Affiliations
Department of Medicine, Stanford University School of Medicine
Given name(s)
Stephanie
Family name
Harman
Degrees
MD

The SDM 3 Circle Model: A Literature Synthesis and Adaptation for Shared Decision Making in the Hospital

Article Type
Article
Changed
Fri, 12/14/2018 - 07:42
Author(s)
Stephanie Rennke, MD
Patrick Yuan, BA
Brad Monash, MD
Rebecca Blankenburg, MD, MPH
Ian Chua, MD
Stephanie Harman, MD
Debbie S. Sakai, MD
Adeena Khan, MD
Joan F. Hilton, DSc, MPH
Lisa Shieh, MD
Jason Satterfield, PhD

Evolving models of medical care emphasize the importance of shared decision-making (SDM) on practical and ethical grounds.1-3 SDM is a cognitive, emotional, and relational process in which provider and patient collaborate in a decision after discussing the options, evidence, and potential benefits and harms, while considering the patient’s values, preferences, and circumstances.4 Categories of decisions include information gathering, pharmacotherapy, therapeutic procedures, consultations and referrals, counseling and precautions (eg, behavior modification, goals of care, end-of-life care), and care transitions (eg, transfer or discharge to home).5 Decisions span the continuum of urgency and may be anticipatory or reactive.6 The patient’s environment7,8 and the provider-patient relationship9 have been explicitly incorporated into the ideal SDM process.

SDM has been conceptually and empirically linked with evidence-based practice,1 although the relationship between SDM and clinical outcomes is less clear.10,11 SDM is desired by patients12 and may bolster patient satisfaction, trust, and adherence.13,14 Limited evidence suggests SDM could reduce inappropriate treatments and testing,15 decrease adverse events,16 and promote greater patient safety,17-19 but more well-designed studies are needed.

Provider, patient, and contextual factors influence the extent to which SDM occurs. Providers commonly cite time constraints and perceived lack of applicability to certain clinical scenarios or settings.19 Providers may also lack training and competency in SDM skills.2 Patients may be reluctant to disagree with their provider or fear being mislabeled as “difficult.”20 When faced with high stakes or emotionally charged decisions, patients’ surrogates may prefer to have the provider serve as the sole decision-maker.21 Contextually, there may be limited evidence, high clinical stake, or a number of equally beneficial (or harmful) options.22,23

Current SDM models guide clinicians in determining when and how to engage in SDM, yet models vary widely. For example, Elwyn’s model emphasizes the ethical imperative for SDM and outlines 3 SDM steps: introduce choice, describe options, and help patients explore preferences and make decisions.3 Using a multimodal review and clinician-driven feedback, Legaré’s “IP-SDM” (Interprofessional Shared Decision Making) model illustrates the roles of the interprofessional team and emphasizes the influence of environmental factors on decision-making.24 Recent systematic reviews of SDM models have attempted to identify common elements, language, and processes.2,25,26

Although published SDM models demonstrate varying emphases–eg, evidence-based medicine,2 provider-patient relationships,9 interprofessional practices and environmental influences,24 or patient contextual factors 7,8–none specifically address hospitalization and the issues that impact decisions as a patients’ clinical condition and care needs change. Studies of SDM in hospitalized patients have relied on either general theoretical frameworks for patient engagement or conceptual models developed specifically for outpatient care.16,27,28 Although the key tenets of SDM are relevant across clinical settings, hospitalization introduces a number of unique and highly relevant factors that may influence all aspects of the SDM process. Table 1 provides several examples from the authors of how inpatient and outpatient SDM may differ.

This study reviews leading SDM models to construct a more environmentally and contextually sensitive model that is appropriate for the hospital setting. Although developed with hospital medicine in mind, a synthesized model that attends to environmental and systems context, provider/team factors, patient factors, and disease/medical variables is highly relevant in any setting where SDM occurs.

METHODS

We constructed a model that is appropriate for SDM across the care continuum through the following 3-part, iterative group process: (1) a comprehensive literature review of existing SDM models, (2) synthesis and inductive development of a new draft model, and (3) modification of the new model using feedback from SDM experts.

Narrative Literature Review

We performed a structured, comprehensive literature review 29 to compare and contrast existing SDM models and frameworks. Leading models and key concepts were first identified using 2 systematic reviews 25,26 and a comprehensive review.2 In order to extend the search to 2016 and include any overlooked articles, a PubMed search was performed using the terms “shared decision-making” or “medical decision-making” AND “model” or “theory” or “framework” for English-language articles from inception to 2016. The search was repeated using Google Scholar to verify results and obtain the number of citations per article as a proxy for impact and saturation. In order to minimize possible search error or selection bias, reference lists in high-impact publications were hand searched to identify additional articles. All abstracts were manually reviewed by 2 independent authors for relevance and later inclusion in our group iterative process. A priori inclusion criteria were limited to provider-patient SDM (ie, not clinical reasoning or making decisions in general) and complete descriptions of a conceptual model or framework. Additional publications suggested by experts (eg, perspective pieces or terminology summaries) were also reviewed.

 

 

Model Development and Expert Review

An electronic SDM reference library and annotated bibliography of the selected articles (Table 2) was created to guide the synthesis of SDM models and highlight needed revisions for hospital medicine. In a process similar to Legaré,24 a group of 8 pediatric and adult medicine hospitalists, a palliative care physician, a cognitive psychologist, a biostatistician, and 3 medical trainees reviewed the selected SDM publications and models30 and independently created their own adapted inpatient SDM models. Through an iterative, consensus-building group process, each model was discussed to select key elements or features to be integrated into a synthesized model. This model was guided by principles of social ecological theory, which emphasizes the role of the individual as influenced by and interactive with systems and the environment.31

The draft model and a standardized set of questions (supplementary Appendix A) were then emailed to all first and last authors of the reviewed studies (Table 2). Expert responses were compiled, coded, and analyzed independently by 3 coauthors. Inductive coding techniques and a constant comparative approach were used to code the qualitative data.32 Preliminary findings were shared among the 3 reviewers and discussed until consensus was reached on emerging themes and implications for the new SDM model and multistep SDM pathway. A master list of suggested revisions was shared with the larger authorship team and the model was refined accordingly.

RESULTS

Two previously published systematic reviews25,26 identified 494 articles, 161 conceptual definitions of SDM, and over 30 separate key concepts. The additional PubMed search garnered 1957 publications (with many overlapping from the systematic reviews). A manual search of the systematic reviews and PubMed abstracts identified 16 unique and complete decision-making models for further review. Hand searches of their citations yielded an additional 6 models for a total of 22 models.3,4,13,23,33-51 The majority of excluded articles described specific decision aids and small clinical studies, focused on only one step of the decision-making process, or were not otherwise relevant. The first (SR) and senior authors (JS) reviewed the 22 models for SDM relevance, generalizability, and content saturation, yielding a final sample of 9 SDM models. A subsequent Google Scholar search did not identify any new SDM models but 2 SDM theory papers1,52 and 2 commentaries53,54 were selected based on influence (ie, number of citations), expert recommendation, or coverage of a novel aspect of SDM. A total of 15 studies (9 SDM models + 6 reviews; Table 2) were used by our development team to create a synthesized SDM model. A 10th SDM model55 and 3 additional descriptive and normative studies8,56,57 were later added based on expert feedback and incorporated into our final SDM 3 Circle Model.

Expert Feedback

Twenty-one of 27 (78%) SDM expert authors responded to our e-mail request for feedback. The majority (62%) agreed with the basic elements of the model, including the environmental frame and the 3 domains. Some respondents viewed SDM as strictly a process between patient and provider independent of the disease, leading to refinement of the medical context category. Several experts emphasized the importance of SDM “set-up,” which includes the elicitation of patient preferences in how decisions are made and the extent of patient and/or surrogate involvement.

Several respondents identified time constraints (N = 2), acuity of disease (N = 3), and presence of multiple teams (N = 6) to be the significant factors distinguishing inpatient from outpatient SDM. For some experts, “team” referred to the interprofessional care team, whereas others referred to it as the collaboration among attending physicians and trainees. Experts noted that although the intensity and frequency of inpatient interactions could promote SDM, higher patient acuity and the urgency of decisions could negatively influence SDM and/or the patient’s ability to participate. Similarly, the presence of other team members may either impede or promote SDM by either contributing to miscommunication or bringing well-trained SDM experts to the bedside. Financial impact on patients and resource constraints were also noted as relevant. All of these elements have been incorporated into the final SDM 3 Circle Model and multistep SDM Pathway (Supplemental Appendix A and B).

The SDM 3 Circle Model

The SDM 3 Circle Model comprises 3 categories of SDM barriers and facilitators that intersect within the environmental frame of an inpatient ward or other setting: (1) provider/team, (2) patient/family, and (3) medical context. A Venn diagram visually represents the conceptual overlaps and distinctions among these categories that are all affected by the environment in which they occur (Supplemental Appendix A).

The patient/family circle mirrors prior SDM models that address the role of patient preferences in making decisions,3,4,12 with the explicit addition of the roles of families and surrogates as either decision-makers or influencers. This circle includes personal characteristics, such as cognitions (eg, beliefs, attitudes), emotions (eg, anxiety, hope), behaviors (eg, adherence, assertiveness), illness history (ie, subjective experience and understanding of one’s own medical history), and related social features (eg, culture, education, literacy, social supports).

Patient factors are not static over time or context. They occur within an environmental setting and are likely to be influenced by concurrent provider and medical variables (the second and third circles). Disease exacerbation leading to hospitalization or transfer to a subacute facility could dramatically shift the calculus a patient uses to determine preferences or activate dormant family dynamics. Strong provider-patient rapport (the overlap of patient and provider factors) may influence the development of trust and subsequent decisions.9 The type of disease or symptom presentation (circle 3–medical context) may further influence patient factors due to stigma, perceived vulnerability, or assumed prognosis.

The provider/team circle includes both individual and team-based factors falling into similar categories as the patient/family domain, such as cognitions, behavior, and social features; however, these factors include both personal (eg, the provider’s personal history, values, and beliefs) and professional (eg, past medical training, decision-making style, past experiences treating a disease) characteristics. Decisions may involve an interprofessional team representing a broad range of personalities and professional values. Decisions and decision-making processes may change over time as team composition changes, as level of provider expertise varies, or as environmental, patient, or disease/illness factors influence providers and teams.

Medical context includes factors related to the disease and the potential ways to evaluate or manage it. Examples of disease factors include acuity, symptoms, course, and prognosis. Most obviously, disease factors will influence the content of risk-benefit discussions but may also affect the SDM process through disease stigma or cultural assumptions about etiology. Disease evaluation factors include the psychometrics of a diagnostic screen, invasive and noninvasive testing, or a range of different preventive or therapeutic interventions. Treatment variables include the available options, costs, and risk of complications. Medical context variables evolve as evidence-based medicine and biomedical knowledge increase and new treatment options emerge.

Each of the 3 circles operates within the same environmental frame, such as an inpatient medicine ward, which itself operates within a hospital and the broader healthcare system. This frame exerts overt and subtle influences on providers, patients, and even the medical context. Features of the environmental frame include culture (eg, values, preferences, social norms), university versus community setting, incentives, formularies, quality improvement campaigns, regulations, and technology use.

The dynamic interactivity of the environmental frame and the 3 circles inform the process of SDM and highlight key differences that may occur between care settings. Certain features may predominate in different situations, but all will influence and be influenced by features of other circles during the course of SDM.

 

 

Application of the SDM 3 Circle Model

As shown in the Figure, the multistep SDM pathway begins with information gathering and processing, where the provider solicits medical history as well as patient preferences for decision-making. This “processing” of patient decision-making preferences is less commonly described. The next steps, sharing information and decision discussion, include patient education about the medical issue and available treatments. Discussions may involve the pros/cons of each option, alternative diagnostic or management strategies, and how these decisions fit with a patient’s preferences, abilities (eg, health literacy)58 and resources, or what has been called “contextualizing care.”7,8 Framing and other provider behaviors, including the use of decision aids and decision guides,15 may influence these conversations. Finally, after gathering, sharing, and discussing information (as influenced by the environment and 3 circles), a medical decision is made and patient understanding is verified. Detailed examples of how this model might be applied are illustrated with case scenarios in supplemental Appendix B.

Although the SDM process is similar across clinical settings, its operationalization varies in important ways for hospital decision-making. In some situations, patients may defer all decisions to their providers or decisions may be considered with multiple providers concurrently. In the hospital, SDM may not be possible, such as in emergency surgery for an obtunded patient or when the patient and surrogate are not available or able to participate in the decision. Therefore, providers may bypass the steps of information sharing and discussion of the decision (big arrow in the Figure and supplemental Appendix B), proceeding directly to decision making.

DISCUSSION

The SDM 3 Circle Model provides a concise, ecologically valid, contextually sensitive representation of SDM that synthesizes and extends beyond recent SDM models.3,7,40 Each circle represents the forces that influence SDM across settings. Although the multistep SDM pathway occurs similarly in outpatient and inpatient settings, how each step is operationalized and how each “circle” exerts its influence may differ and warrants further consideration throughout the SDM process. For example, hospitalized patients may have greater stress and anxiety, have more family involvement, be more motivated to adhere to treatment, and may be under greater financial and social pressures. Unlike outpatient primary care, patients are less likely to have an existing relationship with their inpatient providers, potentially compromising patient confidence in the provider, and necessitating expeditious trust building.

The SDM 3 Circle Model captures “setting” in both the broader environmental frame and within the provider/team category of variables. The frame also captures health system and broader community variables that may influence the practicality of some medical decisions. Within this essential frame, all 3 categories of patient, provider, and medical context are included as part of the SDM process. A better understanding of their interplay may be of great value for clinicians, researchers, administrators, and policy makers who wish to further study and promote SDM. Both the SDM 3 Circle Model and its accompanying pathway (Figures 1 and 2) highlight opportunities for intervention and research, and may drive quality improvement initiatives to improve clinical outcomes.

Limitations

We did not perform a new systematic review, potentially omitting lesser-known publications. We mitigated this risk by using recent systematic reviews, searching multiple databases, hand searching citation lists, and making inquiries to SDM experts. Our selection of models used as a foundation for the synthesized model was based on consensus, which included an element of subjective, clinical judgment. Our SDM expert sample was small and limited to authors of the papers we reviewed, potentially restricting the range of viewpoints received. Lastly, the SDM 3 Circle Model highlights key concept areas rather than all possible factors that influence SDM.

