in the survey was solicited via e‐mail invitations from site PIs to hospitalists within their provider group. To encourage participation, a $10 electronic gift card was offered to respondents who successfully completed the survey. Reminder e‐mails were also sent each week by site PIs to augment participation. To enhance study recruitment, all responses were collected anonymously. The survey was administered between August 2012 and September 2012; data collection occurred for 5 weeks during this interval.

Survey questions were derived from our published, evidence‐based conceptual framework of PICC‐related complications. Briefly, this model identifies complications related to PICCs as arising from domains related to patient‐, provider‐, and device‐related characteristics based on existing evidence.[2] For our survey, questions were sourced from each of these domains so as to improve understanding of hospitalist experience, practice, opinions, and knowledge regarding PICC use. To ensure clarity of the survey questions, all questions were first pilot‐tested with a group of randomly selected hospitalist respondents at the University of Michigan Health System. Direct feedback obtained from these respondents was then used to iteratively improve each question. In order to generate holistic responses, questions were designed to generate a response reflective of the participants typical PICC use/subenario. We used SurveyMonkey to collect and manage survey data.

Statistical Analyses

Variation in hospitalist experience, reported practice, opinions, and knowledge regarding PICCs was assessed by hospitalist type (full time vs part time), years of practice (<1, 15, >5), and care‐delivery model (direct care vs learner‐based care). Bivariate comparisons were made using the 2 or Fisher exact tests as appropriate; 2‐sided with a P value <0.05 was considered statistically significant. All analyses were conducted using Stata version 11 (StataCorp, College Station, TX). Local institutional review board approval was obtained at each site participating in the survey.

RESULTS

A total of 227 surveys were administered and 144 responses collected, for a survey response rate of 63%. Each participating site had unique characteristics including size, number of hospitalists, and modality of PICC insertion (Table 1). Of the hospitalists who completed the survey, 81% held full‐time clinical positions and had been in practice an average of 5.6 years. Surveyed hospitalists reported caring for an average of 40.6 patients per week and ordering a mean of 2.9 (range, 015) PICCs per week of clinical service. Among survey respondents, 36% provided direct patient care, 34% provided care either directly or through mid‐level providers and housestaff, and 9% delivered care exclusively through mid‐level providers or housestaff (Table 2). As our survey was conducted anonymously, potential identifying information such as age, race, and sex of those responding was not collected.

Characteristics of Participating Sites
Survey SiteNo. of HospitalsNo. of Inpatient BedsNo. of Annual Inpatient EncountersNo. of HospitalistsFull‐Time Hospitalists, %Avg. No. Weeks/Year on ServiceAvg. Years of ExperienceNo. PICCs/Week, 2012Modality of PICC Insertion Available
  • NOTE: Abbreviations: Avg., average; PICC, peripherally inserted central catheter; VA, Veterans Affairs.

University of Michigan Health System1900+5,7754610025642Vascular access nurse
Ann Arbor VA Medical Center1135825165017.65.112Vascular access nurse
Spectrum Health System280014,0004780343.7556Interventional radiology
Trinity Health System36342,300678024431Interventional radiology and hospitalists
Henry Ford Health System31,1501,4505110020.45.615Vascular access nurse
Descriptive Characteristics of Study Population
CharacteristicTotal (N=144)
  • NOTE: Abbreviations: SD, standard deviation; VA, Veterans Affairs.

Hospitalist type, n (%)
Full time117 (81)
Part time19 (13)
Unknown8 (6)
Weeks/year on a clinical service, n (%)
<2024 (17)
20107 (74)
Unknown13 (9)
Mean (SD)25.5 (10.7)
Median26
Type of patients treated, n (%)
Adults only129 (90)
Adults and children7 (5)
Unknown8 (6)
Years in practice as a hospitalist, n (%)
581 (56)
>554 (38)
Unknown9 (6)
Model of care delivery, n (%)
Direct52 (36)
Some midlevel or housestaff providers (<50% of all encounters)49 (34)
Mostly midlevel or housestaff providers (>50% of all encounters)22 (15)
Only midlevel or housestaff providers13 (9)
Unknown8 (6)
Location of practice
Trinity Health System39 (27)
University of Michigan Health System37 (26)
Henry Ford Health System28 (19)
Spectrum Health System21 (15)
Ann Arbor VA Medical Center11 (8)
Unknown8 (6)

Hospitalist Experiences and Practice Related to Peripherally Inserted Central Catheters

According to responding hospitalists, the most common indications for PICC placement were long‐term IV antibiotic treatment (64%), followed by inability to obtain peripheral venous access (24%). Hospitalists reported an average duration of PICC placement of 17 days (range, 342 days). A significant percentage of hospitalists (93%) stated that they had cared for patients where a PICC was placed only for use during hospitalization, with the most common reason for such insertion being difficulty in otherwise securing venous access (67%). Respondents also reported caring for patients who had both PICCs and peripheral IV catheters in place at the same time; 49% stated that they had experienced this <5 times, whereas 33% stated they had experienced this 510 times. Furthermore, 87% of respondents indicated having admitted a patient who specifically requested a PICC due to prior difficulties with venous access. More than half of surveyed hospitalists (63%) admitted to having been contacted by a PICC nurse enquiring as to whether their patient might benefit from PICC insertion.

The majority of hospitalists (66%) reported that they specified the number of lumens when ordering PICCs. Thirty‐eight percent indicated that this decision was based on type of medication, whereas 35% selected the lowest number of lumens possible. A power PICC (specialized PICCs that are designed to withstand high‐pressure contrast injections), was specifically requested for radiographic studies (56%), infusion of large volume of fluids (10%), or was the default PICC type at their facility (34%).

A majority (74%) of survey respondents also reported that once inserted, PICCs were always used to obtain blood for routine laboratory testing. Moreover, 41% indicated that PICCs were also always used to obtain blood for microbiological cultures. The 3 most frequently encountered PICC‐related complications reported by hospitalists in our survey were blockage of a PICC lumen, bloodstream infection, and venous thromboembolism (VTE; Table 3).

Key Hospitalist Experience and Opinions Regarding PICCs
Hospitalist Experiences With PICCsTotal (N=144)
  • NOTE: Abbreviations: IV, intravenous; PICC, peripherally inserted central catheter.

  • Mean response values are reflected.

Primary indication for PICC placement*
Long‐term IV antibiotics64
Venous access in a patient with poor peripheral veins24
Parenteral nutrition5
Chemotherapy4
Patient specifically requested a PICC1
Unknown/other2
PICC placed only for venous access, n (%)
Yes135 (94)
No9 (6)
PICC placed only during hospitalization, n (%)
Yes134 (93)
No10 (7)
Notified by a PICC nurse (or other provider) that patient may need or benefit from a PICC, n (%)
Yes91 (63)
No53 (37)
How frequently PICCs are used to obtain blood for routine laboratory testing, n (%)
Always106 (74)
Unknown/other38 (26)
How frequently PICCs are used to obtain blood for blood cultures, n (%) 
Always59 (41)
Unknown/other85 (59)
Hospitalist Opinions on PICCsTotal (N=144)
In your opinion, is it appropriate to place a vascular in a hospitalized patient if other forms of peripheral access cannot be obtained? n (%)
Yes121 (84)
No21 (15)
Unknown2 (1)
In your opinion, should hospitalists be trained to insert PICCs? n (%)
No57 (40)
Yes, this is an important skill set for hospitalists46 (32)
Unsure39 (27)
Unknown/other2 (1)
Do you think the increasing number of vascular nurses and PICC nursing teams has influenced the use of PICCs in hospitalized patients? n (%)
Yes112 (78)
No30 (21)
Unknown2 (1)
What % of PICC insertions do you think may represent inappropriate use in your hospital? n (%)
<1053 (37)
102568 (47)
255018 (13)
>503 (2)
Unknown/other2 (1)

Hospitalist Opinions Regarding Peripherally Inserted Central Catheters

Compared with CVCs, 69% of hospitalists felt that PICCs were safer and more efficient because they could stay in place longer and were less likely to cause infection. Most (65%) also agreed that PICCs were more convenient than CVCs because they were inserted by PICC teams. Additionally, 74% of hospitalists felt that their patients preferred PICCs because they minimize pain from routine peripheral IV changes and phlebotomy. A majority of respondents (84%) indicated that it was appropriate to place a PICC if other forms of peripheral venous access could not be obtained. However, when specifically questioned, 47% of hospitalists indicated that at least 10%25% of PICCs placed in their hospitals might represent inappropriate use. A majority (78%) agreed with the statement that the increase in numbers of vascular nurses had influenced use of PICCs in hospitalized patients, but most (45%) were neutral when asked if PICCs were more cost‐effective than traditional CVCs.

Hospitalist Knowledge Regarding Risk of Peripherally Inserted Central CatheterRelated Venous Thromboembolism and Bloodstream Infection

Although 65% of responding hospitalists disagreed with the statement that PICCs were less likely to lead to VTE, important knowledge gaps regarding PICCs and VTE were identified (Table 4). For instance, only 4% of hospitalists were correctly aware that the PICC‐tip position is checked to reduce risk of PICC‐related VTE, and only 12% knew that the site of PICC insertion has also been associated with VTE risk. Although 85% of respondents stated they would prescribe a therapeutic dose of an anticoagulant in the case of PICC‐associated VTE, deviations from the guideline‐recommended 3‐month treatment period were noted. For example, 6% of hospitalists reported treating with anticoagulation for 6 months, and 19% stated they would treat as long as the PICC remained in place, plus an additional period of time (eg, 24 weeks) after removal. With respect to bloodstream infection, 92% of responding hospitalists correctly identified PICC duration and prompt removal as factors promoting PICC‐related bloodstream infection and 78% accurately identified components of the catheter‐associated bloodstream infection bundle. When specifically asked about factors associated with risk of PICC‐related bloodstream infection, only half of respondents recognized the number of PICC lumens as being associated with this outcome.

