Dissemination and Implementation of Shared Decision Making Into Clinical Practice: A Research Agenda

Abstract

Shared decision making (SDM) is essential to advancing patient-centered care in emergency medicine. Despite many documented benefits of SDM, prior research has demonstrated persistently low levels of patient engagement by clinicians across many disciplines, including emergency medicine. An effective dissemination and implementation (D&I) framework could be used to alter the process of delivering care and to facilitate SDM in routine clinical emergency medicine practice. Here we outline a research and policy agenda to support the D&I strategy needed to integrate SDM into emergency care.

Despite the evidence to support the implementation of shared decision making (SDM), there continues to be low levels of patient-involving behaviors by providers across clinical disciplines, including emergency medicine.^1,2 Despite favorable perceptions of SDM^3,4 and the existence of decision aid tools for common emergency department (ED) complaints like low-risk chest pain,⁵ many barriers exist to the successful integration of SDM into clinical practice in the ED,^6–9 including:

1. The beliefs that a) “many patients prefer that the physician decides,” b) “when offered a choice, many patients opt for more aggressive care than they need,” and c) “it is too complicated for patients to know how to choose”;

2. Time pressures;

3. Increased uncertainty;

4. Limited health literacy and numeracy; and

5. Patient preference with respect to high-stakes decisions.

Addressing the mismatch between evidence-based practice and actual clinical care is one objective of dissemination and implementation (D&I) science. Dissemination has been defined as “the targeted distribution of information and intervention materials to a specific clinical practice audience” and implementation as “the use of strategies to adopt and integrate evidence-based health interventions and change practice patterns within specific clinical settings.”¹⁰ Recognizing that 1) SDM has benefit for some patients and is important to advancing certain patient-centered outcomes,^11,12 2) tools exist for the application of SDM in the ED,⁵ and 3) barriers exist that limit the use of such tools in actual clinical practice,⁶ it remains imperative to develop the infrastructure needed to support the D&I of SDM in emergency medicine.

Prior to the 2016 Academic Emergency Medicine consensus conference “Shared Decision Making in the Emergency Department: Development of a Policy-Relevant, Patient-Centered Research Agenda,” a multidisciplinary task force (see Appendix and Data Supplement S1, available as supporting information in the online version of this paper) held 12 conference calls to develop a prioritized research agenda for the D&I of SDM into emergency care. The proposed agenda and priority research questions were subsequently presented at the consensus conference and discussed by the D&I subgroup. The research agenda proposed in this article is based on a modified Delphi process involving the work group members. We present each of the important themes identified by the preconference task force, followed by the priority research questions within each theme, as determined by the D&I subgroup. The complete list of research questions developed during the task force meetings and consensus conference can be found in Data Supplement S2 (available as supporting information in the online version of this paper).

SECTION 1: THE SCIENCE AND STRATEGIES UPON WHICH TO BUILD D&I

Priority Research Questions

1. What D&I strategies and tools are valid and feasible for SDM in the emergency care setting?

   1. Where can clinicians access available/validated strategies and tools?

   2. Do certain strategies provide distinct advantages for patient subsets, clinical presentations, or disease processes?

   3. When during an episode of care should SDM tools be used (triage, initial assessment, predischarge, all of the above, never)?

2. Which domains of implementation best inform ED-based SDM research: assessment of cultural capacity for change, scalability, adoption, fidelity/adaptation, effectiveness, pragmatisms, evolvability, transportability, sustainability, harms, or costs?

3. How will the potential benefits or harms of implementing ED-based SDM be assessed, by whom, and at what stage in the course of care?