CONCLUSIONS

We present a peer-reviewed, literature-based SDM model capable of accounting for the unique circumstances and challenges of SDM in the hospital. The SDM 3 Circle Model identifies the primary categories of variables thought to influence SDM, places them in a shared environmental frame, and visually represents their interactive nature. A multistep representation of the SDM process further illustrates how the unique features and challenges of hospitalization might exert influence at various points as patients and providers reach a shared decision. As the interrelationships of patient and provider/team, medical context, and the environmental frame in which they occur are better understood, more effective and targeted interventions to promote SDM can be developed and evaluated.

Acknowledgments

The authors would like to thank Evans Whitaker for his assistance with the literature review and the Patient Engagement Project volunteers for their support and assistance with data collection.

Disclosure

Financial support for this study was provided entirely by a grant from NIH/NCCIH (grant #R25 AT006573, awarded to Dr. Jason Satterfield). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. The following authors are employed by the sponsor: Stephanie Rennke, MD, Patrick Yuan, BA, Brad Monash, MD, Rebecca Blankenburg, MD, MPH, Ian Chua, MD, Stephanie Harman, MD, Debbie S. Sakai, MD, Joan F. Hilton, DSc, MPH., and Jason Satterfield, PhD.

 

 

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Article PDF
jhm012121001.pdf
Issue
Journal of Hospital Medicine 12(12)
Publications
Journal of Hospital Medicine
Topics
Hospital Medicine
Page Number
1001-1008. Published online first October 18, 2017
Sections
Reviews
Author(s)
Stephanie Rennke, MD
Patrick Yuan, BA
Brad Monash, MD
Rebecca Blankenburg, MD, MPH
Ian Chua, MD
Stephanie Harman, MD
Debbie S. Sakai, MD
Adeena Khan, MD
Joan F. Hilton, DSc, MPH
Lisa Shieh, MD
Jason Satterfield, PhD
Author(s)
Stephanie Rennke, MD
Patrick Yuan, BA
Brad Monash, MD
Rebecca Blankenburg, MD, MPH
Ian Chua, MD
Stephanie Harman, MD
Debbie S. Sakai, MD
Adeena Khan, MD
Joan F. Hilton, DSc, MPH
Lisa Shieh, MD
Jason Satterfield, PhD
Article PDF
jhm012121001.pdf
Article PDF
jhm012121001.pdf

Evolving models of medical care emphasize the importance of shared decision-making (SDM) on practical and ethical grounds.1-3 SDM is a cognitive, emotional, and relational process in which provider and patient collaborate in a decision after discussing the options, evidence, and potential benefits and harms, while considering the patient’s values, preferences, and circumstances.4 Categories of decisions include information gathering, pharmacotherapy, therapeutic procedures, consultations and referrals, counseling and precautions (eg, behavior modification, goals of care, end-of-life care), and care transitions (eg, transfer or discharge to home).5 Decisions span the continuum of urgency and may be anticipatory or reactive.6 The patient’s environment7,8 and the provider-patient relationship9 have been explicitly incorporated into the ideal SDM process.

SDM has been conceptually and empirically linked with evidence-based practice,1 although the relationship between SDM and clinical outcomes is less clear.10,11 SDM is desired by patients12 and may bolster patient satisfaction, trust, and adherence.13,14 Limited evidence suggests SDM could reduce inappropriate treatments and testing,15 decrease adverse events,16 and promote greater patient safety,17-19 but more well-designed studies are needed.

Provider, patient, and contextual factors influence the extent to which SDM occurs. Providers commonly cite time constraints and perceived lack of applicability to certain clinical scenarios or settings.19 Providers may also lack training and competency in SDM skills.2 Patients may be reluctant to disagree with their provider or fear being mislabeled as “difficult.”20 When faced with high stakes or emotionally charged decisions, patients’ surrogates may prefer to have the provider serve as the sole decision-maker.21 Contextually, there may be limited evidence, high clinical stake, or a number of equally beneficial (or harmful) options.22,23

Current SDM models guide clinicians in determining when and how to engage in SDM, yet models vary widely. For example, Elwyn’s model emphasizes the ethical imperative for SDM and outlines 3 SDM steps: introduce choice, describe options, and help patients explore preferences and make decisions.3 Using a multimodal review and clinician-driven feedback, Legaré’s “IP-SDM” (Interprofessional Shared Decision Making) model illustrates the roles of the interprofessional team and emphasizes the influence of environmental factors on decision-making.24 Recent systematic reviews of SDM models have attempted to identify common elements, language, and processes.2,25,26

Although published SDM models demonstrate varying emphases–eg, evidence-based medicine,2 provider-patient relationships,9 interprofessional practices and environmental influences,24 or patient contextual factors 7,8–none specifically address hospitalization and the issues that impact decisions as a patients’ clinical condition and care needs change. Studies of SDM in hospitalized patients have relied on either general theoretical frameworks for patient engagement or conceptual models developed specifically for outpatient care.16,27,28 Although the key tenets of SDM are relevant across clinical settings, hospitalization introduces a number of unique and highly relevant factors that may influence all aspects of the SDM process. Table 1 provides several examples from the authors of how inpatient and outpatient SDM may differ.

This study reviews leading SDM models to construct a more environmentally and contextually sensitive model that is appropriate for the hospital setting. Although developed with hospital medicine in mind, a synthesized model that attends to environmental and systems context, provider/team factors, patient factors, and disease/medical variables is highly relevant in any setting where SDM occurs.

METHODS

We constructed a model that is appropriate for SDM across the care continuum through the following 3-part, iterative group process: (1) a comprehensive literature review of existing SDM models, (2) synthesis and inductive development of a new draft model, and (3) modification of the new model using feedback from SDM experts.

Narrative Literature Review

We performed a structured, comprehensive literature review 29 to compare and contrast existing SDM models and frameworks. Leading models and key concepts were first identified using 2 systematic reviews 25,26 and a comprehensive review.2 In order to extend the search to 2016 and include any overlooked articles, a PubMed search was performed using the terms “shared decision-making” or “medical decision-making” AND “model” or “theory” or “framework” for English-language articles from inception to 2016. The search was repeated using Google Scholar to verify results and obtain the number of citations per article as a proxy for impact and saturation. In order to minimize possible search error or selection bias, reference lists in high-impact publications were hand searched to identify additional articles. All abstracts were manually reviewed by 2 independent authors for relevance and later inclusion in our group iterative process. A priori inclusion criteria were limited to provider-patient SDM (ie, not clinical reasoning or making decisions in general) and complete descriptions of a conceptual model or framework. Additional publications suggested by experts (eg, perspective pieces or terminology summaries) were also reviewed.

 

 

Model Development and Expert Review

An electronic SDM reference library and annotated bibliography of the selected articles (Table 2) was created to guide the synthesis of SDM models and highlight needed revisions for hospital medicine. In a process similar to Legaré,24 a group of 8 pediatric and adult medicine hospitalists, a palliative care physician, a cognitive psychologist, a biostatistician, and 3 medical trainees reviewed the selected SDM publications and models30 and independently created their own adapted inpatient SDM models. Through an iterative, consensus-building group process, each model was discussed to select key elements or features to be integrated into a synthesized model. This model was guided by principles of social ecological theory, which emphasizes the role of the individual as influenced by and interactive with systems and the environment.31

The draft model and a standardized set of questions (supplementary Appendix A) were then emailed to all first and last authors of the reviewed studies (Table 2). Expert responses were compiled, coded, and analyzed independently by 3 coauthors. Inductive coding techniques and a constant comparative approach were used to code the qualitative data.32 Preliminary findings were shared among the 3 reviewers and discussed until consensus was reached on emerging themes and implications for the new SDM model and multistep SDM pathway. A master list of suggested revisions was shared with the larger authorship team and the model was refined accordingly.

RESULTS

Two previously published systematic reviews25,26 identified 494 articles, 161 conceptual definitions of SDM, and over 30 separate key concepts. The additional PubMed search garnered 1957 publications (with many overlapping from the systematic reviews). A manual search of the systematic reviews and PubMed abstracts identified 16 unique and complete decision-making models for further review. Hand searches of their citations yielded an additional 6 models for a total of 22 models.3,4,13,23,33-51 The majority of excluded articles described specific decision aids and small clinical studies, focused on only one step of the decision-making process, or were not otherwise relevant. The first (SR) and senior authors (JS) reviewed the 22 models for SDM relevance, generalizability, and content saturation, yielding a final sample of 9 SDM models. A subsequent Google Scholar search did not identify any new SDM models but 2 SDM theory papers1,52 and 2 commentaries53,54 were selected based on influence (ie, number of citations), expert recommendation, or coverage of a novel aspect of SDM. A total of 15 studies (9 SDM models + 6 reviews; Table 2) were used by our development team to create a synthesized SDM model. A 10th SDM model55 and 3 additional descriptive and normative studies8,56,57 were later added based on expert feedback and incorporated into our final SDM 3 Circle Model.

Expert Feedback

Twenty-one of 27 (78%) SDM expert authors responded to our e-mail request for feedback. The majority (62%) agreed with the basic elements of the model, including the environmental frame and the 3 domains. Some respondents viewed SDM as strictly a process between patient and provider independent of the disease, leading to refinement of the medical context category. Several experts emphasized the importance of SDM “set-up,” which includes the elicitation of patient preferences in how decisions are made and the extent of patient and/or surrogate involvement.

Several respondents identified time constraints (N = 2), acuity of disease (N = 3), and presence of multiple teams (N = 6) to be the significant factors distinguishing inpatient from outpatient SDM. For some experts, “team” referred to the interprofessional care team, whereas others referred to it as the collaboration among attending physicians and trainees. Experts noted that although the intensity and frequency of inpatient interactions could promote SDM, higher patient acuity and the urgency of decisions could negatively influence SDM and/or the patient’s ability to participate. Similarly, the presence of other team members may either impede or promote SDM by either contributing to miscommunication or bringing well-trained SDM experts to the bedside. Financial impact on patients and resource constraints were also noted as relevant. All of these elements have been incorporated into the final SDM 3 Circle Model and multistep SDM Pathway (Supplemental Appendix A and B).

The SDM 3 Circle Model

The SDM 3 Circle Model comprises 3 categories of SDM barriers and facilitators that intersect within the environmental frame of an inpatient ward or other setting: (1) provider/team, (2) patient/family, and (3) medical context. A Venn diagram visually represents the conceptual overlaps and distinctions among these categories that are all affected by the environment in which they occur (Supplemental Appendix A).

The patient/family circle mirrors prior SDM models that address the role of patient preferences in making decisions,3,4,12 with the explicit addition of the roles of families and surrogates as either decision-makers or influencers. This circle includes personal characteristics, such as cognitions (eg, beliefs, attitudes), emotions (eg, anxiety, hope), behaviors (eg, adherence, assertiveness), illness history (ie, subjective experience and understanding of one’s own medical history), and related social features (eg, culture, education, literacy, social supports).

Patient factors are not static over time or context. They occur within an environmental setting and are likely to be influenced by concurrent provider and medical variables (the second and third circles). Disease exacerbation leading to hospitalization or transfer to a subacute facility could dramatically shift the calculus a patient uses to determine preferences or activate dormant family dynamics. Strong provider-patient rapport (the overlap of patient and provider factors) may influence the development of trust and subsequent decisions.9 The type of disease or symptom presentation (circle 3–medical context) may further influence patient factors due to stigma, perceived vulnerability, or assumed prognosis.

The provider/team circle includes both individual and team-based factors falling into similar categories as the patient/family domain, such as cognitions, behavior, and social features; however, these factors include both personal (eg, the provider’s personal history, values, and beliefs) and professional (eg, past medical training, decision-making style, past experiences treating a disease) characteristics. Decisions may involve an interprofessional team representing a broad range of personalities and professional values. Decisions and decision-making processes may change over time as team composition changes, as level of provider expertise varies, or as environmental, patient, or disease/illness factors influence providers and teams.

Medical context includes factors related to the disease and the potential ways to evaluate or manage it. Examples of disease factors include acuity, symptoms, course, and prognosis. Most obviously, disease factors will influence the content of risk-benefit discussions but may also affect the SDM process through disease stigma or cultural assumptions about etiology. Disease evaluation factors include the psychometrics of a diagnostic screen, invasive and noninvasive testing, or a range of different preventive or therapeutic interventions. Treatment variables include the available options, costs, and risk of complications. Medical context variables evolve as evidence-based medicine and biomedical knowledge increase and new treatment options emerge.

Each of the 3 circles operates within the same environmental frame, such as an inpatient medicine ward, which itself operates within a hospital and the broader healthcare system. This frame exerts overt and subtle influences on providers, patients, and even the medical context. Features of the environmental frame include culture (eg, values, preferences, social norms), university versus community setting, incentives, formularies, quality improvement campaigns, regulations, and technology use.

The dynamic interactivity of the environmental frame and the 3 circles inform the process of SDM and highlight key differences that may occur between care settings. Certain features may predominate in different situations, but all will influence and be influenced by features of other circles during the course of SDM.

 

 

Application of the SDM 3 Circle Model

As shown in the Figure, the multistep SDM pathway begins with information gathering and processing, where the provider solicits medical history as well as patient preferences for decision-making. This “processing” of patient decision-making preferences is less commonly described. The next steps, sharing information and decision discussion, include patient education about the medical issue and available treatments. Discussions may involve the pros/cons of each option, alternative diagnostic or management strategies, and how these decisions fit with a patient’s preferences, abilities (eg, health literacy)58 and resources, or what has been called “contextualizing care.”7,8 Framing and other provider behaviors, including the use of decision aids and decision guides,15 may influence these conversations. Finally, after gathering, sharing, and discussing information (as influenced by the environment and 3 circles), a medical decision is made and patient understanding is verified. Detailed examples of how this model might be applied are illustrated with case scenarios in supplemental Appendix B.