Key Knowledge Gaps and Variation Regarding PICC‐Related VTE
 Total (N=144)
  • NOTE: Abbreviations: ACCP, American College of Chest Physicians; DVT, deep venous thrombosis; PICC, peripherally inserted central catheter; VTE, venous thromboembolism.

  • Correct answer.

  • This represents an unresolved issue; thus, there is no correct guideline recommended answer.

Why is the position of the PICC tip checked after bedside PICC insertion? n (%) 
To decrease the risk of arrhythmia related to right‐atrial positioning108 (75)
To minimize the risk of VTEa6 (4)
To ensure it is not accidentally placed into an artery16 (11)
For documentation purposes (to reduce the risk of lawsuits related to line‐insertion complications)6 (4)
Unsure/Unknown8 (6)
According to the 2012 ACCP Guidelines on VTE prevention, is pharmacologic prophylaxis for DVT recommended in patients who receive long‐term PICCs? n (%)
No; no anticoagulant prophylaxis is recommended for patients who receive long‐term PICCsa107 (74)
Yes, but the choice and duration of anticoagulant is at the discretion of the provider23 (16)
Yes; aspirin is recommended for 3 months4 (3)
Yes; anticoagulation with warfarin or enoxaparin is recommended for 3 months3 (2)
Yes; anticoagulation with warfarin or enoxaparin is recommended for 6 months2 (1)
Unknown5 (4)
Assuming no contraindications exist, do you anticoagulate patients who develop a PICC‐associated DVT (with any therapeutic anticoagulant)? n (%)
Yesa122 (85)
No16 (11)
Unknown6 (4)
How long do you usually prescribe anticoagulation for patients who develop PICC‐associated DVT? n (%)
I don't prescribe anticoagulation12 (8)
1 month4 (3)
3 monthsa84 (58)
6 months8 (6)
As long as the line remains in place; I stop anticoagulation once the PICC comes out3 (2)
As long as the line remains in place and for an additional specified period of time after line removal, such as 2 or 4 weeks27 (19)
Unknown6 (4)
As part of the treatment of PICC‐related DVT, do you routinely remove the PICC?b n (%)
Yes102 (71)
No36 (25)
Unknown6 (4)

Variation in Hospitalist Knowledge, Experience, or Opinions

We assessed whether any of our findings varied according to hospitalist type (full time versus part time), years of practice (<1, 15, >5), and model of care delivery (direct care vs learner‐based care). Our analyses suggested that part‐time hospitalists were more likely to select rarely when it came to finding patients with a PICC and a working peripheral IV at the same time (74% vs 45%, P=0.02). Interestingly, a higher percentage of those in practice <5 years indicated that 10%25% of PICCs represented inappropriate placement (58% vs 33%, P<0.01) and that vascular nurses had influenced the use of PICCs in hospitalized patients (88% vs 69%, P=0.01). Lastly, a higher percentage of hospitalists who provided direct patient care reported that PICCs were always used to obtain blood for microbiological culture (54% vs 37%, P=0.05).

DISCUSSION

In this survey of hospitalists practicing at 5 large healthcare systems in Michigan, we observed significant variation in experience, reported practice, opinions, and knowledge related to PICCs. Our findings highlight important concerns related to inpatient PICC use and suggest a need for greater scrutiny related to these devices in these settings.

The use of PICCs in hospitalized patients has risen dramatically over the past decade. Though such growth is multifactorial and relates in part to increasing inpatient volume and complexity, hospitalists have increasingly turned to PICCs as a convenient and reliable tool to obtain venous access.[7] Indeed, in our survey, PICCs that were only used during hospitalization were most likely to be placed for this very reason. Because PICCs are safer to insert than CVCs and the original evidence regarding PICC‐related VTE or bloodstream infection suggested low rates of these events,[8, 9, 10, 11, 12, 13, 14] many hospitalists may not perceive these devices as being associated with significant risks. In fact, some have suggested that hospitalists be specifically trained to insert these devices, given their safety compared with traditional CVCs.[7]

However, accumulating evidence suggests that PICCs are associated with important complications.[5, 15, 16] In studies examining risk of bloodstream infection, PICCs were associated with significant risk of this outcome.[6, 17, 18] Recently, the presence of a PICC was identified as an independent predictor of VTE in hospitalized patients.[19] Several studies and systematic reviews have repeatedly demonstrated these findings.[19, 20, 21, 22] A recent systematic review examining nonpharmacologic methods to prevent catheter‐related thrombosis specifically called for avoidance of PICC insertion to prevent thrombosis in hospitalized patients.[23] Despite this growing evidence base, the use of PICCs in the inpatient setting is likely to rise, and our survey highlights several practices that may contribute to adverse outcomes. For instance, hospitalists in our survey were unlikely to remove a PICC until a patient was discharged, irrespective of the need for this device. As each day with a PICC increases the risk of complications, such practice poses potential patient safety concerns. Similarly, many hospitalists believe that PICCs are safer than CVCs, a viewpoint that does not stand up to increasing scrutiny and highlights important knowledge gaps. The risk of PICC‐related complications appears not to be a stationary target, but rather a dynamic balance that is influenced by patient‐, provider‐, and device‐specific characteristics.[2] Increasing discretionary use (especially for patients with poor peripheral venous access), forgetting at times that a patient has a PICC, and the finding that up to 25% of PICCs placed in their hospitals may be unnecessary underscore concerns regarding the safety of current practice trends. Interestingly, the viewpoints of hospitalists in practice <5 years and those providing direct patient care were more likely to reflect concerns regarding inappropriate placement, influence of vascular nurses, and use of PICCs for blood culture. This finding may reflect that these nuances are more recent phenomena or perhaps most apparent when care is delivered directly.

Our study must be interpreted in the context of several limitations. First, as this was a survey‐based study of a small, convenience sample of hospitalists in a single state, recall, respondent, and systematic biases remain threats to our findings. However, all site PIs encouraged survey participation and (through local dialogue) none were aware of material differences between those who did or did not participate in the study. Similarly, Michigan is a diverse and relatively large state, and our results should be generalizable to other settings; however, national studies are necessary to confirm our findings. Second, our response rate may be perceived as low; however, our rates are in accordance with, and, in fact, superior to those of many existing physician surveys.[24] Finally, only 1 federal facility was included in this study; thus, this care‐delivery model is underrepresented, limiting generalization of findings to other such sites.

However, our study also has important strengths. First, this is the only survey that specifically examines hospitalist viewpoints when it comes to PICCs. As hospitalists frequently order and/or insert these devices, their perspectives are highly pertinent to discussions regarding current PICC use. Second, our survey highlights several instances that may be associated with preventable patient harm and identifies areas where interventions may be valuable. For example, forgetting the presence of a device, keeping PICCs in place throughout hospitalization, and rendering treatment for PICC‐related VTE not in accordance with accepted guidelines are remediable practices that may lead to poor outcomes. Interventions such as device‐reminder alerts, provider education regarding complications from PICCs, and systematic efforts to identify and remove unnecessary PICCs may mitigate these problems. Finally, our findings highlight the need for data repositories that track PICC use and hospitalist practice on a national scale. Given the risk and significance of the complications associated with these devices, understanding the epidemiology, use, and potential misuse of PICCs are important areas for hospitalist research.

In conclusion, our study of hospitalist experience, practice, opinions, and knowledge related to PICCs suggests important gaps between available evidence and current practice. There is growing need for the development of appropriateness criteria to guide vascular access in inpatient settings.[25, 26] Such criteria should consider not only type of venous access device, but granular details including rationale for venous access, nature of the infusate, optimal number of lumens, and safest gauge when recommending devices. Until such criteria and comparative studies become available, hospitals should consider instituting policies to monitor PICC use with specific attention to indication for insertion, duration of placement, and complications. These interventions represent a first and necessary step in improving patient safety when it comes to preventing PICC‐related complications.

Disclosures

The Blue Cross/Blue Shield of Michigan Foundation in Detroit funded this study through an investigator‐initiated research proposal (1931‐PIRAP). The funding source, however, played no role in study design, acquisition of data, data analysis, or reporting of these results. The authors report no conflicts of interest.