Evidence supporting the effectiveness of SDM is limited, but increasing in quality and quantity.⁵ It takes approximately 17 years for 14% of new practice approaches to reach the bedside.¹³ Healthy skepticism and multiple leaks in the Knowledge Translation Pipeline¹⁴ contribute to delays in implementing SDM even, in the ED setting. Premature uptake of research can be expensive, unduly risky, and inefficient.¹⁵ In addition, deimplementation of ineffective practice once dogma is established can take even longer than implementation of evidence-based behavior.^16,17

Evolving approaches to conduct pragmatic implementation research have led to proposals for a narrative approach to evidence-based medicine,^18,19 whereas others envision a more structured process that encompasses the setting, personnel, practice adaptation strategy, process, measures, resources, and outcomes. Implementation science affords one approach to simultaneously accelerate the integration of SDM into clinical practice and empirically study the process, effectiveness, unintended consequences, adaptability, and sustainability of SDM in the EM setting. When an intervention with sufficiently compelling evidence for efficacy and cost-effectiveness exists, implementation science begins with careful and collaborative consideration of the practice environment and key stakeholders involved, to ensure alignment of the SDM intervention, targets, anticipated outcomes, and available resources. Furthermore, measuring any differences between the intervention as planned and the intervention as executed is important both to understand whether a study failed to demonstrate benefit because of misapplication of the intervention (vs. misalignment of the intervention and the intended target, vs. local adaptation of the intervention into a novel/untested product) and to inform study replication in other practice settings.

What Theories Inform D&I Research in the Clinical Setting?

Properly designed implementation studies require selection of a psychosocial theory used to modify existing clinical practice that is appropriate for the setting, population, and specific outcomes being sought^20,21 to enhance the interpretability of implementation research findings.²² Theories of behavioral and institutional changes provide important explanatory models and describe the interaction of variables in health care operations.²² Theories also provide support and guidance for choice and use of D&I Frameworks. Grol et al.²⁰ organized and reviewed relevant theories describing the level of interaction (i.e., ecological level) and mechanisms and variables (see Table 1).

Table 1.

Theories of Behavioral Change

Name	Synopsis
Impact theories	Describe hypotheses and assumption about specific interventions will facilitate a desired change
Ecological levels
Individual context	Theories that explain change created through cognitive, educational, and motivational activities
Social context	Theories that explain change created through communication, social learning, social networks, teamwork, professional development, and leadership
Organizational context	Theories that explain change created through organizational innovation, culture, quality management, complexity
Political and economic context	Theories that explain change created through reimbursement and contracting
Process theories	Pertain to actual implementation of change: how should interventions be planned organized and schedule for effectiveness
Stages-of-change theories	Assumptions of step required for change to occur

Which D&I Models Are Most Appropriate for Emergency Care Research?

Implementation science models have three objectives:²³ 1) describing or guiding the process of translating research into practice, 2) understanding the factors that influence observed outcomes, and 3) assessing implementation. Prior models have been described extensively^24,25 and those most applicable for the complex ED environment and team-based approach to clinical care are summarized in Table 2. Substantial overlap exists between the content and design of the existing models, as well as the capacity for the models to fulfill design objectives. Selection of an appropriate model optimizes investigators’ ability to attribute behavior or process adaptations to causes, effects, and factors that define success in improving healthcare.²³ The Expert Recommendations for Implementing Clinical Change (ERIC) study developed recommendations for the selection of appropriate models, and their applicability to emergency medicine is summarized in Data Supplement S3 (available as supporting information in the online version of this paper).²⁴ As interest in implementation science broadens, consensus articles²⁴ and website clearinghouses, such as http://dissemination-implementation.org/ and https://www.societyforimplementationresearchcollaboration.org/, provide researchers resources with which to select an appropriate model for individual projects.

Table 2.