Although the SDM process is similar across clinical settings, its operationalization varies in important ways for hospital decision-making. In some situations, patients may defer all decisions to their providers or decisions may be considered with multiple providers concurrently. In the hospital, SDM may not be possible, such as in emergency surgery for an obtunded patient or when the patient and surrogate are not available or able to participate in the decision. Therefore, providers may bypass the steps of information sharing and discussion of the decision (big arrow in the Figure and supplemental Appendix B), proceeding directly to decision making.

DISCUSSION

The SDM 3 Circle Model provides a concise, ecologically valid, contextually sensitive representation of SDM that synthesizes and extends beyond recent SDM models.3,7,40 Each circle represents the forces that influence SDM across settings. Although the multistep SDM pathway occurs similarly in outpatient and inpatient settings, how each step is operationalized and how each “circle” exerts its influence may differ and warrants further consideration throughout the SDM process. For example, hospitalized patients may have greater stress and anxiety, have more family involvement, be more motivated to adhere to treatment, and may be under greater financial and social pressures. Unlike outpatient primary care, patients are less likely to have an existing relationship with their inpatient providers, potentially compromising patient confidence in the provider, and necessitating expeditious trust building.

The SDM 3 Circle Model captures “setting” in both the broader environmental frame and within the provider/team category of variables. The frame also captures health system and broader community variables that may influence the practicality of some medical decisions. Within this essential frame, all 3 categories of patient, provider, and medical context are included as part of the SDM process. A better understanding of their interplay may be of great value for clinicians, researchers, administrators, and policy makers who wish to further study and promote SDM. Both the SDM 3 Circle Model and its accompanying pathway (Figures 1 and 2) highlight opportunities for intervention and research, and may drive quality improvement initiatives to improve clinical outcomes.

Limitations

We did not perform a new systematic review, potentially omitting lesser-known publications. We mitigated this risk by using recent systematic reviews, searching multiple databases, hand searching citation lists, and making inquiries to SDM experts. Our selection of models used as a foundation for the synthesized model was based on consensus, which included an element of subjective, clinical judgment. Our SDM expert sample was small and limited to authors of the papers we reviewed, potentially restricting the range of viewpoints received. Lastly, the SDM 3 Circle Model highlights key concept areas rather than all possible factors that influence SDM.

CONCLUSIONS

We present a peer-reviewed, literature-based SDM model capable of accounting for the unique circumstances and challenges of SDM in the hospital. The SDM 3 Circle Model identifies the primary categories of variables thought to influence SDM, places them in a shared environmental frame, and visually represents their interactive nature. A multistep representation of the SDM process further illustrates how the unique features and challenges of hospitalization might exert influence at various points as patients and providers reach a shared decision. As the interrelationships of patient and provider/team, medical context, and the environmental frame in which they occur are better understood, more effective and targeted interventions to promote SDM can be developed and evaluated.

Acknowledgments

The authors would like to thank Evans Whitaker for his assistance with the literature review and the Patient Engagement Project volunteers for their support and assistance with data collection.

Disclosure

Financial support for this study was provided entirely by a grant from NIH/NCCIH (grant #R25 AT006573, awarded to Dr. Jason Satterfield). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. The following authors are employed by the sponsor: Stephanie Rennke, MD, Patrick Yuan, BA, Brad Monash, MD, Rebecca Blankenburg, MD, MPH, Ian Chua, MD, Stephanie Harman, MD, Debbie S. Sakai, MD, Joan F. Hilton, DSc, MPH., and Jason Satterfield, PhD.

 

 

Evolving models of medical care emphasize the importance of shared decision-making (SDM) on practical and ethical grounds.1-3 SDM is a cognitive, emotional, and relational process in which provider and patient collaborate in a decision after discussing the options, evidence, and potential benefits and harms, while considering the patient’s values, preferences, and circumstances.4 Categories of decisions include information gathering, pharmacotherapy, therapeutic procedures, consultations and referrals, counseling and precautions (eg, behavior modification, goals of care, end-of-life care), and care transitions (eg, transfer or discharge to home).5 Decisions span the continuum of urgency and may be anticipatory or reactive.6 The patient’s environment7,8 and the provider-patient relationship9 have been explicitly incorporated into the ideal SDM process.

SDM has been conceptually and empirically linked with evidence-based practice,1 although the relationship between SDM and clinical outcomes is less clear.10,11 SDM is desired by patients12 and may bolster patient satisfaction, trust, and adherence.13,14 Limited evidence suggests SDM could reduce inappropriate treatments and testing,15 decrease adverse events,16 and promote greater patient safety,17-19 but more well-designed studies are needed.

Provider, patient, and contextual factors influence the extent to which SDM occurs. Providers commonly cite time constraints and perceived lack of applicability to certain clinical scenarios or settings.19 Providers may also lack training and competency in SDM skills.2 Patients may be reluctant to disagree with their provider or fear being mislabeled as “difficult.”20 When faced with high stakes or emotionally charged decisions, patients’ surrogates may prefer to have the provider serve as the sole decision-maker.21 Contextually, there may be limited evidence, high clinical stake, or a number of equally beneficial (or harmful) options.22,23

Current SDM models guide clinicians in determining when and how to engage in SDM, yet models vary widely. For example, Elwyn’s model emphasizes the ethical imperative for SDM and outlines 3 SDM steps: introduce choice, describe options, and help patients explore preferences and make decisions.3 Using a multimodal review and clinician-driven feedback, Legaré’s “IP-SDM” (Interprofessional Shared Decision Making) model illustrates the roles of the interprofessional team and emphasizes the influence of environmental factors on decision-making.24 Recent systematic reviews of SDM models have attempted to identify common elements, language, and processes.2,25,26

Although published SDM models demonstrate varying emphases–eg, evidence-based medicine,2 provider-patient relationships,9 interprofessional practices and environmental influences,24 or patient contextual factors 7,8–none specifically address hospitalization and the issues that impact decisions as a patients’ clinical condition and care needs change. Studies of SDM in hospitalized patients have relied on either general theoretical frameworks for patient engagement or conceptual models developed specifically for outpatient care.16,27,28 Although the key tenets of SDM are relevant across clinical settings, hospitalization introduces a number of unique and highly relevant factors that may influence all aspects of the SDM process. Table 1 provides several examples from the authors of how inpatient and outpatient SDM may differ.

This study reviews leading SDM models to construct a more environmentally and contextually sensitive model that is appropriate for the hospital setting. Although developed with hospital medicine in mind, a synthesized model that attends to environmental and systems context, provider/team factors, patient factors, and disease/medical variables is highly relevant in any setting where SDM occurs.

METHODS

We constructed a model that is appropriate for SDM across the care continuum through the following 3-part, iterative group process: (1) a comprehensive literature review of existing SDM models, (2) synthesis and inductive development of a new draft model, and (3) modification of the new model using feedback from SDM experts.

Narrative Literature Review

We performed a structured, comprehensive literature review 29 to compare and contrast existing SDM models and frameworks. Leading models and key concepts were first identified using 2 systematic reviews 25,26 and a comprehensive review.2 In order to extend the search to 2016 and include any overlooked articles, a PubMed search was performed using the terms “shared decision-making” or “medical decision-making” AND “model” or “theory” or “framework” for English-language articles from inception to 2016. The search was repeated using Google Scholar to verify results and obtain the number of citations per article as a proxy for impact and saturation. In order to minimize possible search error or selection bias, reference lists in high-impact publications were hand searched to identify additional articles. All abstracts were manually reviewed by 2 independent authors for relevance and later inclusion in our group iterative process. A priori inclusion criteria were limited to provider-patient SDM (ie, not clinical reasoning or making decisions in general) and complete descriptions of a conceptual model or framework. Additional publications suggested by experts (eg, perspective pieces or terminology summaries) were also reviewed.

 

 

Model Development and Expert Review

An electronic SDM reference library and annotated bibliography of the selected articles (Table 2) was created to guide the synthesis of SDM models and highlight needed revisions for hospital medicine. In a process similar to Legaré,24 a group of 8 pediatric and adult medicine hospitalists, a palliative care physician, a cognitive psychologist, a biostatistician, and 3 medical trainees reviewed the selected SDM publications and models30 and independently created their own adapted inpatient SDM models. Through an iterative, consensus-building group process, each model was discussed to select key elements or features to be integrated into a synthesized model. This model was guided by principles of social ecological theory, which emphasizes the role of the individual as influenced by and interactive with systems and the environment.31

The draft model and a standardized set of questions (supplementary Appendix A) were then emailed to all first and last authors of the reviewed studies (Table 2). Expert responses were compiled, coded, and analyzed independently by 3 coauthors. Inductive coding techniques and a constant comparative approach were used to code the qualitative data.32 Preliminary findings were shared among the 3 reviewers and discussed until consensus was reached on emerging themes and implications for the new SDM model and multistep SDM pathway. A master list of suggested revisions was shared with the larger authorship team and the model was refined accordingly.

RESULTS

Two previously published systematic reviews25,26 identified 494 articles, 161 conceptual definitions of SDM, and over 30 separate key concepts. The additional PubMed search garnered 1957 publications (with many overlapping from the systematic reviews). A manual search of the systematic reviews and PubMed abstracts identified 16 unique and complete decision-making models for further review. Hand searches of their citations yielded an additional 6 models for a total of 22 models.3,4,13,23,33-51 The majority of excluded articles described specific decision aids and small clinical studies, focused on only one step of the decision-making process, or were not otherwise relevant. The first (SR) and senior authors (JS) reviewed the 22 models for SDM relevance, generalizability, and content saturation, yielding a final sample of 9 SDM models. A subsequent Google Scholar search did not identify any new SDM models but 2 SDM theory papers1,52 and 2 commentaries53,54 were selected based on influence (ie, number of citations), expert recommendation, or coverage of a novel aspect of SDM. A total of 15 studies (9 SDM models + 6 reviews; Table 2) were used by our development team to create a synthesized SDM model. A 10th SDM model55 and 3 additional descriptive and normative studies8,56,57 were later added based on expert feedback and incorporated into our final SDM 3 Circle Model.

Expert Feedback

Twenty-one of 27 (78%) SDM expert authors responded to our e-mail request for feedback. The majority (62%) agreed with the basic elements of the model, including the environmental frame and the 3 domains. Some respondents viewed SDM as strictly a process between patient and provider independent of the disease, leading to refinement of the medical context category. Several experts emphasized the importance of SDM “set-up,” which includes the elicitation of patient preferences in how decisions are made and the extent of patient and/or surrogate involvement.

Several respondents identified time constraints (N = 2), acuity of disease (N = 3), and presence of multiple teams (N = 6) to be the significant factors distinguishing inpatient from outpatient SDM. For some experts, “team” referred to the interprofessional care team, whereas others referred to it as the collaboration among attending physicians and trainees. Experts noted that although the intensity and frequency of inpatient interactions could promote SDM, higher patient acuity and the urgency of decisions could negatively influence SDM and/or the patient’s ability to participate. Similarly, the presence of other team members may either impede or promote SDM by either contributing to miscommunication or bringing well-trained SDM experts to the bedside. Financial impact on patients and resource constraints were also noted as relevant. All of these elements have been incorporated into the final SDM 3 Circle Model and multistep SDM Pathway (Supplemental Appendix A and B).

The SDM 3 Circle Model

The SDM 3 Circle Model comprises 3 categories of SDM barriers and facilitators that intersect within the environmental frame of an inpatient ward or other setting: (1) provider/team, (2) patient/family, and (3) medical context. A Venn diagram visually represents the conceptual overlaps and distinctions among these categories that are all affected by the environment in which they occur (Supplemental Appendix A).

The patient/family circle mirrors prior SDM models that address the role of patient preferences in making decisions,3,4,12 with the explicit addition of the roles of families and surrogates as either decision-makers or influencers. This circle includes personal characteristics, such as cognitions (eg, beliefs, attitudes), emotions (eg, anxiety, hope), behaviors (eg, adherence, assertiveness), illness history (ie, subjective experience and understanding of one’s own medical history), and related social features (eg, culture, education, literacy, social supports).

Patient factors are not static over time or context. They occur within an environmental setting and are likely to be influenced by concurrent provider and medical variables (the second and third circles). Disease exacerbation leading to hospitalization or transfer to a subacute facility could dramatically shift the calculus a patient uses to determine preferences or activate dormant family dynamics. Strong provider-patient rapport (the overlap of patient and provider factors) may influence the development of trust and subsequent decisions.9 The type of disease or symptom presentation (circle 3–medical context) may further influence patient factors due to stigma, perceived vulnerability, or assumed prognosis.

The provider/team circle includes both individual and team-based factors falling into similar categories as the patient/family domain, such as cognitions, behavior, and social features; however, these factors include both personal (eg, the provider’s personal history, values, and beliefs) and professional (eg, past medical training, decision-making style, past experiences treating a disease) characteristics. Decisions may involve an interprofessional team representing a broad range of personalities and professional values. Decisions and decision-making processes may change over time as team composition changes, as level of provider expertise varies, or as environmental, patient, or disease/illness factors influence providers and teams.

Medical context includes factors related to the disease and the potential ways to evaluate or manage it. Examples of disease factors include acuity, symptoms, course, and prognosis. Most obviously, disease factors will influence the content of risk-benefit discussions but may also affect the SDM process through disease stigma or cultural assumptions about etiology. Disease evaluation factors include the psychometrics of a diagnostic screen, invasive and noninvasive testing, or a range of different preventive or therapeutic interventions. Treatment variables include the available options, costs, and risk of complications. Medical context variables evolve as evidence-based medicine and biomedical knowledge increase and new treatment options emerge.

Each of the 3 circles operates within the same environmental frame, such as an inpatient medicine ward, which itself operates within a hospital and the broader healthcare system. This frame exerts overt and subtle influences on providers, patients, and even the medical context. Features of the environmental frame include culture (eg, values, preferences, social norms), university versus community setting, incentives, formularies, quality improvement campaigns, regulations, and technology use.

The dynamic interactivity of the environmental frame and the 3 circles inform the process of SDM and highlight key differences that may occur between care settings. Certain features may predominate in different situations, but all will influence and be influenced by features of other circles during the course of SDM.