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References
  1. Zingg W, Sandoz L, Inan C, et al. Hospital‐wide survey of the use of central venous catheters. J Hosp Infect. 2011;77(4):304308.
  2. Chopra V, Anand S, Krein SL, Chenoweth C, Saint S. Bloodstream infection, venous thrombosis, and peripherally inserted central catheters: reappraising the evidence. Am J Med. 2012;125(8):733741.
  3. Chopra V, Flanders SA, Saint S. The problem with peripherally inserted central catheters. JAMA. 2012;308(15):15271528.
  4. Evans RS, Sharp JH, Linford LH, et al. Reduction of peripherally inserted central catheter associated deep venous thrombosis [published online ahead of print August 1, 2012]. Chest. doi: 10.1378/chest.12–0923.
  5. Pikwer A, Akeson J, Lindgren S. Complications associated with peripheral or central routes for central venous cannulation. Anaesthesia. 2012;67(1):6571.
  6. Pongruangporn M, Ajenjo MC, Russo AJ, et al. Patient‐ and device‐specific risk factors for peripherally inserted central venous catheter‐related bloodstream infections. Infect Control Hosp Epidemiol. 2013;34(2):184189.
  7. Akers AS, Chelluri L. Peripherally inserted central catheter use in the hospitalized patient: is there a role for the hospitalist? J Hosp Med. 2009;4(6):E1E4.
  8. Chakravarthy SB, Rettmann J, Markewitz BA, Elliott G, Sarfati M, Nohavec R. Peripherally inserted central catheter (PICC)‐associated upper‐extremity deep venous thrombosis (UEDVT) in critical‐care setting. Chest. 2005;128(4 suppl S):193S194S.
  9. Cowl CT, Weinstock JV, Al‐Jurf A, Ephgrave K, Murray JA, Dillon K. Complications and cost associated with parenteral nutrition delivered to hospitalized patients through either subclavian or peripherally inserted central catheters. Clin Nutr. 2000;19(4):237243.
  10. Safdar N, Maki DG. Risk of catheter‐related bloodstream infection with peripherally inserted central venous catheters used in hospitalized patients. Chest. 2005;128(2):489495.
  11. Bottino J, McCredie KB, Groschel DH, Lawson M. Long‐term intravenous therapy with peripherally inserted silicone elastomer central venous catheters in patients with malignant diseases. Cancer. 1979;43(5):19371943.
  12. Giuffrida DJ, Bryan‐Brown CW, Lumb PD, Kwun KB, Rhoades HM. Central vs peripheral venous catheters in critically ill patients. Chest. 1986;90(6):806809.
  13. Graham DR, Keldermans MM, Klemm LW, Semenza NJ, Shafer ML. Infectious complications among patients receiving home intravenous therapy with peripheral, central, or peripherally placed central venous catheters. Am J Med. 1991;91(3B):95S100S.
  14. Monreal M, Lafoz E, Ruiz J, Valls R, Alastrue A. Upper‐extremity deep venous thrombosis and pulmonary embolism: a prospective study. Chest. 1991;99(2):280283.
  15. Saber W, Moua T, Williams EC, et al. Risk factors for catheter‐related thrombosis (CRT) in cancer patients: a patient‐level data (IPD) meta‐analysis of clinical trials and prospective studies. J Thromb Haemost. 2011;9(2):312319.
  16. Chemaly RF, Parres JB, Rehm SJ, et al. Venous thrombosis associated with peripherally inserted central catheters: a retrospective analysis of the Cleveland Clinic experience. Clin Infect Dis. 2002;34(9):11791183.
  17. Ajenjo MC, Morley JC, Russo AJ, et al. Peripherally inserted central venous catheter–associated bloodstream infections in hospitalized adult patients. Infect Control Hosp Epidemiol. 2011;32(2):125130.
  18. Al‐Tawfiq JA, Abed MS, Memish ZA. Peripherally inserted central catheter bloodstream infection surveillance rates in an acute care setting in Saudi Arabia. Ann Saudi Med. 2012;32(2):169173.
  19. Woller SC, Stevens SM, Jones JP, et al. Derivation and validation of a simple model to identify venous thromboembolism risk in medical patients. Am J Med. 2011;124(10):947.e942–954.e942.
  20. Evans RS, Sharp JH, Linford LH, et al. Risk of symptomatic DVT associated with peripherally inserted central catheters. Chest. 2010;138(4):803810.
  21. Fletcher JJ, Stetler W, Wilson TJ. The clinical significance of peripherally inserted central venous catheter‐related deep vein thrombosis. Neurocrit Care. 2011;15(3):454460.
  22. Mollee P, Jones M, Stackelroth J, et al. Catheter‐associated bloodstream infection incidence and risk factors in adults with cancer: a prospective cohort study. J Hosp Infect. 2011;78(1):2630.
  23. Mitchell MD, Agarwal R, Hecht TE, Umscheid CA. Nonpharmacologic interventions for prevention of catheter‐related thrombosis: a systematic review [published online ahead of print September 13, 2012]. J Crit Care. doi: 10.1016/j.jcrc.2012.07.007.
  24. Wiebe ER, Kaczorowski J, MacKay J. Why are response rates in clinician surveys declining? Can Fam Physician. 2012;58(4):e225e228.
  25. Shekelle PG, Park RE, Kahan JP, Leape LL, Kamberg CJ, Bernstein SJ. Sensitivity and specificity of the RAND/UCLA Appropriateness Method to identify the overuse and underuse of coronary revascularization and hysterectomy. J Clin Epidemiol. 2001;54(10):10041010.
  26. Kahan JP, Park RE, Leape LL, et al. Variations by specialty in physician ratings of the appropriateness and necessity of indications for procedures. Med Care. 1996;34(6):512523.
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Peripherally inserted central catheters (PICCs) have become among the most common central venous catheters (CVCs) used in contemporary medical practice.[1] Although they were originally developed for delivery of parenteral nutrition, the use of PICCs has expanded to include chemotherapy administration, long‐term intravenous (IV) antibiotic treatment, and venous access when obtaining peripheral veins is difficult (eg, occluded peripheral veins, unusual venous anatomies).[2] Despite these roles, little is known about PICC use in hospitalized patients. This knowledge gap is important, as PICCs are placed in inpatient settings for a variety of reasons. Some of these reasons may not be appropriate, and inappropriate PICC use may worsen outcomes and increase healthcare costs.[3] In addition, PICCs are not innocuous and are frequently associated with important complications including thrombophlebitis, central‐lineassociated bloodstream infection and venous thromboembolism.[4, 5, 6] Therefore, understanding patterns and knowledge associated with PICC use is also an important patient safety concern.

As the main providers of inpatient care, hospitalists frequently order the insertion of PICCs and treat PICC‐related complications. Unfortunately, to date, no study has surveyed hospitalists regarding management or use of PICCs. Understanding hospitalist experiences, practice, opinions, and knowledge related to PICCs is therefore of significant interest when examining present‐day PICC use. To bridge this important knowledge gap and better understand these practices, we conducted a Web‐based survey of hospitalists in 5 healthcare systems in the state of Michigan.

METHODS

A convenience sample of hospitalists (N=227) was assembled from 5 large healthcare systems (representing 10 hospitals) that participate in the Hospital Medicine Safety (HMS) Consortium, a Blue Cross/Blue Shield of Michiganfunded statewide collaborative quality initiative. Individuals engaged in research, quality improvement, or leadership at HMS sites were invited to serve as site principal investigators (site PIs). Site PIs were responsible for obtaining regulatory approval at their parent facilities and disseminating the survey to providers in their group. Participation in the survey was solicited via e‐mail invitations from site PIs to hospitalists within their provider group. To encourage participation, a $10 electronic gift card was offered to respondents who successfully completed the survey. Reminder e‐mails were also sent each week by site PIs to augment participation. To enhance study recruitment, all responses were collected anonymously. The survey was administered between August 2012 and September 2012; data collection occurred for 5 weeks during this interval.

Survey questions were derived from our published, evidence‐based conceptual framework of PICC‐related complications. Briefly, this model identifies complications related to PICCs as arising from domains related to patient‐, provider‐, and device‐related characteristics based on existing evidence.[2] For our survey, questions were sourced from each of these domains so as to improve understanding of hospitalist experience, practice, opinions, and knowledge regarding PICC use. To ensure clarity of the survey questions, all questions were first pilot‐tested with a group of randomly selected hospitalist respondents at the University of Michigan Health System. Direct feedback obtained from these respondents was then used to iteratively improve each question. In order to generate holistic responses, questions were designed to generate a response reflective of the participants typical PICC use/subenario. We used SurveyMonkey to collect and manage survey data.

Statistical Analyses

Variation in hospitalist experience, reported practice, opinions, and knowledge regarding PICCs was assessed by hospitalist type (full time vs part time), years of practice (<1, 15, >5), and care‐delivery model (direct care vs learner‐based care). Bivariate comparisons were made using the 2 or Fisher exact tests as appropriate; 2‐sided with a P value <0.05 was considered statistically significant. All analyses were conducted using Stata version 11 (StataCorp, College Station, TX). Local institutional review board approval was obtained at each site participating in the survey.

RESULTS

A total of 227 surveys were administered and 144 responses collected, for a survey response rate of 63%. Each participating site had unique characteristics including size, number of hospitalists, and modality of PICC insertion (Table 1). Of the hospitalists who completed the survey, 81% held full‐time clinical positions and had been in practice an average of 5.6 years. Surveyed hospitalists reported caring for an average of 40.6 patients per week and ordering a mean of 2.9 (range, 015) PICCs per week of clinical service. Among survey respondents, 36% provided direct patient care, 34% provided care either directly or through mid‐level providers and housestaff, and 9% delivered care exclusively through mid‐level providers or housestaff (Table 2). As our survey was conducted anonymously, potential identifying information such as age, race, and sex of those responding was not collected.

Characteristics of Participating Sites
Survey SiteNo. of HospitalsNo. of Inpatient BedsNo. of Annual Inpatient EncountersNo. of HospitalistsFull‐Time Hospitalists, %Avg. No. Weeks/Year on ServiceAvg. Years of ExperienceNo. PICCs/Week, 2012Modality of PICC Insertion Available
  • NOTE: Abbreviations: Avg., average; PICC, peripherally inserted central catheter; VA, Veterans Affairs.