Description of Most Relevant D&I Models

Model	Dissemination and/or Implementation	Descriptor
Blueprint for Dissemination58	D	Eight-component strategy to align best-practice recommendations with national quality improvement efforts
Collaborative Model Between Research & Practice59	D > I	Research-practitioner collaborative approach to simultaneous implementation and data analysis/synthesis
Knowledge Exchange Framework60	D > I	Five-component approach to link evidence to practice via problem identification, defining context, knowledge classification, intervention integration, and practical application
Ottawa Interdisciplinary Research Use Model61	D = I	Multicomponent model to assess practice environment; potential adopters; and innovative translation process followed by monitoring diffusion of concepts, practice change, and multilevel outcomes
RE-AIM Framework62	D = I	Evaluation of interventions at the level of the individual (reach, efficacy), organization (adoption, implementation), as well as both individual and organization (maintenance)
Research to Practice Framework63	I > D	Method to reduce time from study to practice uptake using field-based implementation; fidelity guidance; science-based interventions; and improved links between consumers, providers, and researchers
Practical, Robust Implementation and Sustainability Model (PRISM)64	I > D	Model evaluating how intervention; external environment; sustainability infrastructure; and recipients influence adoption, implementation, and maintenance
Promoting Action on Research Implementation in Health Services (PARIHS)65	I	Multicomponent and linked model in which evidence informs summative and process measures as well as interventions while the mesoenvironment and macroenvironment inform outcome assessment

D&I = dissemination and implementation.

SECTION 2: PATIENT AND COMMUNITY ENGAGEMENT

Priority Research Questions

1. How can patients, their families, communities, and other important stakeholders be most effectively engaged in research—from study planning, conduct, dissemination, and implementation in the ED setting to facilitate SDM and the delivery of patient-centered care in routine ED practice?

2. How can EDs most effectively partner with local communities (including individual members, care practices, and organizations) to improve patient outcomes, increase patient satisfaction with both their engagement and their care, improve the coordination of care, and facilitate SDM across community care settings?

3. What are the patient-centered outcomes and goals related to SDM in the ED that matter most to patients and their families, and how do these outcomes align with those valued by health care providers in the ED setting?

In our current healthcare delivery system, multiple factors contribute to poor decision quality,¹ including:

• Patients often make decisions about treatments without completely understanding their options;

• Patients might not feel empowered or have the ability to ask questions to better understand their disease process;

• Patients might not understand there are choices in their care;

• Physicians are quite poor at guessing patient preferences;²⁶ and

• Patients/community members may not have a trusting relationship with healthcare providers.

This fact underscores the importance of adopting a true community-partnered approach to D&I so that information is shared and patients are supported to consider and express their values and preferences during the ED decision-making process.^27,28 Using a community- and patient-partnered approach, we developed a conceptual model of D&I of SDM in emergency medicine to serve as a guide for the adoption of SDM into clinical care (see Figure 1).

Figure 1.

Partnered conceptual model of D&I of SDM in emergency medicine. Consistent with the ethos of SDM, the patient, along with his or her family, community, and healthcare providers, were placed in the center of the model. Extending as spokes are specific emotional attributes and activities felt to be necessary to connect the patient and their world to the critical steps in the process. These critical steps are described by the text in the outer circles. Moving from one critical step to another has a delineated directionality, which is denoted by the arrows. Within the arrows are suggested parties either to be responsible for or to drive the change process. The colors ebb as one moves from one element to another to denote how all parties evolve over that part of the journey of SDM. D&I = dissemination and implementation; SDM = shared decision making.

To date, current research has focused on physician-perceived barriers to SDM in emergency medicine.⁶ However, understanding patient-perceived barriers, as well as patient and provider characteristics that affect decision making, is also important for successful adoption of SDM in the ED.²⁹ For example, patients may be unfamiliar with the ED and the process for delivering care. They may find themselves in urgent situations, facing choices with lasting consequences, in the absence of individuals they typically rely on for help in decision-making. Additionally, there may be a disconnect between the patient’s preferences and values and the physician’s preferences for diagnostic or treatment options.^11,30 In reality, the SDM process is designed to help address and resolve many of the physician- and patient-related factors.