 

 

Application of the SDM 3 Circle Model

As shown in the Figure, the multistep SDM pathway begins with information gathering and processing, where the provider solicits medical history as well as patient preferences for decision-making. This “processing” of patient decision-making preferences is less commonly described. The next steps, sharing information and decision discussion, include patient education about the medical issue and available treatments. Discussions may involve the pros/cons of each option, alternative diagnostic or management strategies, and how these decisions fit with a patient’s preferences, abilities (eg, health literacy)58 and resources, or what has been called “contextualizing care.”7,8 Framing and other provider behaviors, including the use of decision aids and decision guides,15 may influence these conversations. Finally, after gathering, sharing, and discussing information (as influenced by the environment and 3 circles), a medical decision is made and patient understanding is verified. Detailed examples of how this model might be applied are illustrated with case scenarios in supplemental Appendix B.

Although the SDM process is similar across clinical settings, its operationalization varies in important ways for hospital decision-making. In some situations, patients may defer all decisions to their providers or decisions may be considered with multiple providers concurrently. In the hospital, SDM may not be possible, such as in emergency surgery for an obtunded patient or when the patient and surrogate are not available or able to participate in the decision. Therefore, providers may bypass the steps of information sharing and discussion of the decision (big arrow in the Figure and supplemental Appendix B), proceeding directly to decision making.

DISCUSSION

The SDM 3 Circle Model provides a concise, ecologically valid, contextually sensitive representation of SDM that synthesizes and extends beyond recent SDM models.3,7,40 Each circle represents the forces that influence SDM across settings. Although the multistep SDM pathway occurs similarly in outpatient and inpatient settings, how each step is operationalized and how each “circle” exerts its influence may differ and warrants further consideration throughout the SDM process. For example, hospitalized patients may have greater stress and anxiety, have more family involvement, be more motivated to adhere to treatment, and may be under greater financial and social pressures. Unlike outpatient primary care, patients are less likely to have an existing relationship with their inpatient providers, potentially compromising patient confidence in the provider, and necessitating expeditious trust building.

The SDM 3 Circle Model captures “setting” in both the broader environmental frame and within the provider/team category of variables. The frame also captures health system and broader community variables that may influence the practicality of some medical decisions. Within this essential frame, all 3 categories of patient, provider, and medical context are included as part of the SDM process. A better understanding of their interplay may be of great value for clinicians, researchers, administrators, and policy makers who wish to further study and promote SDM. Both the SDM 3 Circle Model and its accompanying pathway (Figures 1 and 2) highlight opportunities for intervention and research, and may drive quality improvement initiatives to improve clinical outcomes.

Limitations

We did not perform a new systematic review, potentially omitting lesser-known publications. We mitigated this risk by using recent systematic reviews, searching multiple databases, hand searching citation lists, and making inquiries to SDM experts. Our selection of models used as a foundation for the synthesized model was based on consensus, which included an element of subjective, clinical judgment. Our SDM expert sample was small and limited to authors of the papers we reviewed, potentially restricting the range of viewpoints received. Lastly, the SDM 3 Circle Model highlights key concept areas rather than all possible factors that influence SDM.

CONCLUSIONS

We present a peer-reviewed, literature-based SDM model capable of accounting for the unique circumstances and challenges of SDM in the hospital. The SDM 3 Circle Model identifies the primary categories of variables thought to influence SDM, places them in a shared environmental frame, and visually represents their interactive nature. A multistep representation of the SDM process further illustrates how the unique features and challenges of hospitalization might exert influence at various points as patients and providers reach a shared decision. As the interrelationships of patient and provider/team, medical context, and the environmental frame in which they occur are better understood, more effective and targeted interventions to promote SDM can be developed and evaluated.

Acknowledgments

The authors would like to thank Evans Whitaker for his assistance with the literature review and the Patient Engagement Project volunteers for their support and assistance with data collection.

Disclosure

Financial support for this study was provided entirely by a grant from NIH/NCCIH (grant #R25 AT006573, awarded to Dr. Jason Satterfield). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. The following authors are employed by the sponsor: Stephanie Rennke, MD, Patrick Yuan, BA, Brad Monash, MD, Rebecca Blankenburg, MD, MPH, Ian Chua, MD, Stephanie Harman, MD, Debbie S. Sakai, MD, Joan F. Hilton, DSc, MPH., and Jason Satterfield, PhD.

 

 

References

1. Hoffmann TC, Montori VM, Del Mar C. The connection between evidence-based medicine and shared decision making. JAMA. 2014;312(13):1295-1296. doi:10.1001/jama.2014.10186. PubMed
2. Stiggelbout AM, Pieterse AH, De Haes JC. Shared decision making: Concepts, evidence, and practice. Patient Educ Couns. 2015;98(10):1172-1179. doi:10.1016/j.pec.2015.06.022. PubMed
3. Elwyn G, Frosch D, Thomson R, et al. Shared decision making: a model for clinical practice. J Gen Intern Med. 2012;27(10):1361-1367. doi:10.1007/s11606-012-2077-6. PubMed
4. Charles C, Gafni A, Whelan T. Decision-making in the physician-patient encounter: revisiting the shared treatment decision-making model. Soc Sci Med. 1999;49(5):651-661. PubMed
5. Ofstad EH, Frich JC, Schei E, Frankel RM, Gulbrandsen P. What is a medical decision? A units. Am J Respir Crit Care Med. 2011;183(7):915-921. doi:10.1164/rccm.201008-1214OC. PubMed
22. Müller-Engelmann M, Keller H, Donner-Banzhoff N, Krones T. Shared decision making in medicine: The influence of situational treatment factors. Patient Educ Couns. 2011;82(2):240-246. doi:10.1016/j.pec.2010.04.028. PubMed
23. Whitney SN. A New Model of Medical Decisions: Exploring the Limits of Shared Decision Making. Med Decis Making. 2003;23(4):275-280. doi:10.1177/0272989X03256006. PubMed
24. Légaré F, Bekker H, Desroches S, et al. How can continuing professional development better promote shared decision-making? Perspectives from an international collaboration. Implement Sci. 2011;6:68. doi:10.1186/1748-5908-6-68. PubMed
25. Makoul G, Clayman ML. An integrative model of shared decision making in medical encounters. Patient Educ Couns. 2006;60(3):301-312. doi:10.1016/j.pec.2005.06.010. PubMed
26. Moumjid N, Gafni A, Brémond A, Carrère MO. Shared decision making in the medical taxonomy based on physician statements in hospital encounters: a qualitative study. BMJ Open. 2016;6(2):e010098. doi:10.1136/bmjopen-2015-010098. PubMed
6. Fowler FJ, Levin CA, Sepucha KR. Informing and involving patients to improve the quality of medical decisions. Health Aff (Millwood). 2011;30(4):699-706. doi:10.1377/hlthaff.2011.0003. PubMed
7. Weiner SJ, Kelly B, Ashley N, et al. Content coding for contextualization of care: evaluating physician performance at patient-centered decision making. Med Decis Making. 2014;34(1):97-106. doi:10.1177/0272989X13493146. PubMed
8. Weiner SJ, Schwartz A, Sharma G, et al. Patient-centered decision making and health care outcomes: an observational study. Ann Intern Med. 2013;158(8):573-579. doi:10.7326/0003-4819-158-8-201304160-00001. PubMed
9. Matthias MS, Salyers MP, Frankel RM. Re-thinking shared decision-making: context matters. Patient Educ Couns. 2013;91(2):176-179. doi:10.1016/j.pec.2013.01.006 PubMed
10. Clayman ML, Bylund CL, Chewning B, Makoul G. The Impact of Patient Participation in Health Decisions Within Medical Encounters: A Systematic Review. Med Decis Making. 2016;36(4):427-452. doi:10.1177/0272989X15613530. PubMed
11. Shay LA, Lafata JE. Understanding patient perceptions of shared decision making. Patient Educ Couns. 2014;96(3):295-301. doi:10.1016/j.pec.2014.07.017. PubMed
12. Chewning B, Bylund CL, Shah B, Arora NK, Gueguen JA, Makoul G. Patient preferences for shared decisions: a systematic review. Patient Educ Couns. 2012;86(1):9-18. doi:10.1016/j.pec.2011.02.004. PubMed
13. Butterworth JE, Campbell JL. Older patients and their GPs: shared decision making in enhancing trust. Br J Gen Pract. 2014;64(628):e709-e718. doi:10.3399/bjgp14X682297. PubMed
14. Joosten EA, DeFuentes-Merillas L, de Weert GH, Sensky T, van der Staak CP, de Jong CA. Systematic review of the effects of shared decision-making on patient satisfaction, treatment adherence and health status. Psychother Psychosom. 2008;77(4):219-226. doi:10.1159/000126073. PubMed
15. Stacey D, Légaré F, Col NF, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2014;1:CD001431. doi:10.1002/14651858.CD001431.pub4. PubMed
16. Weingart SN, Zhu J, Chiappetta L, et al. Hospitalized patients’ participation and its impact on quality of care and patient safety. Int J Qual Health Care. 2011;23(3):269-277. doi:10.1093/intqhc/mzr002. PubMed
17. Mohammed K, Nolan MB, Rajjo T, et al. Creating a Patient-Centered Health Care Delivery System: A Systematic Review of Health Care Quality From the Patient Perspective. Am J Med Qual. 2014;31(1):12-21. doi:10.1177/1062860614545124. PubMed
18. Berger Z, Flickinger TE, Pfoh E, Martinez KA, Dy SM. Promoting engagement by patients and families to reduce adverse events in acute care settings: a systematic review. BMJ Qual Saf. 2014;23(7):548-555. doi:10.1136/bmjqs-2012-001769. PubMed
19. Légaré F, Ratté S, Gravel K, Graham ID. Barriers and facilitators to implementing shared decision-making in clinical practice: update of a systematic review of health professionals’ perceptions. Patient Educ Couns. 2008;73(3):526-535. doi:10.1016/j.pec.2008.07.018. PubMed
20. Frosch DL, May SG, Rendle KAS, Tietbohl C, Elwyn G. Authoritarian physicians and patients’ fear of being labeled “difficult” among key obstacles to shared decision making. Health Aff (Millwood). 2012;31(5):1030-1038. doi:10.1377/hlthaff.2011.0576. PubMed
21. Johnson SK, Bautista CA, Hong SY, Weissfeld L, White DB. An empirical study of surrogates’ preferred level of control over value-laden life support decisions in intensive care encounter: are we all talking about the same thing? Med Decis Making. 2007;27(5):539-546. doi:10.1177/0272989X07306779. PubMed
27. Hallström I, Elander G. Decision-making during hospitalization: parents’ and children’s involvement. J Clin Nurs. 2004;13(3):367-375. PubMed
28. Ofstad EH, Frich JC, Schei E, Frankel RM, Gulbrandsen P. Temporal characteristics of decisions in hospital encounters: a threshold for shared decision making? A qualitative study. Patient Educ Couns. 2014;97(2):216-222. doi:10.1016/j.pec.2014.08.005. PubMed
29. Baumeister RF, Leary MR. Writing narrative literature reviews. Rev Gen Psychol. 1997;1(3):311. 
30. Moody DL. Theoretical and practical issues in evaluating the quality of conceptual models: current state and future directions. Data Knowl Eng. 2005;55(3):243-276. doi:10.1016/j.datak.2004.12.005. 
31. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective on health promotion programs. Health Educ Q. 1988;15(4):351-377. PubMed
32. Basics of Qualitative Research | SAGE Publications Inc. https://us.sagepub.com/en-us/nam/basics-of-qualitative-research/book235578. Accessed on September 13, 2016. PubMed

 

 

33. 2013;2(4):421-433. doi:10.2217/cer.13.46.J Comp Eff Res33. Halley MC, Rendle KA, Frosch DL. A conceptual model of the multiple stages of communication necessary to support patient-centered care. PubMed
34. 2012;87(1):54-61. doi:10.1016/j.pec.2011.07.027.Patient Educ Couns34. Torke AM, Petronio S, Sachs GA, Helft PR, Purnell C. A conceptual model of the role of communication in surrogate decision making for hospitalized adults. PubMed
35. 2009;15(6):1142-1151. doi:10.1111/j.1365-2753.2009.01315.x.J Eval Clin Pract35. Falzer PR, Garman MD. A conditional model of evidence-based decision making: Model of evidence-based decision making. PubMed
36. 2012;8(4):161-164. doi:10.1097/PTS.0b013e318267c56e.J Patient Saf36. Holzmueller CG, Wu AW, Pronovost PJ. A framework for encouraging patient engagement in medical decision making. PubMed
37. 2014;97(2):158-164. doi:10.1016/j.pec.2014.07.027.Patient Educ Couns37. Elwyn G, Lloyd A, May C, et al. Collaborative deliberation: a model for patient care. PubMed
38. 2002;35(5-6):313-321. doi:10.1016/S1532-0464(03)00037-6.J Biomed Inform38. Ruland CM, Bakken S. Developing, implementing, and evaluating decision support systems for shared decision making in patient care: a conceptual model and case illustration. PubMed
39. 1999;319(7212):764.BMJ39. Shepperd S, Charnock D, Gann B. Helping patients access high quality health information. PubMed
40. 2011;25(1):18-25. doi:10.3109/13561820.2010.490502.J Interprof Care40. Légaré F, Stacey D, Pouliot S, et al. Interprofessionalism and shared decision-making in primary care: a stepwise approach towards a new model. PubMed
41. 2015;25(1):141-152. doi:10.1007/s10926-014-9532-7.J Occup Rehabil41. Coutu MF, Légaré F, Durand MJ, et al. Operationalizing a Shared Decision Making Model for Work Rehabilitation Programs: A Consensus Process. PubMed
42. 2013;13:231.BMC Health Serv Res42. Hölzel LP, Kriston L, Härter M. Patient preference for involvement, experienced involvement, decisional conflict, and satisfaction with physician: a structural equation model test. PubMed
43. 2008;134(4):835-843. doi:10.1378/chest.08-0235.Chest43. Curtis JR, White DB. Practical guidance for evidence-based ICU family conferences. PubMed
44. 2013;8:29-36. doi:10.4137/IMI.S12783.Integr Med Insights44. Brooks AT, Silverman L, Wallen G. Shared Decision Making: A Fundamental Tenet in a Conceptual Framework of Integrative Healthcare Delivery. PubMed
45. 2013;33(1):37-47. doi:10.1177/0272989X12458159.Med Decis Making45. Müller-Engelmann M, Donner-Banzhoff N, Keller H, et al. When decisions should be shared: a study of social norms in medical decision making using a factorial survey approach. PubMed
46. 2007;101(4):205-211.Z Arztl Fortbild Qualitatssich46. Mccaffery KJ, Shepherd HL, Trevena L, et al. Shared decision-making in Australia. PubMed
47. 2014;20(2):311-318. doi:10.1007/s12028-013-9922-2.Neurocrit Care