University of Michigan Health System1900+5,7754610025642Vascular access nurse
Ann Arbor VA Medical Center1135825165017.65.112Vascular access nurse
Spectrum Health System280014,0004780343.7556Interventional radiology
Trinity Health System36342,300678024431Interventional radiology and hospitalists
Henry Ford Health System31,1501,4505110020.45.615Vascular access nurse
Descriptive Characteristics of Study Population
CharacteristicTotal (N=144)
  • NOTE: Abbreviations: SD, standard deviation; VA, Veterans Affairs.

Hospitalist type, n (%)
Full time117 (81)
Part time19 (13)
Unknown8 (6)
Weeks/year on a clinical service, n (%)
<2024 (17)
20107 (74)
Unknown13 (9)
Mean (SD)25.5 (10.7)
Median26
Type of patients treated, n (%)
Adults only129 (90)
Adults and children7 (5)
Unknown8 (6)
Years in practice as a hospitalist, n (%)
581 (56)
>554 (38)
Unknown9 (6)
Model of care delivery, n (%)
Direct52 (36)
Some midlevel or housestaff providers (<50% of all encounters)49 (34)
Mostly midlevel or housestaff providers (>50% of all encounters)22 (15)
Only midlevel or housestaff providers13 (9)
Unknown8 (6)
Location of practice
Trinity Health System39 (27)
University of Michigan Health System37 (26)
Henry Ford Health System28 (19)
Spectrum Health System21 (15)
Ann Arbor VA Medical Center11 (8)
Unknown8 (6)

Hospitalist Experiences and Practice Related to Peripherally Inserted Central Catheters

According to responding hospitalists, the most common indications for PICC placement were long‐term IV antibiotic treatment (64%), followed by inability to obtain peripheral venous access (24%). Hospitalists reported an average duration of PICC placement of 17 days (range, 342 days). A significant percentage of hospitalists (93%) stated that they had cared for patients where a PICC was placed only for use during hospitalization, with the most common reason for such insertion being difficulty in otherwise securing venous access (67%). Respondents also reported caring for patients who had both PICCs and peripheral IV catheters in place at the same time; 49% stated that they had experienced this <5 times, whereas 33% stated they had experienced this 510 times. Furthermore, 87% of respondents indicated having admitted a patient who specifically requested a PICC due to prior difficulties with venous access. More than half of surveyed hospitalists (63%) admitted to having been contacted by a PICC nurse enquiring as to whether their patient might benefit from PICC insertion.

The majority of hospitalists (66%) reported that they specified the number of lumens when ordering PICCs. Thirty‐eight percent indicated that this decision was based on type of medication, whereas 35% selected the lowest number of lumens possible. A power PICC (specialized PICCs that are designed to withstand high‐pressure contrast injections), was specifically requested for radiographic studies (56%), infusion of large volume of fluids (10%), or was the default PICC type at their facility (34%).

A majority (74%) of survey respondents also reported that once inserted, PICCs were always used to obtain blood for routine laboratory testing. Moreover, 41% indicated that PICCs were also always used to obtain blood for microbiological cultures. The 3 most frequently encountered PICC‐related complications reported by hospitalists in our survey were blockage of a PICC lumen, bloodstream infection, and venous thromboembolism (VTE; Table 3).

Key Hospitalist Experience and Opinions Regarding PICCs
Hospitalist Experiences With PICCsTotal (N=144)
  • NOTE: Abbreviations: IV, intravenous; PICC, peripherally inserted central catheter.

  • Mean response values are reflected.

Primary indication for PICC placement*
Long‐term IV antibiotics64
Venous access in a patient with poor peripheral veins24
Parenteral nutrition5
Chemotherapy4
Patient specifically requested a PICC1
Unknown/other2
PICC placed only for venous access, n (%)
Yes135 (94)
No9 (6)
PICC placed only during hospitalization, n (%)
Yes134 (93)
No10 (7)
Notified by a PICC nurse (or other provider) that patient may need or benefit from a PICC, n (%)
Yes91 (63)
No53 (37)
How frequently PICCs are used to obtain blood for routine laboratory testing, n (%)
Always106 (74)
Unknown/other38 (26)
How frequently PICCs are used to obtain blood for blood cultures, n (%) 
Always59 (41)
Unknown/other85 (59)
Hospitalist Opinions on PICCsTotal (N=144)
In your opinion, is it appropriate to place a vascular in a hospitalized patient if other forms of peripheral access cannot be obtained? n (%)
Yes121 (84)
No21 (15)
Unknown2 (1)
In your opinion, should hospitalists be trained to insert PICCs? n (%)
No57 (40)
Yes, this is an important skill set for hospitalists46 (32)
Unsure39 (27)
Unknown/other2 (1)
Do you think the increasing number of vascular nurses and PICC nursing teams has influenced the use of PICCs in hospitalized patients? n (%)
Yes112 (78)
No30 (21)
Unknown2 (1)
What % of PICC insertions do you think may represent inappropriate use in your hospital? n (%)
<1053 (37)
102568 (47)
255018 (13)
>503 (2)
Unknown/other2 (1)

Hospitalist Opinions Regarding Peripherally Inserted Central Catheters

Compared with CVCs, 69% of hospitalists felt that PICCs were safer and more efficient because they could stay in place longer and were less likely to cause infection. Most (65%) also agreed that PICCs were more convenient than CVCs because they were inserted by PICC teams. Additionally, 74% of hospitalists felt that their patients preferred PICCs because they minimize pain from routine peripheral IV changes and phlebotomy. A majority of respondents (84%) indicated that it was appropriate to place a PICC if other forms of peripheral venous access could not be obtained. However, when specifically questioned, 47% of hospitalists indicated that at least 10%25% of PICCs placed in their hospitals might represent inappropriate use. A majority (78%) agreed with the statement that the increase in numbers of vascular nurses had influenced use of PICCs in hospitalized patients, but most (45%) were neutral when asked if PICCs were more cost‐effective than traditional CVCs.

Hospitalist Knowledge Regarding Risk of Peripherally Inserted Central CatheterRelated Venous Thromboembolism and Bloodstream Infection

Although 65% of responding hospitalists disagreed with the statement that PICCs were less likely to lead to VTE, important knowledge gaps regarding PICCs and VTE were identified (Table 4). For instance, only 4% of hospitalists were correctly aware that the PICC‐tip position is checked to reduce risk of PICC‐related VTE, and only 12% knew that the site of PICC insertion has also been associated with VTE risk. Although 85% of respondents stated they would prescribe a therapeutic dose of an anticoagulant in the case of PICC‐associated VTE, deviations from the guideline‐recommended 3‐month treatment period were noted. For example, 6% of hospitalists reported treating with anticoagulation for 6 months, and 19% stated they would treat as long as the PICC remained in place, plus an additional period of time (eg, 24 weeks) after removal. With respect to bloodstream infection, 92% of responding hospitalists correctly identified PICC duration and prompt removal as factors promoting PICC‐related bloodstream infection and 78% accurately identified components of the catheter‐associated bloodstream infection bundle. When specifically asked about factors associated with risk of PICC‐related bloodstream infection, only half of respondents recognized the number of PICC lumens as being associated with this outcome.

Key Knowledge Gaps and Variation Regarding PICC‐Related VTE
 Total (N=144)
  • NOTE: Abbreviations: ACCP, American College of Chest Physicians; DVT, deep venous thrombosis; PICC, peripherally inserted central catheter; VTE, venous thromboembolism.

  • Correct answer.

  • This represents an unresolved issue; thus, there is no correct guideline recommended answer.

Why is the position of the PICC tip checked after bedside PICC insertion? n (%) 
To decrease the risk of arrhythmia related to right‐atrial positioning108 (75)
To minimize the risk of VTEa6 (4)
To ensure it is not accidentally placed into an artery16 (11)
For documentation purposes (to reduce the risk of lawsuits related to line‐insertion complications)6 (4)
Unsure/Unknown8 (6)
According to the 2012 ACCP Guidelines on VTE prevention, is pharmacologic prophylaxis for DVT recommended in patients who receive long‐term PICCs? n (%)
No; no anticoagulant prophylaxis is recommended for patients who receive long‐term PICCsa107 (74)
Yes, but the choice and duration of anticoagulant is at the discretion of the provider23 (16)
Yes; aspirin is recommended for 3 months4 (3)
Yes; anticoagulation with warfarin or enoxaparin is recommended for 3 months3 (2)
Yes; anticoagulation with warfarin or enoxaparin is recommended for 6 months2 (1)
Unknown5 (4)
Assuming no contraindications exist, do you anticoagulate patients who develop a PICC‐associated DVT (with any therapeutic anticoagulant)? n (%)
Yesa122 (85)
No16 (11)
Unknown6 (4)
How long do you usually prescribe anticoagulation for patients who develop PICC‐associated DVT? n (%)
I don't prescribe anticoagulation12 (8)
1 month4 (3)
3 monthsa84 (58)
6 months8 (6)
As long as the line remains in place; I stop anticoagulation once the PICC comes out3 (2)
As long as the line remains in place and for an additional specified period of time after line removal, such as 2 or 4 weeks27 (19)
Unknown6 (4)
As part of the treatment of PICC‐related DVT, do you routinely remove the PICC?b n (%)
Yes102 (71)
No36 (25)
Unknown6 (4)

Variation in Hospitalist Knowledge, Experience, or Opinions

We assessed whether any of our findings varied according to hospitalist type (full time versus part time), years of practice (<1, 15, >5), and model of care delivery (direct care vs learner‐based care). Our analyses suggested that part‐time hospitalists were more likely to select rarely when it came to finding patients with a PICC and a working peripheral IV at the same time (74% vs 45%, P=0.02). Interestingly, a higher percentage of those in practice <5 years indicated that 10%25% of PICCs represented inappropriate placement (58% vs 33%, P<0.01) and that vascular nurses had influenced the use of PICCs in hospitalized patients (88% vs 69%, P=0.01). Lastly, a higher percentage of hospitalists who provided direct patient care reported that PICCs were always used to obtain blood for microbiological culture (54% vs 37%, P=0.05).