Another challenge to the successful engagement of patients in the ED is perceived time constraints as well as the lack of care coordination between the ED and other ambulatory care delivery settings or service providers within the community.²⁷ Because EDs often suffer from crowding and suboptimal staffing, understanding the ergonomics of SDM in the ED—and any potential unintended consequences of SDM implementation—is needed to measure what models of community/patient partnership are most effective. Such an approach may help to understand, for example, 1) how long should (or can) ED providers spend with patients to facilitate SDM; 2) whether alternative approaches to SDM, other than patient–physician engagement, should be contemplated to facilitate community involvement (e.g., blogs, podcasts, informational videos in the ED, etc.); and 3) whether ED patients are willing to potentially spend increased time waiting for the opportunity to engage in SDM. While SDM may not require more time than usual care, time constraints are a frequently cited barrier.³¹

Additionally, emergency physicians and patients are often put in the difficult situation of making treatment decisions without the input of the patients’ other providers, past or future. The most robust study of SDM in emergency medicine focused on disposition of patients with low-risk chest pain; patients were offered the choice of outpatient follow-up with a primary care doctor or cardiologist.⁵ However, disposition decisions in many EDs occur with little knowledge of the available community resources available (or lack thereof) for helping patients deal with the practical burdens associated with follow-up. Such environment, practical, and contextual barriers to engaging patients and other important stakeholders in SDM in the ED provide ample opportunity for patient-centered research.

The unique environment of the ED, and the associated barriers to SDM within it, necessitate a research paradigm and funding mechanisms that replicate these realities and actively involve patients, families, communities, and other ED stakeholders to define and better understand engaged healthcare delivery in a complex system. Embracing these realities and engaging representative patients and communities as partners in the planning and conduct of research may help ensure that the right questions are being asked and answered and help build a foundation for timely and meaningful D&I of evidence-based approaches to SDM in the ED. This involvement may help with successful development, testing, and implementation of SDM into ED practice.

The relative infancy of SDM, and the opportunity to create consensus around a patient-centered research agenda in the ED, provides an excellent opportunity to engage patients and communities at the ground level and embrace them as the integral partners they are with the mutual goal of designing and implementing a patient-centered care paradigm in the ED.

SECTION 3: DECISION AIDS TO FACILITATE AND PROMOTE SDM

Priority Research Questions

1. How do we evaluate the effectiveness of decision aids within the emergency medicine setting and assess their impact on patient-centered outcomes? Who should define these patient-centered outcomes and are these outcomes the same for every instrument and for every patient?

2. What effective strategies can help overcome barriers to use and implementation of decision aids in the emergency medicine context?

3. How can implementation scientists ensure availability of updated decision aids at the point of care setting? How can providers use the right tool, for the right decision, at the right time, for the right patient?

4. Where can researchers access the best evidence for inclusion in decision aid development and how do we ensure that decision aids continue to include up-to-date evidence? How should “best evidence” be defined and who will determine this definition?

The most common approach to promote and facilitate SDM is through the use of decision aids,^32,33 which clearly and accessibly present the available healthcare options and their relative advantages and disadvantages and help clarify patients’ values and preferences in the appropriate context.^32,33 The use of decision aids increases patients’ knowledge, accuracy of risk perception, engagement in making decisions, and comfort with the decision-making process, but their impact on patient adherence to treatment, clinical outcomes, or use of services remains to be determined.¹²

Decision aids come in various forms: brochures, multimedia websites, cards, or combinations. They can be used in numerous ways such that they can be brief enough to be used within clinical encounters (i.e., in-visit, face-to-face) or be designed to have sufficient content that patients can use them independently (i.e., out-of-visit).³² While differing, these approaches share a similar goal that is to prepare patients and facilitate their engagement in SDM with their clinician at the point of care.