47. Rubin MA. The Collaborative Autonomy Model of Medical Decision-Making. 48. 2013;70(1 Suppl):141S-158S. doi:10.1177/1077558712461952.Med Care Res Rev PubMed

48. McCullough LB. The professional medical ethics model of decision making under conditions of clinical uncertainty. PubMed
49. 2009;87(2):368–390.Milbank Q49. Satterfield JM, Spring B, Brownson RC, et al. Toward a Transdisciplinary Model of Evidence-Based Practice. PubMed
50. 2015;25(3):276-282. doi:10.1016/j.whi.2015.02.002.Womens Health Issues50. Moore JE, Titler MG, Kane Low L, Dalton VK, Sampselle CM. Transforming Patient-Centered Care: Development of the Evidence Informed Decision Making through Engagement Model. PubMed
51. 1997;44(5):681-692.Soc Sci Med51. Charles C, Gafni A, Whelan T. Shared decision-making in the medical encounter: what does it mean? (or it takes at least two to tango). PubMed
52. 2010;80(2):164-172. doi:10.1016/j.pec.2009.10.015.Patient Educ Couns52. Stacey D, Légaré F, Pouliot S, Kryworuchko J, Dunn S. Shared decision making models to inform an interprofessional perspective on decision making: a theory analysis. PubMed
53. 2013;70(1 Suppl):94S-112S. doi:10.1177/1077558712459216.Med Care Res Rev53. Epstein RM, Gramling RE. What is shared in shared decision making? Complex decisions when the evidence is unclear. PubMed
54. 2010;304(8):903-904. doi:10.1001/jama.2010.1208.JAMA54. Kon AA. The shared decision-making continuum. PubMed
55. 2008;30(3):429-444. doi:10.1111/j.1467-9566.2007.01064.x.Sociol Health Illn55. Rapley T. Distributed decision making: the anatomy of decisions-in-action. PubMed
56. 1997;12(6):339-345.J Gen Intern Med56. Braddock CH 3rd, Fihn SD, Levinson W, Jonsen AR, Pearlman RA. How doctors and patients discuss routine clinical decisions. Informed decision making in the outpatient setting. PubMed
57. 1999;282(24):2313-2320.JAMA57. Braddock CH 3rd, Edwards KA, Hasenberg NM, Laidley TL, Levinson W. Informed decision making in outpatient practice: time to get back to basics. PubMed
58. 2009;69(12):1805-1812. doi:10.1016/j.socscimed.2009.09.056.Soc Sci Med58. Smith SK, Dixon A, Trevena L, Nutbeam D, McCaffery KJ. Exploring patient involvement in healthcare decision making across different education and functional health literacy groups.
2006;9(4):321-332. doi:10.1111/j.1369-7625.2006.00404.x.Health Expect. PubMed

59. Towle A, Godolphin W, Grams G, Lamarre A. Putting informed and shared decision making into practice. PubMed
60. 2011;17(4):554-564. doi: 10.1111/j.1365-2753.2010.01515.x.J Eval Clin Pract60. Légaré F, Stacey D, Gagnon S, et al. Validating a conceptual model for an interprofessional approach to shared decision making: a mixed methods study. PubMed

 

 

References

1. Hoffmann TC, Montori VM, Del Mar C. The connection between evidence-based medicine and shared decision making. JAMA. 2014;312(13):1295-1296. doi:10.1001/jama.2014.10186. PubMed
2. Stiggelbout AM, Pieterse AH, De Haes JC. Shared decision making: Concepts, evidence, and practice. Patient Educ Couns. 2015;98(10):1172-1179. doi:10.1016/j.pec.2015.06.022. PubMed
3. Elwyn G, Frosch D, Thomson R, et al. Shared decision making: a model for clinical practice. J Gen Intern Med. 2012;27(10):1361-1367. doi:10.1007/s11606-012-2077-6. PubMed
4. Charles C, Gafni A, Whelan T. Decision-making in the physician-patient encounter: revisiting the shared treatment decision-making model. Soc Sci Med. 1999;49(5):651-661. PubMed
5. Ofstad EH, Frich JC, Schei E, Frankel RM, Gulbrandsen P. What is a medical decision? A units. Am J Respir Crit Care Med. 2011;183(7):915-921. doi:10.1164/rccm.201008-1214OC. PubMed
22. Müller-Engelmann M, Keller H, Donner-Banzhoff N, Krones T. Shared decision making in medicine: The influence of situational treatment factors. Patient Educ Couns. 2011;82(2):240-246. doi:10.1016/j.pec.2010.04.028. PubMed
23. Whitney SN. A New Model of Medical Decisions: Exploring the Limits of Shared Decision Making. Med Decis Making. 2003;23(4):275-280. doi:10.1177/0272989X03256006. PubMed
24. Légaré F, Bekker H, Desroches S, et al. How can continuing professional development better promote shared decision-making? Perspectives from an international collaboration. Implement Sci. 2011;6:68. doi:10.1186/1748-5908-6-68. PubMed
25. Makoul G, Clayman ML. An integrative model of shared decision making in medical encounters. Patient Educ Couns. 2006;60(3):301-312. doi:10.1016/j.pec.2005.06.010. PubMed
26. Moumjid N, Gafni A, Brémond A, Carrère MO. Shared decision making in the medical taxonomy based on physician statements in hospital encounters: a qualitative study. BMJ Open. 2016;6(2):e010098. doi:10.1136/bmjopen-2015-010098. PubMed
6. Fowler FJ, Levin CA, Sepucha KR. Informing and involving patients to improve the quality of medical decisions. Health Aff (Millwood). 2011;30(4):699-706. doi:10.1377/hlthaff.2011.0003. PubMed
7. Weiner SJ, Kelly B, Ashley N, et al. Content coding for contextualization of care: evaluating physician performance at patient-centered decision making. Med Decis Making. 2014;34(1):97-106. doi:10.1177/0272989X13493146. PubMed
8. Weiner SJ, Schwartz A, Sharma G, et al. Patient-centered decision making and health care outcomes: an observational study. Ann Intern Med. 2013;158(8):573-579. doi:10.7326/0003-4819-158-8-201304160-00001. PubMed
9. Matthias MS, Salyers MP, Frankel RM. Re-thinking shared decision-making: context matters. Patient Educ Couns. 2013;91(2):176-179. doi:10.1016/j.pec.2013.01.006 PubMed
10. Clayman ML, Bylund CL, Chewning B, Makoul G. The Impact of Patient Participation in Health Decisions Within Medical Encounters: A Systematic Review. Med Decis Making. 2016;36(4):427-452. doi:10.1177/0272989X15613530. PubMed
11. Shay LA, Lafata JE. Understanding patient perceptions of shared decision making. Patient Educ Couns. 2014;96(3):295-301. doi:10.1016/j.pec.2014.07.017. PubMed
12. Chewning B, Bylund CL, Shah B, Arora NK, Gueguen JA, Makoul G. Patient preferences for shared decisions: a systematic review. Patient Educ Couns. 2012;86(1):9-18. doi:10.1016/j.pec.2011.02.004. PubMed
13. Butterworth JE, Campbell JL. Older patients and their GPs: shared decision making in enhancing trust. Br J Gen Pract. 2014;64(628):e709-e718. doi:10.3399/bjgp14X682297. PubMed
14. Joosten EA, DeFuentes-Merillas L, de Weert GH, Sensky T, van der Staak CP, de Jong CA. Systematic review of the effects of shared decision-making on patient satisfaction, treatment adherence and health status. Psychother Psychosom. 2008;77(4):219-226. doi:10.1159/000126073. PubMed
15. Stacey D, Légaré F, Col NF, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2014;1:CD001431. doi:10.1002/14651858.CD001431.pub4. PubMed
16. Weingart SN, Zhu J, Chiappetta L, et al. Hospitalized patients’ participation and its impact on quality of care and patient safety. Int J Qual Health Care. 2011;23(3):269-277. doi:10.1093/intqhc/mzr002. PubMed
17. Mohammed K, Nolan MB, Rajjo T, et al. Creating a Patient-Centered Health Care Delivery System: A Systematic Review of Health Care Quality From the Patient Perspective. Am J Med Qual. 2014;31(1):12-21. doi:10.1177/1062860614545124. PubMed
18. Berger Z, Flickinger TE, Pfoh E, Martinez KA, Dy SM. Promoting engagement by patients and families to reduce adverse events in acute care settings: a systematic review. BMJ Qual Saf. 2014;23(7):548-555. doi:10.1136/bmjqs-2012-001769. PubMed
19. Légaré F, Ratté S, Gravel K, Graham ID. Barriers and facilitators to implementing shared decision-making in clinical practice: update of a systematic review of health professionals’ perceptions. Patient Educ Couns. 2008;73(3):526-535. doi:10.1016/j.pec.2008.07.018. PubMed
20. Frosch DL, May SG, Rendle KAS, Tietbohl C, Elwyn G. Authoritarian physicians and patients’ fear of being labeled “difficult” among key obstacles to shared decision making. Health Aff (Millwood). 2012;31(5):1030-1038. doi:10.1377/hlthaff.2011.0576. PubMed
21. Johnson SK, Bautista CA, Hong SY, Weissfeld L, White DB. An empirical study of surrogates’ preferred level of control over value-laden life support decisions in intensive care encounter: are we all talking about the same thing? Med Decis Making. 2007;27(5):539-546. doi:10.1177/0272989X07306779. PubMed
27. Hallström I, Elander G. Decision-making during hospitalization: parents’ and children’s involvement. J Clin Nurs. 2004;13(3):367-375. PubMed
28. Ofstad EH, Frich JC, Schei E, Frankel RM, Gulbrandsen P. Temporal characteristics of decisions in hospital encounters: a threshold for shared decision making? A qualitative study. Patient Educ Couns. 2014;97(2):216-222. doi:10.1016/j.pec.2014.08.005. PubMed
29. Baumeister RF, Leary MR. Writing narrative literature reviews. Rev Gen Psychol. 1997;1(3):311. 
30. Moody DL. Theoretical and practical issues in evaluating the quality of conceptual models: current state and future directions. Data Knowl Eng. 2005;55(3):243-276. doi:10.1016/j.datak.2004.12.005. 
31. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective on health promotion programs. Health Educ Q. 1988;15(4):351-377. PubMed
32. Basics of Qualitative Research | SAGE Publications Inc. https://us.sagepub.com/en-us/nam/basics-of-qualitative-research/book235578. Accessed on September 13, 2016. PubMed

 

 

33. 2013;2(4):421-433. doi:10.2217/cer.13.46.J Comp Eff Res33. Halley MC, Rendle KA, Frosch DL. A conceptual model of the multiple stages of communication necessary to support patient-centered care. PubMed
34. 2012;87(1):54-61. doi:10.1016/j.pec.2011.07.027.Patient Educ Couns34. Torke AM, Petronio S, Sachs GA, Helft PR, Purnell C. A conceptual model of the role of communication in surrogate decision making for hospitalized adults. PubMed
35. 2009;15(6):1142-1151. doi:10.1111/j.1365-2753.2009.01315.x.J Eval Clin Pract35. Falzer PR, Garman MD. A conditional model of evidence-based decision making: Model of evidence-based decision making. PubMed
36. 2012;8(4):161-164. doi:10.1097/PTS.0b013e318267c56e.J Patient Saf36. Holzmueller CG, Wu AW, Pronovost PJ. A framework for encouraging patient engagement in medical decision making. PubMed
37. 2014;97(2):158-164. doi:10.1016/j.pec.2014.07.027.Patient Educ Couns37. Elwyn G, Lloyd A, May C, et al. Collaborative deliberation: a model for patient care. PubMed
38. 2002;35(5-6):313-321. doi:10.1016/S1532-0464(03)00037-6.J Biomed Inform38. Ruland CM, Bakken S. Developing, implementing, and evaluating decision support systems for shared decision making in patient care: a conceptual model and case illustration. PubMed
39. 1999;319(7212):764.BMJ39. Shepperd S, Charnock D, Gann B. Helping patients access high quality health information. PubMed
40. 2011;25(1):18-25. doi:10.3109/13561820.2010.490502.J Interprof Care40. Légaré F, Stacey D, Pouliot S, et al. Interprofessionalism and shared decision-making in primary care: a stepwise approach towards a new model. PubMed
41. 2015;25(1):141-152. doi:10.1007/s10926-014-9532-7.J Occup Rehabil41. Coutu MF, Légaré F, Durand MJ, et al. Operationalizing a Shared Decision Making Model for Work Rehabilitation Programs: A Consensus Process. PubMed
42. 2013;13:231.BMC Health Serv Res42. Hölzel LP, Kriston L, Härter M. Patient preference for involvement, experienced involvement, decisional conflict, and satisfaction with physician: a structural equation model test. PubMed
43. 2008;134(4):835-843. doi:10.1378/chest.08-0235.Chest43. Curtis JR, White DB. Practical guidance for evidence-based ICU family conferences. PubMed
44. 2013;8:29-36. doi:10.4137/IMI.S12783.Integr Med Insights44. Brooks AT, Silverman L, Wallen G. Shared Decision Making: A Fundamental Tenet in a Conceptual Framework of Integrative Healthcare Delivery. PubMed
45. 2013;33(1):37-47. doi:10.1177/0272989X12458159.Med Decis Making45. Müller-Engelmann M, Donner-Banzhoff N, Keller H, et al. When decisions should be shared: a study of social norms in medical decision making using a factorial survey approach. PubMed
46. 2007;101(4):205-211.Z Arztl Fortbild Qualitatssich46. Mccaffery KJ, Shepherd HL, Trevena L, et al. Shared decision-making in Australia. PubMed
47. 2014;20(2):311-318. doi:10.1007/s12028-013-9922-2.Neurocrit Care

47. Rubin MA. The Collaborative Autonomy Model of Medical Decision-Making. 48. 2013;70(1 Suppl):141S-158S. doi:10.1177/1077558712461952.Med Care Res Rev PubMed