DISCUSSION

In this survey of hospitalists practicing at 5 large healthcare systems in Michigan, we observed significant variation in experience, reported practice, opinions, and knowledge related to PICCs. Our findings highlight important concerns related to inpatient PICC use and suggest a need for greater scrutiny related to these devices in these settings.

The use of PICCs in hospitalized patients has risen dramatically over the past decade. Though such growth is multifactorial and relates in part to increasing inpatient volume and complexity, hospitalists have increasingly turned to PICCs as a convenient and reliable tool to obtain venous access.[7] Indeed, in our survey, PICCs that were only used during hospitalization were most likely to be placed for this very reason. Because PICCs are safer to insert than CVCs and the original evidence regarding PICC‐related VTE or bloodstream infection suggested low rates of these events,[8, 9, 10, 11, 12, 13, 14] many hospitalists may not perceive these devices as being associated with significant risks. In fact, some have suggested that hospitalists be specifically trained to insert these devices, given their safety compared with traditional CVCs.[7]

However, accumulating evidence suggests that PICCs are associated with important complications.[5, 15, 16] In studies examining risk of bloodstream infection, PICCs were associated with significant risk of this outcome.[6, 17, 18] Recently, the presence of a PICC was identified as an independent predictor of VTE in hospitalized patients.[19] Several studies and systematic reviews have repeatedly demonstrated these findings.[19, 20, 21, 22] A recent systematic review examining nonpharmacologic methods to prevent catheter‐related thrombosis specifically called for avoidance of PICC insertion to prevent thrombosis in hospitalized patients.[23] Despite this growing evidence base, the use of PICCs in the inpatient setting is likely to rise, and our survey highlights several practices that may contribute to adverse outcomes. For instance, hospitalists in our survey were unlikely to remove a PICC until a patient was discharged, irrespective of the need for this device. As each day with a PICC increases the risk of complications, such practice poses potential patient safety concerns. Similarly, many hospitalists believe that PICCs are safer than CVCs, a viewpoint that does not stand up to increasing scrutiny and highlights important knowledge gaps. The risk of PICC‐related complications appears not to be a stationary target, but rather a dynamic balance that is influenced by patient‐, provider‐, and device‐specific characteristics.[2] Increasing discretionary use (especially for patients with poor peripheral venous access), forgetting at times that a patient has a PICC, and the finding that up to 25% of PICCs placed in their hospitals may be unnecessary underscore concerns regarding the safety of current practice trends. Interestingly, the viewpoints of hospitalists in practice <5 years and those providing direct patient care were more likely to reflect concerns regarding inappropriate placement, influence of vascular nurses, and use of PICCs for blood culture. This finding may reflect that these nuances are more recent phenomena or perhaps most apparent when care is delivered directly.

Our study must be interpreted in the context of several limitations. First, as this was a survey‐based study of a small, convenience sample of hospitalists in a single state, recall, respondent, and systematic biases remain threats to our findings. However, all site PIs encouraged survey participation and (through local dialogue) none were aware of material differences between those who did or did not participate in the study. Similarly, Michigan is a diverse and relatively large state, and our results should be generalizable to other settings; however, national studies are necessary to confirm our findings. Second, our response rate may be perceived as low; however, our rates are in accordance with, and, in fact, superior to those of many existing physician surveys.[24] Finally, only 1 federal facility was included in this study; thus, this care‐delivery model is underrepresented, limiting generalization of findings to other such sites.

However, our study also has important strengths. First, this is the only survey that specifically examines hospitalist viewpoints when it comes to PICCs. As hospitalists frequently order and/or insert these devices, their perspectives are highly pertinent to discussions regarding current PICC use. Second, our survey highlights several instances that may be associated with preventable patient harm and identifies areas where interventions may be valuable. For example, forgetting the presence of a device, keeping PICCs in place throughout hospitalization, and rendering treatment for PICC‐related VTE not in accordance with accepted guidelines are remediable practices that may lead to poor outcomes. Interventions such as device‐reminder alerts, provider education regarding complications from PICCs, and systematic efforts to identify and remove unnecessary PICCs may mitigate these problems. Finally, our findings highlight the need for data repositories that track PICC use and hospitalist practice on a national scale. Given the risk and significance of the complications associated with these devices, understanding the epidemiology, use, and potential misuse of PICCs are important areas for hospitalist research.

In conclusion, our study of hospitalist experience, practice, opinions, and knowledge related to PICCs suggests important gaps between available evidence and current practice. There is growing need for the development of appropriateness criteria to guide vascular access in inpatient settings.[25, 26] Such criteria should consider not only type of venous access device, but granular details including rationale for venous access, nature of the infusate, optimal number of lumens, and safest gauge when recommending devices. Until such criteria and comparative studies become available, hospitals should consider instituting policies to monitor PICC use with specific attention to indication for insertion, duration of placement, and complications. These interventions represent a first and necessary step in improving patient safety when it comes to preventing PICC‐related complications.

Disclosures

The Blue Cross/Blue Shield of Michigan Foundation in Detroit funded this study through an investigator‐initiated research proposal (1931‐PIRAP). The funding source, however, played no role in study design, acquisition of data, data analysis, or reporting of these results. The authors report no conflicts of interest.

Peripherally inserted central catheters (PICCs) have become among the most common central venous catheters (CVCs) used in contemporary medical practice.[1] Although they were originally developed for delivery of parenteral nutrition, the use of PICCs has expanded to include chemotherapy administration, long‐term intravenous (IV) antibiotic treatment, and venous access when obtaining peripheral veins is difficult (eg, occluded peripheral veins, unusual venous anatomies).[2] Despite these roles, little is known about PICC use in hospitalized patients. This knowledge gap is important, as PICCs are placed in inpatient settings for a variety of reasons. Some of these reasons may not be appropriate, and inappropriate PICC use may worsen outcomes and increase healthcare costs.[3] In addition, PICCs are not innocuous and are frequently associated with important complications including thrombophlebitis, central‐lineassociated bloodstream infection and venous thromboembolism.[4, 5, 6] Therefore, understanding patterns and knowledge associated with PICC use is also an important patient safety concern.

As the main providers of inpatient care, hospitalists frequently order the insertion of PICCs and treat PICC‐related complications. Unfortunately, to date, no study has surveyed hospitalists regarding management or use of PICCs. Understanding hospitalist experiences, practice, opinions, and knowledge related to PICCs is therefore of significant interest when examining present‐day PICC use. To bridge this important knowledge gap and better understand these practices, we conducted a Web‐based survey of hospitalists in 5 healthcare systems in the state of Michigan.

METHODS

A convenience sample of hospitalists (N=227) was assembled from 5 large healthcare systems (representing 10 hospitals) that participate in the Hospital Medicine Safety (HMS) Consortium, a Blue Cross/Blue Shield of Michiganfunded statewide collaborative quality initiative. Individuals engaged in research, quality improvement, or leadership at HMS sites were invited to serve as site principal investigators (site PIs). Site PIs were responsible for obtaining regulatory approval at their parent facilities and disseminating the survey to providers in their group. Participation in the survey was solicited via e‐mail invitations from site PIs to hospitalists within their provider group. To encourage participation, a $10 electronic gift card was offered to respondents who successfully completed the survey. Reminder e‐mails were also sent each week by site PIs to augment participation. To enhance study recruitment, all responses were collected anonymously. The survey was administered between August 2012 and September 2012; data collection occurred for 5 weeks during this interval.

Survey questions were derived from our published, evidence‐based conceptual framework of PICC‐related complications. Briefly, this model identifies complications related to PICCs as arising from domains related to patient‐, provider‐, and device‐related characteristics based on existing evidence.[2] For our survey, questions were sourced from each of these domains so as to improve understanding of hospitalist experience, practice, opinions, and knowledge regarding PICC use. To ensure clarity of the survey questions, all questions were first pilot‐tested with a group of randomly selected hospitalist respondents at the University of Michigan Health System. Direct feedback obtained from these respondents was then used to iteratively improve each question. In order to generate holistic responses, questions were designed to generate a response reflective of the participants typical PICC use/subenario. We used SurveyMonkey to collect and manage survey data.

Statistical Analyses

Variation in hospitalist experience, reported practice, opinions, and knowledge regarding PICCs was assessed by hospitalist type (full time vs part time), years of practice (<1, 15, >5), and care‐delivery model (direct care vs learner‐based care). Bivariate comparisons were made using the 2 or Fisher exact tests as appropriate; 2‐sided with a P value <0.05 was considered statistically significant. All analyses were conducted using Stata version 11 (StataCorp, College Station, TX). Local institutional review board approval was obtained at each site participating in the survey.