To date, commercial providers of decision aids primarily promote SDM through the distribution of decision aids to patients outside the clinical setting (e.g., reviewing different options for prostate cancer screening or management prior to the clinical encounter),^1,12 but these often provide generic rather than patient-tailored information. They also may be expensive, may be onerous to update or to integrate into practice, may contain content unfamiliar to the clinician, and may not promote patient engagement or SDM at the point of care.^12,34,35 Furthermore, these decision aids are not designed for the fast paced, chaotic environment of the ED, where care is typically unplanned and nonvoluntary and where decisions have to be made immediately.^8,9

The use of decision aids during clinical encounters, on the other hand, offers timely, relevant, and tailored support to clinicians and patients when confronted with key decisions. When specifically developed for time-sensitive use, such decision aids have been effective and feasible.⁵ They are not intended to be comprehensive or even to help patients clarify their values. Instead they rely on the unique conversations that take place between patients and clinicians providing just-in-time, tailored explanations of the patient’s current situation. While these decision aids face implementation challenges (i.e., training of clinicians, impact on duration of encounter), they have been used successfully in the ED setting.⁵

Decision aids should focus on facilitating a conversation between clinicians and patients in specific contexts. They should be developed with extensive input from patients and clinicians, prototyped early and extensively in expected clinical settings, piloted and when feasible, evaluated, in rigorous yet practical trials to ascertain their effectiveness and prevent any unintended consequences of their use.^34,36 To date, several attempts, such as efforts from the International Patient Decision Aid Standards (IPDAS) Collaboration, have been made to define and standardize the process by which decision aids are developed and tested, but their impact in producing high-quality, patient-centered, efficacious decision aids remains to be determined.

The most recent review of SDM in the ED setting identified only five studies involving decision support interventions or decision aids, but found a positive impact on patient knowledge and satisfaction, preferences for involvement in decision making, elicitation of preferences and values, and reduction of health care utilization without evidence of harm or lack of feasibility.⁹ While none of these tools are currently used routinely nationwide in the ED, more tools are being developed and evaluated, which may facilitate further use in the future.^37,38

Despite the potential benefits of decision aids, their sustained adoption in actual clinical practice has proven difficult and is far more complex than merely making these tools available.^39–41 Efforts to improve D&I of decision aids in practice remain limited overall, but prior studies have evaluated perceived barriers to decision aids use and assessed obstacles to individual behavioral change and organizational diffusion.^39,40 Overall, evidence to support how decision aids become both implemented, and subsequently sustained, in clinical practice is still needed.

SECTION 4: MEASUREMENT OF SDM

Priority Research Questions

1. What are valid, reliable, and feasible methods for measuring and evaluating SDM in the ED context?

   • Which disciplines should be involved in the development or choice of measures?

   • Should patient-reported measures or observer-based methods or both be used?

   • What are the appropriate situations and timing to measure SDM in the ED?

   • What should the practical standards for measures be—e.g., are measures feasible, meaningful, and actionable to clinicians and patients?

2. What outcomes should be used to measure the impact of SDM on the healthcare system?

   • What are the process measures that are most relevant for the patient? For the clinician? For the healthcare system?

   • What are the outcome measures that are most relevant for the patient? For the clinician? For the healthcare system?

   • What are the most relevant outcomes—e.g., impact, penetration, and/or sustainability—to assess the success of implementation of an SDM intervention and how are those best measured?

Purpose of Measurement

There is little evidence that SDM happens consistently for the majority of patients, including for those in the ED. As SDM is increasingly promoted as a model of achieving patient-centered care and interventions to increase SDM are designed and implemented, it is important to have methods for determining the effect of such interventions on patients, providers, and the healthcare system.

Measurement of SDM may serve several purposes. One is to assess the rate of SDM when appropriate, which allows for identification of gaps in care and improvements in care over time, particularly if quality improvement interventions are implemented. Another is to assess the efficacy (in clinical trials), effectiveness (in clinical practice), and reach of interventions like decision aids to increase the quality of the decision-making process. Aggregation and feedback of SDM quality metrics may help with accountability at the patient, provider, and health system levels and is important to document the effect of SDM on outcomes such as patient satisfaction and patient-oriented health outcomes in the ED.^11,42