48. McCullough LB. The professional medical ethics model of decision making under conditions of clinical uncertainty. PubMed
49. 2009;87(2):368–390.Milbank Q49. Satterfield JM, Spring B, Brownson RC, et al. Toward a Transdisciplinary Model of Evidence-Based Practice. PubMed
50. 2015;25(3):276-282. doi:10.1016/j.whi.2015.02.002.Womens Health Issues50. Moore JE, Titler MG, Kane Low L, Dalton VK, Sampselle CM. Transforming Patient-Centered Care: Development of the Evidence Informed Decision Making through Engagement Model. PubMed
51. 1997;44(5):681-692.Soc Sci Med51. Charles C, Gafni A, Whelan T. Shared decision-making in the medical encounter: what does it mean? (or it takes at least two to tango). PubMed
52. 2010;80(2):164-172. doi:10.1016/j.pec.2009.10.015.Patient Educ Couns52. Stacey D, Légaré F, Pouliot S, Kryworuchko J, Dunn S. Shared decision making models to inform an interprofessional perspective on decision making: a theory analysis. PubMed
53. 2013;70(1 Suppl):94S-112S. doi:10.1177/1077558712459216.Med Care Res Rev53. Epstein RM, Gramling RE. What is shared in shared decision making? Complex decisions when the evidence is unclear. PubMed
54. 2010;304(8):903-904. doi:10.1001/jama.2010.1208.JAMA54. Kon AA. The shared decision-making continuum. PubMed
55. 2008;30(3):429-444. doi:10.1111/j.1467-9566.2007.01064.x.Sociol Health Illn55. Rapley T. Distributed decision making: the anatomy of decisions-in-action. PubMed
56. 1997;12(6):339-345.J Gen Intern Med56. Braddock CH 3rd, Fihn SD, Levinson W, Jonsen AR, Pearlman RA. How doctors and patients discuss routine clinical decisions. Informed decision making in the outpatient setting. PubMed
57. 1999;282(24):2313-2320.JAMA57. Braddock CH 3rd, Edwards KA, Hasenberg NM, Laidley TL, Levinson W. Informed decision making in outpatient practice: time to get back to basics. PubMed
58. 2009;69(12):1805-1812. doi:10.1016/j.socscimed.2009.09.056.Soc Sci Med58. Smith SK, Dixon A, Trevena L, Nutbeam D, McCaffery KJ. Exploring patient involvement in healthcare decision making across different education and functional health literacy groups.
2006;9(4):321-332. doi:10.1111/j.1369-7625.2006.00404.x.Health Expect. PubMed

59. Towle A, Godolphin W, Grams G, Lamarre A. Putting informed and shared decision making into practice. PubMed
60. 2011;17(4):554-564. doi: 10.1111/j.1365-2753.2010.01515.x.J Eval Clin Pract60. Légaré F, Stacey D, Gagnon S, et al. Validating a conceptual model for an interprofessional approach to shared decision making: a mixed methods study. PubMed

 

 

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Journal of Hospital Medicine 12(12)
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Journal of Hospital Medicine 12(12)
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1001-1008. Published online first October 18, 2017
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Jason Satterfield, PhD
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Jason Satterfield, PhD, Department of Medicine, University of California, San Francisco, 1701 Divisadero Street, Suite 500, San Francisco, CA, 94115; Telephone: 415-353-2104; Fax: 415-353-7901; E-mail: Jason.Satterfield@ucsf.edu
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Resident‐Created Hospitalist Curriculum

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Article
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Display Headline
A resident‐created hospitalist curriculum for internal medicine housestaff
Author(s)
Andre Kumar, MD
Andrea Smeraglio, MD
Ronald Witteles, MD
Stephanie Harman, MD
Shriram Nallamshetty, MD
Angela Rogers, MD
Robert Harrington, MD
Neera Ahuja, MD

Hospital medicine has grown tremendously since its inception in the 1990s.[1, 2] This expansion has led to the firm establishment of hospitalists in medical education, quality improvement (QI), research, subspecialty comanagement, and administration.[3, 4, 5]

This growth has also created new challenges. The training needs for the next generation of hospitalists are changing given the expanded clinical duties expected of hospitalists.[6, 7, 8] Prior surveys have suggested that some graduates employed as hospitalists have reported feeling underprepared in the areas of surgical comanagement, neurology, geriatrics, palliative care, and navigating the interdisciplinary care system.[9, 10]

In keeping with national trends, the number of residents interested in hospital medicine at our institution has dramatically increased. As internal medicine residents interested in careers in hospitalist medicine, we felt that improving hospitalist training at our institution was imperative given the increasing scope of practice and job competitiveness.[11, 12] We therefore sought to design and implement a hospitalist curriculum within our residency. In this article, we describe the genesis of our program, our final product, and the challenges of creating a curriculum while being internal medicine residents.

METHODS

Needs Assessment

To improve hospitalist training at our institution, we first performed a needs assessment. We contacted recent hospitalist graduates and current faculty to identify aspects of their clinical duties that may have been underemphasized during their training. Next, we performed a literature search in PubMed using the combined terms of hospitalist, hospital medicine, residency, education, training gaps, or curriculum. Based on these efforts, we developed a resident survey that assessed their attitudes toward various components of a potential curriculum. The survey was sent to all categorical internal medicine residents at our institution in December 2014. The survey specified that the respondents only include those who were interested in careers in hospital medicine. Responses were measured using a 5‐point Likert scale (1 = least important to 5 = most important).

Curriculum Development

Our intention was to develop a well‐rounded program that utilized mentorship, research, and clinical experience to augment our learner's knowledge and skills for a successful, long‐term career in the increasingly competitive field of hospital medicine. When designing our curriculum, we accounted for our program's current rotational requirements and local culture. Several previously identified underemphasized areas within hospital medicine, such as palliative care and neurology, were already required rotations at our program.[3, 4, 5] Therefore, any proposed curricular changes would need to mold into program requirements while still providing a preparatory experience in hospital medicine beyond what our current rotations offered. We felt this could be accomplished by including rotations that could provide specific skills pertinent to hospital medicine, such as ultrasound diagnostics or QI.

Key Differences in Curriculum Requirements Between Our Internal Medicine Residency Program and the Hospitalist Curriculum
Rotation Non‐SHAPE SHAPE

  • NOTE: Abbreviations: ICU, intensive care unit; SHAPE, Stanford Hospitalist Advanced Practice and Education.

ICU At least 12 weeks At least 16 weeks
Medical wards At least 16 weeks At least 16 weeks
Ultrasound diagnostics Elective Required
Quality improvement Elective Required
Surgical comanagement Elective Required
Medicine consult Elective Required
Neurology Required Required
Palliative care Required Required

Meeting With Stakeholders

We presented our curriculum proposal to the chief of the Stanford Hospital Medicine Program. We identified her early in the process to be our primary mentor, and she proved instrumental in being an advocate. After several meetings with the hospitalist group to further develop our program, we presented it to the residency program leadership who helped us to finalize our program.

RESULTS

Needs Assessment

Twenty‐two out of 111 categorical residents in our program (19.8%) identified themselves as interested in hospital medicine and responded to the survey. There were several areas of a potential hospitalist curriculum that the residents identified as important (defined as 4 or 5 on a 5‐point Likert scale). These areas included mentorship (90.9% of residents; mean 4.6, standard deviation [SD] 0.7), opportunities to teach (86.3%; mean 4.4, SD 0.9), and the establishment of a formal hospitalist curriculum (85.7%; mean 4.2, SD 0.8). The residents also identified several rotations that would be beneficial (defined as a 4 or 5 on a 5‐point Likert scale). These included medicine consult/procedures team (95.5% of residents; mean 4.7, SD 0.6), point‐of‐care ultrasound diagnostics (90.8%; mean 4.7, SD 0.8), and a community hospitalist preceptorship (86.4%; mean 4.4, SD 1.0). The residents also identified several rotations deemed to be of lesser benefit. These rotations included inpatient neurology (only 27.3% of residents; mean 3.2, SD 0.8) and palliative care (50.0%; mean 3.5, SD 1.0).

The Final Product: A Hospitalist Training Curriculum

Based on the needs assessment and meetings with program leadership, we designed a hospitalist program and named it the Stanford Hospitalist Advanced Practice and Education (SHAPE) program. The program was based on 3 core principles: (1) clinical excellence: by training in hospitalist‐relevant clinical areas, (2) academic development: with required research, QI, and teaching, and (3) career mentorship.

Clinical Excellence By Training in Hospitalist‐Relevant Clinical Areas

The SHAPE curriculum builds off of our institution's current curriculum with additional required rotations to improve the resident's skillsets. These included ultrasound diagnostics, surgical comanagement, and QI (Box 1). Given that some hospitalists work in an open intensive care unit (ICU), we increased the amount of required ICU time to provide expanded procedural and critical care experiences. The residents also receive 10 seminars focused on hospital medicine, including patient safety, QI, and career development (Box 1).

Box

The Stanford Hospitalist Advanced Practice and Education (SHAPE) program curriculum. Members of the program are required to complete the requirements listed before the end of their third year. Note that the clinical rotations are spread over the 3 years of residency.

Stanford Hospitalist Advanced Practice and Education Required Clinical Rotations

  • Medicine Consult (24 weeks)
  • Critical Care (16 weeks)
  • Ultrasound Diagnostics (2 weeks)
  • Quality Improvement (4 weeks)
  • Inpatient Neurology (2 weeks)
  • Palliative Care (2 weeks)
  • Surgical Comanagement (2 weeks)

Required Nonclinical Work

  • Quality improvement, clinical or educational project with a presentation at an academic conference or manuscript submission in a peer‐reviewed journal
  • Enrollment in the Stanford Faculty Development Center workshop on effective clinical teaching
  • Attendance at the hospitalist lecture series (10 lectures): patient safety, hospital efficiency, fundamentals of perioperative medicine, healthcare structure and changing reimbursement patterns, patient handoff, career development, prevention of burnout, inpatient nutrition, hospitalist research, and lean modeling in the hospital setting

Mentorship

  • Each participant is matched with 3 hospitalist mentors in order to provide comprehensive career and personal mentorship

Academic Development With Required Research and Teaching

SHAPE program residents are required to develop a QI, education, or clinical research project before graduation. They are required to present their work at a hospitalist conference or submit to a peer‐reviewed journal. They are also encouraged to attend the Society of Hospital Medicine annual meeting for their own career development.

SHAPE program residents also have increased opportunities to improve their teaching skills. The residents are enrolled in a clinical teaching workshop. Furthermore, the residents are responsible for leading regular lectures regarding common inpatient conditions for first‐ and second‐year medical students enrolled in a transitions‐of‐care elective.

Career Mentorship

Each resident is paired with 3 faculty hospitalists who have different areas of expertise (ie, clinical teaching, surgical comanagement, QI). They individually meet on a quarterly basis to discuss their career development and research projects. The SHAPE program will also host an annual resume‐development and career workshop.

SHAPE Resident Characteristics

In its first year, 13 of 25 residents (52%) interested in hospital medicine enrolled in the program. The SHAPE residents were predominantly second‐year residents (11 residents, 84.6%).

Among the 12 residents who did not enroll, there were 7 seniors (58.3%) who would soon be graduating and would not be eligible.

DISCUSSION

The training needs of aspiring hospitalists are changing as the scope of hospital medicine has expanded.[6] Residency programs can facilitate this by implementing a hospitalist curriculum that augments training and provides focused mentorship.[13, 14] An emphasis on resident leadership within these programs ensures positive housestaff buy‐in and satisfaction.

There were several key lessons we learned while designing our curriculum because of our unique role as residents and curriculum founders. This included the early engagement of departmental leadership as mentors. They assisted us in integrating our program within the existing internal medicine residency and the selection of electives. It was also imperative to secure adequate buy‐in from the academic hospitalists at our institution, as they would be our primary source of faculty mentors and lecturers.

A second challenge was balancing curriculum requirements and ensuring adequate buy‐in from our residents. The residents had fewer electives over their second and third years. However, this was balanced by the fact that the residents were given first preference on historically desirable rotations at our institution (including ultrasound, medicine consult, and QI). Furthermore, we purposefully included current resident opinions when performing our needs assessment to ensure adequate buy‐in. Surprisingly, the residents found several key rotations to be of low importance in our needs assessment, such as palliative care and inpatient neurology. Although this may seem confounding, several of these rotations (ie, neurology and palliative care) are already required of all residents at our program. It may be that some residents feel comfortable in these areas based on their previous experiences. Alternatively, this result may represent a lack of knowledge on the residents' part of what skill sets are imperative for career hospitalists. [4, 6]

Finally, we recognize that our program was based on our local needs assessment. Other residency programs may already have similar curricula built into their rotation schedule. In those instances, a hospitalist curriculum that emphasizes scholarly advancement and mentorship may be more appropriate.

CONCLUSIONS AND FUTURE DIRECTIONS

At out institution, we have created a hospitalist program designed to train the next generation of hospitalists with improved clinical, research, and teaching skills. Our cohort of residents will be observed over the next year, and we will administer a follow‐up study to assess the effectiveness of the program.

Acknowledgements

The authors acknowledge Karina Delgado, program manager at Stanford's internal medicine residency, for providing data on recent graduate plans.

Disclosures: Andre Kumar, MD, and Andrea Smeraglio, MD, are cofirst authors. The authors report no conflicts of interest.