RESULTS

A total of 227 surveys were administered and 144 responses collected, for a survey response rate of 63%. Each participating site had unique characteristics including size, number of hospitalists, and modality of PICC insertion (Table 1). Of the hospitalists who completed the survey, 81% held full‐time clinical positions and had been in practice an average of 5.6 years. Surveyed hospitalists reported caring for an average of 40.6 patients per week and ordering a mean of 2.9 (range, 015) PICCs per week of clinical service. Among survey respondents, 36% provided direct patient care, 34% provided care either directly or through mid‐level providers and housestaff, and 9% delivered care exclusively through mid‐level providers or housestaff (Table 2). As our survey was conducted anonymously, potential identifying information such as age, race, and sex of those responding was not collected.

Characteristics of Participating Sites
Survey SiteNo. of HospitalsNo. of Inpatient BedsNo. of Annual Inpatient EncountersNo. of HospitalistsFull‐Time Hospitalists, %Avg. No. Weeks/Year on ServiceAvg. Years of ExperienceNo. PICCs/Week, 2012Modality of PICC Insertion Available
  • NOTE: Abbreviations: Avg., average; PICC, peripherally inserted central catheter; VA, Veterans Affairs.

University of Michigan Health System1900+5,7754610025642Vascular access nurse
Ann Arbor VA Medical Center1135825165017.65.112Vascular access nurse
Spectrum Health System280014,0004780343.7556Interventional radiology
Trinity Health System36342,300678024431Interventional radiology and hospitalists
Henry Ford Health System31,1501,4505110020.45.615Vascular access nurse
Descriptive Characteristics of Study Population
CharacteristicTotal (N=144)
  • NOTE: Abbreviations: SD, standard deviation; VA, Veterans Affairs.

Hospitalist type, n (%)
Full time117 (81)
Part time19 (13)
Unknown8 (6)
Weeks/year on a clinical service, n (%)
<2024 (17)
20107 (74)
Unknown13 (9)
Mean (SD)25.5 (10.7)
Median26
Type of patients treated, n (%)
Adults only129 (90)
Adults and children7 (5)
Unknown8 (6)
Years in practice as a hospitalist, n (%)
581 (56)
>554 (38)
Unknown9 (6)
Model of care delivery, n (%)
Direct52 (36)
Some midlevel or housestaff providers (<50% of all encounters)49 (34)
Mostly midlevel or housestaff providers (>50% of all encounters)22 (15)
Only midlevel or housestaff providers13 (9)
Unknown8 (6)
Location of practice
Trinity Health System39 (27)
University of Michigan Health System37 (26)
Henry Ford Health System28 (19)
Spectrum Health System21 (15)
Ann Arbor VA Medical Center11 (8)
Unknown8 (6)

Hospitalist Experiences and Practice Related to Peripherally Inserted Central Catheters

According to responding hospitalists, the most common indications for PICC placement were long‐term IV antibiotic treatment (64%), followed by inability to obtain peripheral venous access (24%). Hospitalists reported an average duration of PICC placement of 17 days (range, 342 days). A significant percentage of hospitalists (93%) stated that they had cared for patients where a PICC was placed only for use during hospitalization, with the most common reason for such insertion being difficulty in otherwise securing venous access (67%). Respondents also reported caring for patients who had both PICCs and peripheral IV catheters in place at the same time; 49% stated that they had experienced this <5 times, whereas 33% stated they had experienced this 510 times. Furthermore, 87% of respondents indicated having admitted a patient who specifically requested a PICC due to prior difficulties with venous access. More than half of surveyed hospitalists (63%) admitted to having been contacted by a PICC nurse enquiring as to whether their patient might benefit from PICC insertion.

The majority of hospitalists (66%) reported that they specified the number of lumens when ordering PICCs. Thirty‐eight percent indicated that this decision was based on type of medication, whereas 35% selected the lowest number of lumens possible. A power PICC (specialized PICCs that are designed to withstand high‐pressure contrast injections), was specifically requested for radiographic studies (56%), infusion of large volume of fluids (10%), or was the default PICC type at their facility (34%).

A majority (74%) of survey respondents also reported that once inserted, PICCs were always used to obtain blood for routine laboratory testing. Moreover, 41% indicated that PICCs were also always used to obtain blood for microbiological cultures. The 3 most frequently encountered PICC‐related complications reported by hospitalists in our survey were blockage of a PICC lumen, bloodstream infection, and venous thromboembolism (VTE; Table 3).

Key Hospitalist Experience and Opinions Regarding PICCs
Hospitalist Experiences With PICCsTotal (N=144)
  • NOTE: Abbreviations: IV, intravenous; PICC, peripherally inserted central catheter.

  • Mean response values are reflected.

Primary indication for PICC placement*
Long‐term IV antibiotics64
Venous access in a patient with poor peripheral veins24
Parenteral nutrition5
Chemotherapy4
Patient specifically requested a PICC1
Unknown/other2
PICC placed only for venous access, n (%)
Yes135 (94)
No9 (6)
PICC placed only during hospitalization, n (%)
Yes134 (93)
No10 (7)
Notified by a PICC nurse (or other provider) that patient may need or benefit from a PICC, n (%)
Yes91 (63)
No53 (37)
How frequently PICCs are used to obtain blood for routine laboratory testing, n (%)
Always106 (74)
Unknown/other38 (26)
How frequently PICCs are used to obtain blood for blood cultures, n (%) 
Always59 (41)
Unknown/other85 (59)
Hospitalist Opinions on PICCsTotal (N=144)
In your opinion, is it appropriate to place a vascular in a hospitalized patient if other forms of peripheral access cannot be obtained? n (%)
Yes121 (84)
No21 (15)
Unknown2 (1)
In your opinion, should hospitalists be trained to insert PICCs? n (%)
No57 (40)
Yes, this is an important skill set for hospitalists46 (32)
Unsure39 (27)
Unknown/other2 (1)
Do you think the increasing number of vascular nurses and PICC nursing teams has influenced the use of PICCs in hospitalized patients? n (%)
Yes112 (78)
No30 (21)
Unknown2 (1)
What % of PICC insertions do you think may represent inappropriate use in your hospital? n (%)
<1053 (37)
102568 (47)
255018 (13)
>503 (2)
Unknown/other2 (1)

Hospitalist Opinions Regarding Peripherally Inserted Central Catheters

Compared with CVCs, 69% of hospitalists felt that PICCs were safer and more efficient because they could stay in place longer and were less likely to cause infection. Most (65%) also agreed that PICCs were more convenient than CVCs because they were inserted by PICC teams. Additionally, 74% of hospitalists felt that their patients preferred PICCs because they minimize pain from routine peripheral IV changes and phlebotomy. A majority of respondents (84%) indicated that it was appropriate to place a PICC if other forms of peripheral venous access could not be obtained. However, when specifically questioned, 47% of hospitalists indicated that at least 10%25% of PICCs placed in their hospitals might represent inappropriate use. A majority (78%) agreed with the statement that the increase in numbers of vascular nurses had influenced use of PICCs in hospitalized patients, but most (45%) were neutral when asked if PICCs were more cost‐effective than traditional CVCs.

Hospitalist Knowledge Regarding Risk of Peripherally Inserted Central CatheterRelated Venous Thromboembolism and Bloodstream Infection

Although 65% of responding hospitalists disagreed with the statement that PICCs were less likely to lead to VTE, important knowledge gaps regarding PICCs and VTE were identified (Table 4). For instance, only 4% of hospitalists were correctly aware that the PICC‐tip position is checked to reduce risk of PICC‐related VTE, and only 12% knew that the site of PICC insertion has also been associated with VTE risk. Although 85% of respondents stated they would prescribe a therapeutic dose of an anticoagulant in the case of PICC‐associated VTE, deviations from the guideline‐recommended 3‐month treatment period were noted. For example, 6% of hospitalists reported treating with anticoagulation for 6 months, and 19% stated they would treat as long as the PICC remained in place, plus an additional period of time (eg, 24 weeks) after removal. With respect to bloodstream infection, 92% of responding hospitalists correctly identified PICC duration and prompt removal as factors promoting PICC‐related bloodstream infection and 78% accurately identified components of the catheter‐associated bloodstream infection bundle. When specifically asked about factors associated with risk of PICC‐related bloodstream infection, only half of respondents recognized the number of PICC lumens as being associated with this outcome.

Key Knowledge Gaps and Variation Regarding PICC‐Related VTE
 Total (N=144)
  • NOTE: Abbreviations: ACCP, American College of Chest Physicians; DVT, deep venous thrombosis; PICC, peripherally inserted central catheter; VTE, venous thromboembolism.

  • Correct answer.

  • This represents an unresolved issue; thus, there is no correct guideline recommended answer.