Considerations for Choosing a SDM Measure

A detailed review of current concepts in the measurement of SDM and the state of measures in the field is provided in the Appendix. There are, however, at least three essentials considerations for choosing optimal SDM measures. The first is context. A longer, comprehensive instrument may be desirable for a decision aid efficacy trial, while measuring the level of SDM in clinical practice calls for a shorter, less burdensome measure. The second consideration is the outcome of interest. Measurement choices depend on what you are studying—decision antecedents, decision-making processes, or decision outcome (see Figure 2).^43,44 The third consideration is perspective. Patient-reported and observer-reported scales exist and measure different aspects of SDM. Table 3 lists commonly used measures.

Figure 2.

Conceptual model of medical decision making highlighting different measurement constructs. Reproduced, with permission, from Sepucha and Scholl.⁵⁷ SDM = shared decision making.

Table 3.

Commonly Used Shared Decision Making Instruments

Scale or Instrument	Description	Decision-making Domain Measured
Control Preferences Scale66,67	Original tool used card sorting method to assess preference for participation; now often translated into one item	Decision antecedent
Problem-solving Decision-making scale68	Three vignettes with six questions about patient’s preferred method of problem-solving and decision making	Decision antecedent
Autonomy Preference Index69	Twenty-three items measuring patients' preferences about involvement in care	Decision antecedent
Decisional Conflict Scale70	Sixteen-item scale covering uncertainty in decision making, informed values, clarity, support, effective decisions; low literacy version available	Decision-making process
Consumer Assessment of Health Providers and Systems (CAHPS) Survey71	Four items included on Clinician & Group/Patient-Centered Medical Home Survey; questions specific to starting medication	Decision-making process
OPTION72 OPTION(5)73	Twelve items measuring various SDM processes, rating done by observer; five-item version also available	Decision-making process
SDM-Q-974 SDM-Q-Doc75	Nine items measuring various SDM processes of care, rating either from patient or provider point of view	Decision-making process
Informed Decision-making Scale76	Seven items measuring SDM processes of care, rating done by observer	Decision-making process
CollaboRATE77	Three items measuring SDM processes of care	Decision-making process
Satisfaction with Decision Scale78	Six items measuring satisfaction with decision	Decision outcome
Decision Regret Scale79	Five items measuring decision regret	Decision outcome
Decision Quality Instruments80	Condition-specific questionnaires measuring patient knowledge, involvement, and preferences	Decision outcome

When assessing how and when to measure SDM, particularly with a patient-reported measure, two issues merit additional consideration—identification of decision point(s) and patient awareness of decision point (s).⁴⁵ Current patient-reported measures of SDM assume that patients are aware that a decision has been made. However, decisions may be made implicitly during consultations such that patients do not recognize that a decision was made or needs to be made.^46,47 This may be of particular significance in the ED, where the perceived acuity of the situation may cause patients to defer any decisions to the provider. While decision-making may have to be more prescriptive in such situations, SDM remains both possible and beneficial to care in the emergency care setting.^5,9

SECTION 5: CULTURE CHANGE

Priority Research Questions

1. What implementation/change strategies (top/down–bottom/up) best address supporting the adoption of SDM within the interactional/relationship context of EM physician/healthcare providers and care recipients?

2. What barriers and facilitators to SDM exist at the 1) individual emergency physician provider level, 2) individual patient level, 3) EM setting, and 4) health system level/administrator? At each level, how can the barriers be understood/overcome to best support adoption of SDM into standard care?

3. What emergency care decisions (e.g., clinical situations) are most amenable to, or appropriate for, SDM? Can SDM in such clinical situations be incorporated into standardized algorithms of care?

EDs are unique local practice settings with their own subcultures that evolve and change over time within larger healthcare systems. These subcultures are composed of the shared values, beliefs, practices, geographies, and expectations of their members who function in a highly stressful and unpredictable work environment.⁴⁸ Despite awareness of the concept of culture and the lived experience of providing care in EDs, few studies have actually examined the cultural processes at work in emergency medicine and their role in the facilitation or prevention of evidence-based practices.