Files
Supporting Information (1)
Supporting Information (2)
Supporting Information (3)
Supporting Information (4)
Supporting Information (5)
Supporting Information (6)
Supporting Information (7)
Supporting Information (8)
Supporting Information (9)
References
  1. Wachter RM. The hospitalist field turns 15: new opportunities and challenges. J Hosp Med. 2011;6(4):10–13.
  2. Glasheen JJ, Epstein KR, Siegal E, Kutner JS, Prochazka AV. The spectrum of community based hospitalist practice: A call to tailor internal medicine residency training. Arch Intern Med. 2007;167:727–729.
  3. Pham HH, Devers KJ, Kuo S, Berenson R. Health care market trends and the evolution of hospitalist use and roles. J Gen Intern Med. 2005;20(2):101–107.
  4. Lindenauer PK, Pantilat SZ, Katz PP, Wachter RM. Survey of the National Association of Inpatient Physicians. Ann Intern Med. 1999:343–349.
  5. Goldenberg J, Glasheen JJ. Hospitalist educators: future of inpatient internal medicine training. Mt Sinai J Med. 2008;75(5):430–435.
  6. Glasheen JJ, Siegal EM, Epstein K, Kutner J, Prochazka AV. Fulfilling the promise of hospital medicine: tailoring internal medicine training to address hospitalists' needs. J Gen Intern Med. 2008;23(7):1110–1115.
  7. Arora V, Guardiano S, Donaldson D, Storch I, Hemstreet P. Closing the gap between internal medicine training and practice: recommendations from recent graduates. Am J Med. 2005;118(6):680–685
  8. Chaudhry SI, Lien C, Ehrlich J, et al. Curricular content of internal medicine residency programs: a nationwide report. Am J Med. 2014;127(12):1247–1254.
  9. Plauth WH, Pantilat SZ, Wachter RM, Fenton CL. Hospitalists' perceptions of their residency training needs: results of a national survey. Am J Med. 2001;111(3):247–254.
  10. Holmboe ES, Bowen JL, Green M, et al. Reforming internal medicine residency training: a report from the Society of General Internal Medicine's Task Force for Residency Reform. J Gen Intern Med. 2005;20(12):1165–1172.
  11. Goodman PH, Januska A. Clinical hospital medicine fellowships: perspectives of employers, hospitalists, and medicine residents. J Hosp Med. 2008;3(1):28–34.
  12. Flanders SA, Centor B, Weber V, McGinn T, DeSalvo K, Auerbach A. Challenges and opportunities in academic hospital medicine: report from the Academic hospital medicine Summit. J Hosp Med. 2009;4(4):240–246.
  13. Glasheen JJ, Goldenberg J, Nelson JR. Achieving hospital medicine's promise through internal medicine residency redesign. Mt Sinai J Med. 2008;75(5):436–441.
  14. Hauer , Karen E, Flanders , Scott A, Wachter RM. Training Future Hospitalists. Cult Med. 1999;171(12):367–370.
Article PDF
jhm2590.pdf
Issue
Journal of Hospital Medicine - 11(9)
Publications
Journal of Hospital Medicine
Page Number
646-649
Sections
Brief Reports
Author(s)
Andre Kumar, MD
Andrea Smeraglio, MD
Ronald Witteles, MD
Stephanie Harman, MD
Shriram Nallamshetty, MD
Angela Rogers, MD
Robert Harrington, MD
Neera Ahuja, MD
Author(s)
Andre Kumar, MD
Andrea Smeraglio, MD
Ronald Witteles, MD
Stephanie Harman, MD
Shriram Nallamshetty, MD
Angela Rogers, MD
Robert Harrington, MD
Neera Ahuja, MD
Files
Supporting Information (1)
Supporting Information (2)
Supporting Information (3)
Supporting Information (4)
Supporting Information (5)
Supporting Information (6)
Supporting Information (7)
Supporting Information (8)
Supporting Information (9)
Files
Supporting Information (1)
Supporting Information (2)
Supporting Information (3)
Supporting Information (4)
Supporting Information (5)
Supporting Information (6)
Supporting Information (7)
Supporting Information (8)
Supporting Information (9)
Article PDF
jhm2590.pdf
Article PDF
jhm2590.pdf

Hospital medicine has grown tremendously since its inception in the 1990s.[1, 2] This expansion has led to the firm establishment of hospitalists in medical education, quality improvement (QI), research, subspecialty comanagement, and administration.[3, 4, 5]

This growth has also created new challenges. The training needs for the next generation of hospitalists are changing given the expanded clinical duties expected of hospitalists.[6, 7, 8] Prior surveys have suggested that some graduates employed as hospitalists have reported feeling underprepared in the areas of surgical comanagement, neurology, geriatrics, palliative care, and navigating the interdisciplinary care system.[9, 10]

In keeping with national trends, the number of residents interested in hospital medicine at our institution has dramatically increased. As internal medicine residents interested in careers in hospitalist medicine, we felt that improving hospitalist training at our institution was imperative given the increasing scope of practice and job competitiveness.[11, 12] We therefore sought to design and implement a hospitalist curriculum within our residency. In this article, we describe the genesis of our program, our final product, and the challenges of creating a curriculum while being internal medicine residents.

METHODS

Needs Assessment

To improve hospitalist training at our institution, we first performed a needs assessment. We contacted recent hospitalist graduates and current faculty to identify aspects of their clinical duties that may have been underemphasized during their training. Next, we performed a literature search in PubMed using the combined terms of hospitalist, hospital medicine, residency, education, training gaps, or curriculum. Based on these efforts, we developed a resident survey that assessed their attitudes toward various components of a potential curriculum. The survey was sent to all categorical internal medicine residents at our institution in December 2014. The survey specified that the respondents only include those who were interested in careers in hospital medicine. Responses were measured using a 5‐point Likert scale (1 = least important to 5 = most important).

Curriculum Development

Our intention was to develop a well‐rounded program that utilized mentorship, research, and clinical experience to augment our learner's knowledge and skills for a successful, long‐term career in the increasingly competitive field of hospital medicine. When designing our curriculum, we accounted for our program's current rotational requirements and local culture. Several previously identified underemphasized areas within hospital medicine, such as palliative care and neurology, were already required rotations at our program.[3, 4, 5] Therefore, any proposed curricular changes would need to mold into program requirements while still providing a preparatory experience in hospital medicine beyond what our current rotations offered. We felt this could be accomplished by including rotations that could provide specific skills pertinent to hospital medicine, such as ultrasound diagnostics or QI.

Key Differences in Curriculum Requirements Between Our Internal Medicine Residency Program and the Hospitalist Curriculum
Rotation Non‐SHAPE SHAPE

  • NOTE: Abbreviations: ICU, intensive care unit; SHAPE, Stanford Hospitalist Advanced Practice and Education.

ICU At least 12 weeks At least 16 weeks
Medical wards At least 16 weeks At least 16 weeks
Ultrasound diagnostics Elective Required
Quality improvement Elective Required
Surgical comanagement Elective Required
Medicine consult Elective Required
Neurology Required Required
Palliative care Required Required

Meeting With Stakeholders

We presented our curriculum proposal to the chief of the Stanford Hospital Medicine Program. We identified her early in the process to be our primary mentor, and she proved instrumental in being an advocate. After several meetings with the hospitalist group to further develop our program, we presented it to the residency program leadership who helped us to finalize our program.

RESULTS

Needs Assessment

Twenty‐two out of 111 categorical residents in our program (19.8%) identified themselves as interested in hospital medicine and responded to the survey. There were several areas of a potential hospitalist curriculum that the residents identified as important (defined as 4 or 5 on a 5‐point Likert scale). These areas included mentorship (90.9% of residents; mean 4.6, standard deviation [SD] 0.7), opportunities to teach (86.3%; mean 4.4, SD 0.9), and the establishment of a formal hospitalist curriculum (85.7%; mean 4.2, SD 0.8). The residents also identified several rotations that would be beneficial (defined as a 4 or 5 on a 5‐point Likert scale). These included medicine consult/procedures team (95.5% of residents; mean 4.7, SD 0.6), point‐of‐care ultrasound diagnostics (90.8%; mean 4.7, SD 0.8), and a community hospitalist preceptorship (86.4%; mean 4.4, SD 1.0). The residents also identified several rotations deemed to be of lesser benefit. These rotations included inpatient neurology (only 27.3% of residents; mean 3.2, SD 0.8) and palliative care (50.0%; mean 3.5, SD 1.0).

The Final Product: A Hospitalist Training Curriculum

Based on the needs assessment and meetings with program leadership, we designed a hospitalist program and named it the Stanford Hospitalist Advanced Practice and Education (SHAPE) program. The program was based on 3 core principles: (1) clinical excellence: by training in hospitalist‐relevant clinical areas, (2) academic development: with required research, QI, and teaching, and (3) career mentorship.

Clinical Excellence By Training in Hospitalist‐Relevant Clinical Areas

The SHAPE curriculum builds off of our institution's current curriculum with additional required rotations to improve the resident's skillsets. These included ultrasound diagnostics, surgical comanagement, and QI (Box 1). Given that some hospitalists work in an open intensive care unit (ICU), we increased the amount of required ICU time to provide expanded procedural and critical care experiences. The residents also receive 10 seminars focused on hospital medicine, including patient safety, QI, and career development (Box 1).

Box

The Stanford Hospitalist Advanced Practice and Education (SHAPE) program curriculum. Members of the program are required to complete the requirements listed before the end of their third year. Note that the clinical rotations are spread over the 3 years of residency.

Stanford Hospitalist Advanced Practice and Education Required Clinical Rotations

  • Medicine Consult (24 weeks)
  • Critical Care (16 weeks)
  • Ultrasound Diagnostics (2 weeks)
  • Quality Improvement (4 weeks)
  • Inpatient Neurology (2 weeks)
  • Palliative Care (2 weeks)
  • Surgical Comanagement (2 weeks)

Required Nonclinical Work

  • Quality improvement, clinical or educational project with a presentation at an academic conference or manuscript submission in a peer‐reviewed journal
  • Enrollment in the Stanford Faculty Development Center workshop on effective clinical teaching
  • Attendance at the hospitalist lecture series (10 lectures): patient safety, hospital efficiency, fundamentals of perioperative medicine, healthcare structure and changing reimbursement patterns, patient handoff, career development, prevention of burnout, inpatient nutrition, hospitalist research, and lean modeling in the hospital setting

Mentorship

  • Each participant is matched with 3 hospitalist mentors in order to provide comprehensive career and personal mentorship

Academic Development With Required Research and Teaching

SHAPE program residents are required to develop a QI, education, or clinical research project before graduation. They are required to present their work at a hospitalist conference or submit to a peer‐reviewed journal. They are also encouraged to attend the Society of Hospital Medicine annual meeting for their own career development.

SHAPE program residents also have increased opportunities to improve their teaching skills. The residents are enrolled in a clinical teaching workshop. Furthermore, the residents are responsible for leading regular lectures regarding common inpatient conditions for first‐ and second‐year medical students enrolled in a transitions‐of‐care elective.

Career Mentorship

Each resident is paired with 3 faculty hospitalists who have different areas of expertise (ie, clinical teaching, surgical comanagement, QI). They individually meet on a quarterly basis to discuss their career development and research projects. The SHAPE program will also host an annual resume‐development and career workshop.

SHAPE Resident Characteristics

In its first year, 13 of 25 residents (52%) interested in hospital medicine enrolled in the program. The SHAPE residents were predominantly second‐year residents (11 residents, 84.6%).

Among the 12 residents who did not enroll, there were 7 seniors (58.3%) who would soon be graduating and would not be eligible.

DISCUSSION

The training needs of aspiring hospitalists are changing as the scope of hospital medicine has expanded.[6] Residency programs can facilitate this by implementing a hospitalist curriculum that augments training and provides focused mentorship.[13, 14] An emphasis on resident leadership within these programs ensures positive housestaff buy‐in and satisfaction.

There were several key lessons we learned while designing our curriculum because of our unique role as residents and curriculum founders. This included the early engagement of departmental leadership as mentors. They assisted us in integrating our program within the existing internal medicine residency and the selection of electives. It was also imperative to secure adequate buy‐in from the academic hospitalists at our institution, as they would be our primary source of faculty mentors and lecturers.

A second challenge was balancing curriculum requirements and ensuring adequate buy‐in from our residents. The residents had fewer electives over their second and third years. However, this was balanced by the fact that the residents were given first preference on historically desirable rotations at our institution (including ultrasound, medicine consult, and QI). Furthermore, we purposefully included current resident opinions when performing our needs assessment to ensure adequate buy‐in. Surprisingly, the residents found several key rotations to be of low importance in our needs assessment, such as palliative care and inpatient neurology. Although this may seem confounding, several of these rotations (ie, neurology and palliative care) are already required of all residents at our program. It may be that some residents feel comfortable in these areas based on their previous experiences. Alternatively, this result may represent a lack of knowledge on the residents' part of what skill sets are imperative for career hospitalists. [4, 6]

Finally, we recognize that our program was based on our local needs assessment. Other residency programs may already have similar curricula built into their rotation schedule. In those instances, a hospitalist curriculum that emphasizes scholarly advancement and mentorship may be more appropriate.

CONCLUSIONS AND FUTURE DIRECTIONS

At out institution, we have created a hospitalist program designed to train the next generation of hospitalists with improved clinical, research, and teaching skills. Our cohort of residents will be observed over the next year, and we will administer a follow‐up study to assess the effectiveness of the program.

Acknowledgements

The authors acknowledge Karina Delgado, program manager at Stanford's internal medicine residency, for providing data on recent graduate plans.

Disclosures: Andre Kumar, MD, and Andrea Smeraglio, MD, are cofirst authors. The authors report no conflicts of interest.

Hospital medicine has grown tremendously since its inception in the 1990s.[1, 2] This expansion has led to the firm establishment of hospitalists in medical education, quality improvement (QI), research, subspecialty comanagement, and administration.[3, 4, 5]

This growth has also created new challenges. The training needs for the next generation of hospitalists are changing given the expanded clinical duties expected of hospitalists.[6, 7, 8] Prior surveys have suggested that some graduates employed as hospitalists have reported feeling underprepared in the areas of surgical comanagement, neurology, geriatrics, palliative care, and navigating the interdisciplinary care system.[9, 10]

In keeping with national trends, the number of residents interested in hospital medicine at our institution has dramatically increased. As internal medicine residents interested in careers in hospitalist medicine, we felt that improving hospitalist training at our institution was imperative given the increasing scope of practice and job competitiveness.[11, 12] We therefore sought to design and implement a hospitalist curriculum within our residency. In this article, we describe the genesis of our program, our final product, and the challenges of creating a curriculum while being internal medicine residents.