Why is the position of the PICC tip checked after bedside PICC insertion? n (%) 
To decrease the risk of arrhythmia related to right‐atrial positioning108 (75)
To minimize the risk of VTEa6 (4)
To ensure it is not accidentally placed into an artery16 (11)
For documentation purposes (to reduce the risk of lawsuits related to line‐insertion complications)6 (4)
Unsure/Unknown8 (6)
According to the 2012 ACCP Guidelines on VTE prevention, is pharmacologic prophylaxis for DVT recommended in patients who receive long‐term PICCs? n (%)
No; no anticoagulant prophylaxis is recommended for patients who receive long‐term PICCsa107 (74)
Yes, but the choice and duration of anticoagulant is at the discretion of the provider23 (16)
Yes; aspirin is recommended for 3 months4 (3)
Yes; anticoagulation with warfarin or enoxaparin is recommended for 3 months3 (2)
Yes; anticoagulation with warfarin or enoxaparin is recommended for 6 months2 (1)
Unknown5 (4)
Assuming no contraindications exist, do you anticoagulate patients who develop a PICC‐associated DVT (with any therapeutic anticoagulant)? n (%)
Yesa122 (85)
No16 (11)
Unknown6 (4)
How long do you usually prescribe anticoagulation for patients who develop PICC‐associated DVT? n (%)
I don't prescribe anticoagulation12 (8)
1 month4 (3)
3 monthsa84 (58)
6 months8 (6)
As long as the line remains in place; I stop anticoagulation once the PICC comes out3 (2)
As long as the line remains in place and for an additional specified period of time after line removal, such as 2 or 4 weeks27 (19)
Unknown6 (4)
As part of the treatment of PICC‐related DVT, do you routinely remove the PICC?b n (%)
Yes102 (71)
No36 (25)
Unknown6 (4)

Variation in Hospitalist Knowledge, Experience, or Opinions

We assessed whether any of our findings varied according to hospitalist type (full time versus part time), years of practice (<1, 15, >5), and model of care delivery (direct care vs learner‐based care). Our analyses suggested that part‐time hospitalists were more likely to select rarely when it came to finding patients with a PICC and a working peripheral IV at the same time (74% vs 45%, P=0.02). Interestingly, a higher percentage of those in practice <5 years indicated that 10%25% of PICCs represented inappropriate placement (58% vs 33%, P<0.01) and that vascular nurses had influenced the use of PICCs in hospitalized patients (88% vs 69%, P=0.01). Lastly, a higher percentage of hospitalists who provided direct patient care reported that PICCs were always used to obtain blood for microbiological culture (54% vs 37%, P=0.05).

DISCUSSION

In this survey of hospitalists practicing at 5 large healthcare systems in Michigan, we observed significant variation in experience, reported practice, opinions, and knowledge related to PICCs. Our findings highlight important concerns related to inpatient PICC use and suggest a need for greater scrutiny related to these devices in these settings.

The use of PICCs in hospitalized patients has risen dramatically over the past decade. Though such growth is multifactorial and relates in part to increasing inpatient volume and complexity, hospitalists have increasingly turned to PICCs as a convenient and reliable tool to obtain venous access.[7] Indeed, in our survey, PICCs that were only used during hospitalization were most likely to be placed for this very reason. Because PICCs are safer to insert than CVCs and the original evidence regarding PICC‐related VTE or bloodstream infection suggested low rates of these events,[8, 9, 10, 11, 12, 13, 14] many hospitalists may not perceive these devices as being associated with significant risks. In fact, some have suggested that hospitalists be specifically trained to insert these devices, given their safety compared with traditional CVCs.[7]

However, accumulating evidence suggests that PICCs are associated with important complications.[5, 15, 16] In studies examining risk of bloodstream infection, PICCs were associated with significant risk of this outcome.[6, 17, 18] Recently, the presence of a PICC was identified as an independent predictor of VTE in hospitalized patients.[19] Several studies and systematic reviews have repeatedly demonstrated these findings.[19, 20, 21, 22] A recent systematic review examining nonpharmacologic methods to prevent catheter‐related thrombosis specifically called for avoidance of PICC insertion to prevent thrombosis in hospitalized patients.[23] Despite this growing evidence base, the use of PICCs in the inpatient setting is likely to rise, and our survey highlights several practices that may contribute to adverse outcomes. For instance, hospitalists in our survey were unlikely to remove a PICC until a patient was discharged, irrespective of the need for this device. As each day with a PICC increases the risk of complications, such practice poses potential patient safety concerns. Similarly, many hospitalists believe that PICCs are safer than CVCs, a viewpoint that does not stand up to increasing scrutiny and highlights important knowledge gaps. The risk of PICC‐related complications appears not to be a stationary target, but rather a dynamic balance that is influenced by patient‐, provider‐, and device‐specific characteristics.[2] Increasing discretionary use (especially for patients with poor peripheral venous access), forgetting at times that a patient has a PICC, and the finding that up to 25% of PICCs placed in their hospitals may be unnecessary underscore concerns regarding the safety of current practice trends. Interestingly, the viewpoints of hospitalists in practice <5 years and those providing direct patient care were more likely to reflect concerns regarding inappropriate placement, influence of vascular nurses, and use of PICCs for blood culture. This finding may reflect that these nuances are more recent phenomena or perhaps most apparent when care is delivered directly.

Our study must be interpreted in the context of several limitations. First, as this was a survey‐based study of a small, convenience sample of hospitalists in a single state, recall, respondent, and systematic biases remain threats to our findings. However, all site PIs encouraged survey participation and (through local dialogue) none were aware of material differences between those who did or did not participate in the study. Similarly, Michigan is a diverse and relatively large state, and our results should be generalizable to other settings; however, national studies are necessary to confirm our findings. Second, our response rate may be perceived as low; however, our rates are in accordance with, and, in fact, superior to those of many existing physician surveys.[24] Finally, only 1 federal facility was included in this study; thus, this care‐delivery model is underrepresented, limiting generalization of findings to other such sites.

However, our study also has important strengths. First, this is the only survey that specifically examines hospitalist viewpoints when it comes to PICCs. As hospitalists frequently order and/or insert these devices, their perspectives are highly pertinent to discussions regarding current PICC use. Second, our survey highlights several instances that may be associated with preventable patient harm and identifies areas where interventions may be valuable. For example, forgetting the presence of a device, keeping PICCs in place throughout hospitalization, and rendering treatment for PICC‐related VTE not in accordance with accepted guidelines are remediable practices that may lead to poor outcomes. Interventions such as device‐reminder alerts, provider education regarding complications from PICCs, and systematic efforts to identify and remove unnecessary PICCs may mitigate these problems. Finally, our findings highlight the need for data repositories that track PICC use and hospitalist practice on a national scale. Given the risk and significance of the complications associated with these devices, understanding the epidemiology, use, and potential misuse of PICCs are important areas for hospitalist research.

In conclusion, our study of hospitalist experience, practice, opinions, and knowledge related to PICCs suggests important gaps between available evidence and current practice. There is growing need for the development of appropriateness criteria to guide vascular access in inpatient settings.[25, 26] Such criteria should consider not only type of venous access device, but granular details including rationale for venous access, nature of the infusate, optimal number of lumens, and safest gauge when recommending devices. Until such criteria and comparative studies become available, hospitals should consider instituting policies to monitor PICC use with specific attention to indication for insertion, duration of placement, and complications. These interventions represent a first and necessary step in improving patient safety when it comes to preventing PICC‐related complications.

Disclosures

The Blue Cross/Blue Shield of Michigan Foundation in Detroit funded this study through an investigator‐initiated research proposal (1931‐PIRAP). The funding source, however, played no role in study design, acquisition of data, data analysis, or reporting of these results. The authors report no conflicts of interest.