Two recent ED studies highlight the importance of cultural awareness in the successful implementation of new evidence-based practices. In a study from the United Kingdom regarding lay and professional perceptions of what defined an “emergency,” the authors concluded that it was a “negotiated reality between people and not an objective of description of reality.”⁴⁹ Understanding this negotiated process could play an important role in changing both providers’ and patients’ perceptions and behaviors related to SDM. Meanwhile, Kirk and Nilsen⁵⁰ found that implementation of new, evidence-based practices was limited by the perceived effect on patient flow, an important cultural value held by providers which drives ED design and operations.⁵¹ A clear understanding of these cultural practices can be used to support and facilitate the implementation of new practice and behaviors, such as SDM.

Adoption of SDM will require changes in many aspects of the way emergency physicians provide care. One area is how emergency physicians make decisions and communicate with patients. One study described emergency physicians as being reluctant to share risks with patients, too focused on efficient information gathering over information sharing, and less focused on addressing lifestyle and psychosocial issues.⁵² Factors that supported this communication style include the clinical uncertainty of medicine, the importance of diagnostic accuracy, time limitations for communication, and high patient volume. These same factors, along with medicolegal pressures and reimbursement patterns, may also be barriers to the collaborative, patient-centered communication that defines SDM.

There are numerous approaches to support behavioral and cultural changes.²⁰ One example is through the implementation of clinical care pathways based on the best available evidence. These pathways can provide opportunities for the implementation of SDM into practice. However, widespread adoption of SDM requires more than simply changing clinical processes through clinical care pathways or best practices; it still requires a change in clinical culture. Another approach to culture change includes education and continued feedback on the positive effects of the behavior change on health outcomes.⁵³ This can occur at any level of training, from medical students and residents to practicing physicians. Within medical education, some believe that SDM communication skills should be taught to preclinical students so that they develop a positive attitude toward SDM before their practice habits are established⁵⁴ and before they lose their positive attitudes toward patient-centeredness as they progress through residency training.⁵⁵ However, medical students often learn communication skills by observing clinicians (either residents or faculty) in the workplace, so any intervention for behavior change must also occur at the clinician-teacher level, to mitigate any discrepancy in what students are taught and what they actually observe.⁵⁶ Beyond educational efforts, integration of SDM into daily practice will require a multipronged approach that includes enculturation of SDM into the practice community.

CONCLUSIONS

Shared decision making has not been successfully embedded into routine clinical practice to date. In this article, we advocate that academic and community partners work together to understand applicable dissemination and implementation strategies within the ED, develop decision aids for appropriate clinical scenarios, assess the efficacy and effectiveness of such tools in actual clinical practice, and advocate for changes necessary for patients’ values and preferences to be regularly incorporated into practice.

The author group thanks Richard Thomson for his contributions to the early stages of this project; Kristine Petre MLS, CM, AHIP, for her administrative assistance; and all the breakout group attendees.

Breakout Group Attendees:

Casey Clements, Carlos Torres, Christopher Gayer, Erica Shelton, Ariane Plaisance, Jean-Simon Letourneau, Timothy Jang, Tess Hogan, Timothy Platts-Mills, Olga Kovalerchik, Natalie Richmond, Katherine Hunold, Bory Kea, Charles Graffeo, Shelley McLeod, Eddie Lang, Maureen Gang, K. Gordon Ngai, Ana Castaneda-Guarderas, Annie Leblanc, Jake Valentine, Ted Melnick, Hemal Kanzaria, Juanita Booker-Vaughns, Kaoru Itakura, Lynne Richardson, Jeffrey Glassberg, Marc Probst, Pluscedia Williams, Esther Chen, Bryan Kane, Michelle Santos, Jennie Wang, Keith Kocher, Rakesh Engineer, Blair Alden Parry, Patrick Dunn, Robert Gibson, Stephen Wall, Cassandra Hall, Karen Sepucha, Angela Young-Brinn, Kei Ouchi, and Dowin Boatright.