METHODS

Needs Assessment

To improve hospitalist training at our institution, we first performed a needs assessment. We contacted recent hospitalist graduates and current faculty to identify aspects of their clinical duties that may have been underemphasized during their training. Next, we performed a literature search in PubMed using the combined terms of hospitalist, hospital medicine, residency, education, training gaps, or curriculum. Based on these efforts, we developed a resident survey that assessed their attitudes toward various components of a potential curriculum. The survey was sent to all categorical internal medicine residents at our institution in December 2014. The survey specified that the respondents only include those who were interested in careers in hospital medicine. Responses were measured using a 5‐point Likert scale (1 = least important to 5 = most important).

Curriculum Development

Our intention was to develop a well‐rounded program that utilized mentorship, research, and clinical experience to augment our learner's knowledge and skills for a successful, long‐term career in the increasingly competitive field of hospital medicine. When designing our curriculum, we accounted for our program's current rotational requirements and local culture. Several previously identified underemphasized areas within hospital medicine, such as palliative care and neurology, were already required rotations at our program.[3, 4, 5] Therefore, any proposed curricular changes would need to mold into program requirements while still providing a preparatory experience in hospital medicine beyond what our current rotations offered. We felt this could be accomplished by including rotations that could provide specific skills pertinent to hospital medicine, such as ultrasound diagnostics or QI.

Key Differences in Curriculum Requirements Between Our Internal Medicine Residency Program and the Hospitalist Curriculum
Rotation Non‐SHAPE SHAPE

  • NOTE: Abbreviations: ICU, intensive care unit; SHAPE, Stanford Hospitalist Advanced Practice and Education.

ICU At least 12 weeks At least 16 weeks
Medical wards At least 16 weeks At least 16 weeks
Ultrasound diagnostics Elective Required
Quality improvement Elective Required
Surgical comanagement Elective Required
Medicine consult Elective Required
Neurology Required Required
Palliative care Required Required

Meeting With Stakeholders

We presented our curriculum proposal to the chief of the Stanford Hospital Medicine Program. We identified her early in the process to be our primary mentor, and she proved instrumental in being an advocate. After several meetings with the hospitalist group to further develop our program, we presented it to the residency program leadership who helped us to finalize our program.

RESULTS

Needs Assessment

Twenty‐two out of 111 categorical residents in our program (19.8%) identified themselves as interested in hospital medicine and responded to the survey. There were several areas of a potential hospitalist curriculum that the residents identified as important (defined as 4 or 5 on a 5‐point Likert scale). These areas included mentorship (90.9% of residents; mean 4.6, standard deviation [SD] 0.7), opportunities to teach (86.3%; mean 4.4, SD 0.9), and the establishment of a formal hospitalist curriculum (85.7%; mean 4.2, SD 0.8). The residents also identified several rotations that would be beneficial (defined as a 4 or 5 on a 5‐point Likert scale). These included medicine consult/procedures team (95.5% of residents; mean 4.7, SD 0.6), point‐of‐care ultrasound diagnostics (90.8%; mean 4.7, SD 0.8), and a community hospitalist preceptorship (86.4%; mean 4.4, SD 1.0). The residents also identified several rotations deemed to be of lesser benefit. These rotations included inpatient neurology (only 27.3% of residents; mean 3.2, SD 0.8) and palliative care (50.0%; mean 3.5, SD 1.0).

The Final Product: A Hospitalist Training Curriculum

Based on the needs assessment and meetings with program leadership, we designed a hospitalist program and named it the Stanford Hospitalist Advanced Practice and Education (SHAPE) program. The program was based on 3 core principles: (1) clinical excellence: by training in hospitalist‐relevant clinical areas, (2) academic development: with required research, QI, and teaching, and (3) career mentorship.

Clinical Excellence By Training in Hospitalist‐Relevant Clinical Areas

The SHAPE curriculum builds off of our institution's current curriculum with additional required rotations to improve the resident's skillsets. These included ultrasound diagnostics, surgical comanagement, and QI (Box 1). Given that some hospitalists work in an open intensive care unit (ICU), we increased the amount of required ICU time to provide expanded procedural and critical care experiences. The residents also receive 10 seminars focused on hospital medicine, including patient safety, QI, and career development (Box 1).

Box

The Stanford Hospitalist Advanced Practice and Education (SHAPE) program curriculum. Members of the program are required to complete the requirements listed before the end of their third year. Note that the clinical rotations are spread over the 3 years of residency.

Stanford Hospitalist Advanced Practice and Education Required Clinical Rotations

  • Medicine Consult (24 weeks)
  • Critical Care (16 weeks)
  • Ultrasound Diagnostics (2 weeks)
  • Quality Improvement (4 weeks)
  • Inpatient Neurology (2 weeks)
  • Palliative Care (2 weeks)
  • Surgical Comanagement (2 weeks)

Required Nonclinical Work

  • Quality improvement, clinical or educational project with a presentation at an academic conference or manuscript submission in a peer‐reviewed journal
  • Enrollment in the Stanford Faculty Development Center workshop on effective clinical teaching
  • Attendance at the hospitalist lecture series (10 lectures): patient safety, hospital efficiency, fundamentals of perioperative medicine, healthcare structure and changing reimbursement patterns, patient handoff, career development, prevention of burnout, inpatient nutrition, hospitalist research, and lean modeling in the hospital setting

Mentorship

  • Each participant is matched with 3 hospitalist mentors in order to provide comprehensive career and personal mentorship

Academic Development With Required Research and Teaching

SHAPE program residents are required to develop a QI, education, or clinical research project before graduation. They are required to present their work at a hospitalist conference or submit to a peer‐reviewed journal. They are also encouraged to attend the Society of Hospital Medicine annual meeting for their own career development.

SHAPE program residents also have increased opportunities to improve their teaching skills. The residents are enrolled in a clinical teaching workshop. Furthermore, the residents are responsible for leading regular lectures regarding common inpatient conditions for first‐ and second‐year medical students enrolled in a transitions‐of‐care elective.

Career Mentorship

Each resident is paired with 3 faculty hospitalists who have different areas of expertise (ie, clinical teaching, surgical comanagement, QI). They individually meet on a quarterly basis to discuss their career development and research projects. The SHAPE program will also host an annual resume‐development and career workshop.

SHAPE Resident Characteristics

In its first year, 13 of 25 residents (52%) interested in hospital medicine enrolled in the program. The SHAPE residents were predominantly second‐year residents (11 residents, 84.6%).

Among the 12 residents who did not enroll, there were 7 seniors (58.3%) who would soon be graduating and would not be eligible.

DISCUSSION

The training needs of aspiring hospitalists are changing as the scope of hospital medicine has expanded.[6] Residency programs can facilitate this by implementing a hospitalist curriculum that augments training and provides focused mentorship.[13, 14] An emphasis on resident leadership within these programs ensures positive housestaff buy‐in and satisfaction.

There were several key lessons we learned while designing our curriculum because of our unique role as residents and curriculum founders. This included the early engagement of departmental leadership as mentors. They assisted us in integrating our program within the existing internal medicine residency and the selection of electives. It was also imperative to secure adequate buy‐in from the academic hospitalists at our institution, as they would be our primary source of faculty mentors and lecturers.

A second challenge was balancing curriculum requirements and ensuring adequate buy‐in from our residents. The residents had fewer electives over their second and third years. However, this was balanced by the fact that the residents were given first preference on historically desirable rotations at our institution (including ultrasound, medicine consult, and QI). Furthermore, we purposefully included current resident opinions when performing our needs assessment to ensure adequate buy‐in. Surprisingly, the residents found several key rotations to be of low importance in our needs assessment, such as palliative care and inpatient neurology. Although this may seem confounding, several of these rotations (ie, neurology and palliative care) are already required of all residents at our program. It may be that some residents feel comfortable in these areas based on their previous experiences. Alternatively, this result may represent a lack of knowledge on the residents' part of what skill sets are imperative for career hospitalists. [4, 6]

Finally, we recognize that our program was based on our local needs assessment. Other residency programs may already have similar curricula built into their rotation schedule. In those instances, a hospitalist curriculum that emphasizes scholarly advancement and mentorship may be more appropriate.

CONCLUSIONS AND FUTURE DIRECTIONS

At out institution, we have created a hospitalist program designed to train the next generation of hospitalists with improved clinical, research, and teaching skills. Our cohort of residents will be observed over the next year, and we will administer a follow‐up study to assess the effectiveness of the program.

Acknowledgements

The authors acknowledge Karina Delgado, program manager at Stanford's internal medicine residency, for providing data on recent graduate plans.

Disclosures: Andre Kumar, MD, and Andrea Smeraglio, MD, are cofirst authors. The authors report no conflicts of interest.

References
  1. Wachter RM. The hospitalist field turns 15: new opportunities and challenges. J Hosp Med. 2011;6(4):10–13.
  2. Glasheen JJ, Epstein KR, Siegal E, Kutner JS, Prochazka AV. The spectrum of community based hospitalist practice: A call to tailor internal medicine residency training. Arch Intern Med. 2007;167:727–729.
  3. Pham HH, Devers KJ, Kuo S, Berenson R. Health care market trends and the evolution of hospitalist use and roles. J Gen Intern Med. 2005;20(2):101–107.
  4. Lindenauer PK, Pantilat SZ, Katz PP, Wachter RM. Survey of the National Association of Inpatient Physicians. Ann Intern Med. 1999:343–349.
  5. Goldenberg J, Glasheen JJ. Hospitalist educators: future of inpatient internal medicine training. Mt Sinai J Med. 2008;75(5):430–435.
  6. Glasheen JJ, Siegal EM, Epstein K, Kutner J, Prochazka AV. Fulfilling the promise of hospital medicine: tailoring internal medicine training to address hospitalists' needs. J Gen Intern Med. 2008;23(7):1110–1115.
  7. Arora V, Guardiano S, Donaldson D, Storch I, Hemstreet P. Closing the gap between internal medicine training and practice: recommendations from recent graduates. Am J Med. 2005;118(6):680–685
  8. Chaudhry SI, Lien C, Ehrlich J, et al. Curricular content of internal medicine residency programs: a nationwide report. Am J Med. 2014;127(12):1247–1254.
  9. Plauth WH, Pantilat SZ, Wachter RM, Fenton CL. Hospitalists' perceptions of their residency training needs: results of a national survey. Am J Med. 2001;111(3):247–254.
  10. Holmboe ES, Bowen JL, Green M, et al. Reforming internal medicine residency training: a report from the Society of General Internal Medicine's Task Force for Residency Reform. J Gen Intern Med. 2005;20(12):1165–1172.
  11. Goodman PH, Januska A. Clinical hospital medicine fellowships: perspectives of employers, hospitalists, and medicine residents. J Hosp Med. 2008;3(1):28–34.
  12. Flanders SA, Centor B, Weber V, McGinn T, DeSalvo K, Auerbach A. Challenges and opportunities in academic hospital medicine: report from the Academic hospital medicine Summit. J Hosp Med. 2009;4(4):240–246.
  13. Glasheen JJ, Goldenberg J, Nelson JR. Achieving hospital medicine's promise through internal medicine residency redesign. Mt Sinai J Med. 2008;75(5):436–441.
  14. Hauer , Karen E, Flanders , Scott A, Wachter RM. Training Future Hospitalists. Cult Med. 1999;171(12):367–370.
References
  1. Wachter RM. The hospitalist field turns 15: new opportunities and challenges. J Hosp Med. 2011;6(4):10–13.
  2. Glasheen JJ, Epstein KR, Siegal E, Kutner JS, Prochazka AV. The spectrum of community based hospitalist practice: A call to tailor internal medicine residency training. Arch Intern Med. 2007;167:727–729.
  3. Pham HH, Devers KJ, Kuo S, Berenson R. Health care market trends and the evolution of hospitalist use and roles. J Gen Intern Med. 2005;20(2):101–107.
  4. Lindenauer PK, Pantilat SZ, Katz PP, Wachter RM. Survey of the National Association of Inpatient Physicians. Ann Intern Med. 1999:343–349.
  5. Goldenberg J, Glasheen JJ. Hospitalist educators: future of inpatient internal medicine training. Mt Sinai J Med. 2008;75(5):430–435.
  6. Glasheen JJ, Siegal EM, Epstein K, Kutner J, Prochazka AV. Fulfilling the promise of hospital medicine: tailoring internal medicine training to address hospitalists' needs. J Gen Intern Med. 2008;23(7):1110–1115.
  7. Arora V, Guardiano S, Donaldson D, Storch I, Hemstreet P. Closing the gap between internal medicine training and practice: recommendations from recent graduates. Am J Med. 2005;118(6):680–685
  8. Chaudhry SI, Lien C, Ehrlich J, et al. Curricular content of internal medicine residency programs: a nationwide report. Am J Med. 2014;127(12):1247–1254.
  9. Plauth WH, Pantilat SZ, Wachter RM, Fenton CL. Hospitalists' perceptions of their residency training needs: results of a national survey. Am J Med. 2001;111(3):247–254.
  10. Holmboe ES, Bowen JL, Green M, et al. Reforming internal medicine residency training: a report from the Society of General Internal Medicine's Task Force for Residency Reform. J Gen Intern Med. 2005;20(12):1165–1172.
  11. Goodman PH, Januska A. Clinical hospital medicine fellowships: perspectives of employers, hospitalists, and medicine residents. J Hosp Med. 2008;3(1):28–34.
  12. Flanders SA, Centor B, Weber V, McGinn T, DeSalvo K, Auerbach A. Challenges and opportunities in academic hospital medicine: report from the Academic hospital medicine Summit. J Hosp Med. 2009;4(4):240–246.
  13. Glasheen JJ, Goldenberg J, Nelson JR. Achieving hospital medicine's promise through internal medicine residency redesign. Mt Sinai J Med. 2008;75(5):436–441.
  14. Hauer , Karen E, Flanders , Scott A, Wachter RM. Training Future Hospitalists. Cult Med. 1999;171(12):367–370.
Issue
Journal of Hospital Medicine - 11(9)
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Journal of Hospital Medicine - 11(9)
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A resident‐created hospitalist curriculum for internal medicine housestaff
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A resident‐created hospitalist curriculum for internal medicine housestaff
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Andre Kumar, MD
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Address for correspondence and reprint requests: Andre Kumar, MD, Department of Medicine, Stanford University Hospital, 300 Pasteur Drive, Lane 154, Stanford, CA 94305‐5133; Telephone: 650‐723‐6661; Fax: 650‐498‐6205; E‐mail: akumar3@stanford.edu
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