References
  1. Zingg W, Sandoz L, Inan C, et al. Hospital‐wide survey of the use of central venous catheters. J Hosp Infect. 2011;77(4):304308.
  2. Chopra V, Anand S, Krein SL, Chenoweth C, Saint S. Bloodstream infection, venous thrombosis, and peripherally inserted central catheters: reappraising the evidence. Am J Med. 2012;125(8):733741.
  3. Chopra V, Flanders SA, Saint S. The problem with peripherally inserted central catheters. JAMA. 2012;308(15):15271528.
  4. Evans RS, Sharp JH, Linford LH, et al. Reduction of peripherally inserted central catheter associated deep venous thrombosis [published online ahead of print August 1, 2012]. Chest. doi: 10.1378/chest.12–0923.
  5. Pikwer A, Akeson J, Lindgren S. Complications associated with peripheral or central routes for central venous cannulation. Anaesthesia. 2012;67(1):6571.
  6. Pongruangporn M, Ajenjo MC, Russo AJ, et al. Patient‐ and device‐specific risk factors for peripherally inserted central venous catheter‐related bloodstream infections. Infect Control Hosp Epidemiol. 2013;34(2):184189.
  7. Akers AS, Chelluri L. Peripherally inserted central catheter use in the hospitalized patient: is there a role for the hospitalist? J Hosp Med. 2009;4(6):E1E4.
  8. Chakravarthy SB, Rettmann J, Markewitz BA, Elliott G, Sarfati M, Nohavec R. Peripherally inserted central catheter (PICC)‐associated upper‐extremity deep venous thrombosis (UEDVT) in critical‐care setting. Chest. 2005;128(4 suppl S):193S194S.
  9. Cowl CT, Weinstock JV, Al‐Jurf A, Ephgrave K, Murray JA, Dillon K. Complications and cost associated with parenteral nutrition delivered to hospitalized patients through either subclavian or peripherally inserted central catheters. Clin Nutr. 2000;19(4):237243.
  10. Safdar N, Maki DG. Risk of catheter‐related bloodstream infection with peripherally inserted central venous catheters used in hospitalized patients. Chest. 2005;128(2):489495.
  11. Bottino J, McCredie KB, Groschel DH, Lawson M. Long‐term intravenous therapy with peripherally inserted silicone elastomer central venous catheters in patients with malignant diseases. Cancer. 1979;43(5):19371943.
  12. Giuffrida DJ, Bryan‐Brown CW, Lumb PD, Kwun KB, Rhoades HM. Central vs peripheral venous catheters in critically ill patients. Chest. 1986;90(6):806809.
  13. Graham DR, Keldermans MM, Klemm LW, Semenza NJ, Shafer ML. Infectious complications among patients receiving home intravenous therapy with peripheral, central, or peripherally placed central venous catheters. Am J Med. 1991;91(3B):95S100S.
  14. Monreal M, Lafoz E, Ruiz J, Valls R, Alastrue A. Upper‐extremity deep venous thrombosis and pulmonary embolism: a prospective study. Chest. 1991;99(2):280283.
  15. Saber W, Moua T, Williams EC, et al. Risk factors for catheter‐related thrombosis (CRT) in cancer patients: a patient‐level data (IPD) meta‐analysis of clinical trials and prospective studies. J Thromb Haemost. 2011;9(2):312319.
  16. Chemaly RF, Parres JB, Rehm SJ, et al. Venous thrombosis associated with peripherally inserted central catheters: a retrospective analysis of the Cleveland Clinic experience. Clin Infect Dis. 2002;34(9):11791183.
  17. Ajenjo MC, Morley JC, Russo AJ, et al. Peripherally inserted central venous catheter–associated bloodstream infections in hospitalized adult patients. Infect Control Hosp Epidemiol. 2011;32(2):125130.
  18. Al‐Tawfiq JA, Abed MS, Memish ZA. Peripherally inserted central catheter bloodstream infection surveillance rates in an acute care setting in Saudi Arabia. Ann Saudi Med. 2012;32(2):169173.
  19. Woller SC, Stevens SM, Jones JP, et al. Derivation and validation of a simple model to identify venous thromboembolism risk in medical patients. Am J Med. 2011;124(10):947.e942–954.e942.
  20. Evans RS, Sharp JH, Linford LH, et al. Risk of symptomatic DVT associated with peripherally inserted central catheters. Chest. 2010;138(4):803810.
  21. Fletcher JJ, Stetler W, Wilson TJ. The clinical significance of peripherally inserted central venous catheter‐related deep vein thrombosis. Neurocrit Care. 2011;15(3):454460.
  22. Mollee P, Jones M, Stackelroth J, et al. Catheter‐associated bloodstream infection incidence and risk factors in adults with cancer: a prospective cohort study. J Hosp Infect. 2011;78(1):2630.
  23. Mitchell MD, Agarwal R, Hecht TE, Umscheid CA. Nonpharmacologic interventions for prevention of catheter‐related thrombosis: a systematic review [published online ahead of print September 13, 2012]. J Crit Care. doi: 10.1016/j.jcrc.2012.07.007.
  24. Wiebe ER, Kaczorowski J, MacKay J. Why are response rates in clinician surveys declining? Can Fam Physician. 2012;58(4):e225e228.
  25. Shekelle PG, Park RE, Kahan JP, Leape LL, Kamberg CJ, Bernstein SJ. Sensitivity and specificity of the RAND/UCLA Appropriateness Method to identify the overuse and underuse of coronary revascularization and hysterectomy. J Clin Epidemiol. 2001;54(10):10041010.
  26. Kahan JP, Park RE, Leape LL, et al. Variations by specialty in physician ratings of the appropriateness and necessity of indications for procedures. Med Care. 1996;34(6):512523.
References
  1. Zingg W, Sandoz L, Inan C, et al. Hospital‐wide survey of the use of central venous catheters. J Hosp Infect. 2011;77(4):304308.
  2. Chopra V, Anand S, Krein SL, Chenoweth C, Saint S. Bloodstream infection, venous thrombosis, and peripherally inserted central catheters: reappraising the evidence. Am J Med. 2012;125(8):733741.
  3. Chopra V, Flanders SA, Saint S. The problem with peripherally inserted central catheters. JAMA. 2012;308(15):15271528.
  4. Evans RS, Sharp JH, Linford LH, et al. Reduction of peripherally inserted central catheter associated deep venous thrombosis [published online ahead of print August 1, 2012]. Chest. doi: 10.1378/chest.12–0923.
  5. Pikwer A, Akeson J, Lindgren S. Complications associated with peripheral or central routes for central venous cannulation. Anaesthesia. 2012;67(1):6571.
  6. Pongruangporn M, Ajenjo MC, Russo AJ, et al. Patient‐ and device‐specific risk factors for peripherally inserted central venous catheter‐related bloodstream infections. Infect Control Hosp Epidemiol. 2013;34(2):184189.
  7. Akers AS, Chelluri L. Peripherally inserted central catheter use in the hospitalized patient: is there a role for the hospitalist? J Hosp Med. 2009;4(6):E1E4.
  8. Chakravarthy SB, Rettmann J, Markewitz BA, Elliott G, Sarfati M, Nohavec R. Peripherally inserted central catheter (PICC)‐associated upper‐extremity deep venous thrombosis (UEDVT) in critical‐care setting. Chest. 2005;128(4 suppl S):193S194S.
  9. Cowl CT, Weinstock JV, Al‐Jurf A, Ephgrave K, Murray JA, Dillon K. Complications and cost associated with parenteral nutrition delivered to hospitalized patients through either subclavian or peripherally inserted central catheters. Clin Nutr. 2000;19(4):237243.
  10. Safdar N, Maki DG. Risk of catheter‐related bloodstream infection with peripherally inserted central venous catheters used in hospitalized patients. Chest. 2005;128(2):489495.
  11. Bottino J, McCredie KB, Groschel DH, Lawson M. Long‐term intravenous therapy with peripherally inserted silicone elastomer central venous catheters in patients with malignant diseases. Cancer. 1979;43(5):19371943.
  12. Giuffrida DJ, Bryan‐Brown CW, Lumb PD, Kwun KB, Rhoades HM. Central vs peripheral venous catheters in critically ill patients. Chest. 1986;90(6):806809.
  13. Graham DR, Keldermans MM, Klemm LW, Semenza NJ, Shafer ML. Infectious complications among patients receiving home intravenous therapy with peripheral, central, or peripherally placed central venous catheters. Am J Med. 1991;91(3B):95S100S.
  14. Monreal M, Lafoz E, Ruiz J, Valls R, Alastrue A. Upper‐extremity deep venous thrombosis and pulmonary embolism: a prospective study. Chest. 1991;99(2):280283.
  15. Saber W, Moua T, Williams EC, et al. Risk factors for catheter‐related thrombosis (CRT) in cancer patients: a patient‐level data (IPD) meta‐analysis of clinical trials and prospective studies. J Thromb Haemost. 2011;9(2):312319.
  16. Chemaly RF, Parres JB, Rehm SJ, et al. Venous thrombosis associated with peripherally inserted central catheters: a retrospective analysis of the Cleveland Clinic experience. Clin Infect Dis. 2002;34(9):11791183.
  17. Ajenjo MC, Morley JC, Russo AJ, et al. Peripherally inserted central venous catheter–associated bloodstream infections in hospitalized adult patients. Infect Control Hosp Epidemiol. 2011;32(2):125130.
  18. Al‐Tawfiq JA, Abed MS, Memish ZA. Peripherally inserted central catheter bloodstream infection surveillance rates in an acute care setting in Saudi Arabia. Ann Saudi Med. 2012;32(2):169173.
  19. Woller SC, Stevens SM, Jones JP, et al. Derivation and validation of a simple model to identify venous thromboembolism risk in medical patients. Am J Med. 2011;124(10):947.e942–954.e942.
  20. Evans RS, Sharp JH, Linford LH, et al. Risk of symptomatic DVT associated with peripherally inserted central catheters. Chest. 2010;138(4):803810.
  21. Fletcher JJ, Stetler W, Wilson TJ. The clinical significance of peripherally inserted central venous catheter‐related deep vein thrombosis. Neurocrit Care. 2011;15(3):454460.
  22. Mollee P, Jones M, Stackelroth J, et al. Catheter‐associated bloodstream infection incidence and risk factors in adults with cancer: a prospective cohort study. J Hosp Infect. 2011;78(1):2630.
  23. Mitchell MD, Agarwal R, Hecht TE, Umscheid CA. Nonpharmacologic interventions for prevention of catheter‐related thrombosis: a systematic review [published online ahead of print September 13, 2012]. J Crit Care. doi: 10.1016/j.jcrc.2012.07.007.
  24. Wiebe ER, Kaczorowski J, MacKay J. Why are response rates in clinician surveys declining? Can Fam Physician. 2012;58(4):e225e228.
  25. Shekelle PG, Park RE, Kahan JP, Leape LL, Kamberg CJ, Bernstein SJ. Sensitivity and specificity of the RAND/UCLA Appropriateness Method to identify the overuse and underuse of coronary revascularization and hysterectomy. J Clin Epidemiol. 2001;54(10):10041010.
  26. Kahan JP, Park RE, Leape LL, et al. Variations by specialty in physician ratings of the appropriateness and necessity of indications for procedures. Med Care. 1996;34(6):512523.
Issue
Journal of Hospital Medicine - 8(6)
Issue
Journal of Hospital Medicine - 8(6)
Page Number
309-314
Page Number
309-314
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Hospitalist experiences, practice, opinions, and knowledge regarding peripherally inserted central catheters: A Michigan survey
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Hospitalist experiences, practice, opinions, and knowledge regarding peripherally inserted central catheters: A Michigan survey
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Copyright © 2013 Society of Hospital Medicine

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Address for correspondence and reprint requests: Vineet Chopra MD, MSc, Division of General Medicine, Department of Internal Medicine, North Campus Research Complex, University of Michigan Health System, 2800 Plymouth Road, Building 16, Room 432E, Ann Arbor, MI 48109; E‐mail: vineetc@umich.edu
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