APPENDIX

Current Concepts in the Measurement of SDM

While the standard definition of SDM provides for the actors (patient, provider, and others) and general process of SDM, to measure the effect of SDM, a more detailed understanding of the decision-making process is required. The decision-making process, as well as the outcome of the decision, needs to be considered when assessing whether “good” decision making has taken place.⁴³ Sepucha and Mulley⁴⁴ present a conceptual model of medical decision making that highlights three groups of constructs—decision antecedents, decision-making processes, and decision outcomes—that can guide measures of both processes and outcome (see Figure 2). Decision antecedents refer to characteristics of the patient and family, provider and care team, or organization that may influence the decision-making process and the success of SDM interventions. Measures of the decision-making process may focus on behaviors that happen during the consultation, such as information exchange, deliberation, and implementation of a decision.⁸¹ Finally, decision outcomes such as decision quality, defined as the consistency of an individual’s decision with his or her values, satisfaction with decision, participation in decision making and patient-centered communication, decision regret, and health outcomes may also be measured to assess the impact of SDM interventions.

Current State of SDM Measures

There is tremendous variation in existing SDM measures, with no one instrument being consistently used in clinical trials.⁸² Scholl et al.⁸³ found 19 different measures in a recent systematic review; on the other hand, Bekker et al.⁸⁴ found that less than one-third of articles evaluating SDM included a measure of the quality of the decision-making process. Existing measures may assess only one of the decision-making components such as decision antecedent, processes of care, or outcomes; only a few instruments measure multiple dimensions of the decision-making process. There are both patient-reported and observer-reported measures. However, many of the measures have been validated in only a small number of patients and thus the psychometric properties and validity testing are often of only fair or poor quality, and many of the patient-reported measures did not include patients in the development of the scale.^45,85 Finally, some instruments have been developed for specific decisions while others more generically measure aspects of SDM. Thus, there is no current criterion standard for measuring the quality of SDM, either in research studies or in clinical practice. Table 3 lists commonly used measures.

Measures of decision antecedents assess a patient’s desire for information and participation in the decision-making process. Measures may focus on just the decision antecedents, for example, the Control Preferences Scale,⁶⁷ the Problem-solving Decision-making Scale,⁶⁸ and the Autonomy Preference Index;⁶⁹ other multidimensional measures may include a single question addressing patient preferences for participation. However, it is unclear if assessment via a single item is as reliable as the aforementioned scales.

Many studies assessing the efficacy of decision aids use measures that target the decision-making process, primarily from the patient point of view. The most commonly used measure is the Decisional Conflict Scale, a 16-item scale that includes five subscales: uncertainty, informed, values clarity, support, and effective decision. Another commonly used self-report measure is the 9-item SDM Questionnaire (SDM-Q-9).⁷⁴ Both the Decisional Conflict Scale and the SDM-Q-9 have had extensive validation testing and have been translated into multiple languages.⁷⁰ There are also items rating the decision-making process contained in the supplemental Consumer Assessment of Health Providers and Systems survey (CAHPS) survey,⁷¹ a commonly used survey to assess the quality of providers. Finally, there are observational measures that assess the decision-making process. For example, the Observing Patient Involvement in Decision Making (OPTION) scale^72,73 and the Informed Decision Making scale⁷⁶ rely on review of audiotaped encounters to rate physician behaviors. These scales measure the presence of certain skills or behaviors, such as physician communication skills, information exchanged, assessment of patient understanding, and patient role preference elicitation, during a consultation to determine the extent to which clinicians encourage participatory decision making. However, application of these scales is time- and labor-intensive, involving either direct observation of a consultation or review of audiotapes or transcripts.

Instruments measuring decision outcomes are somewhat less developed, particularly in the case of measuring decision quality. Decision quality measures that contain all the relevant domains (knowledge and match of goals and treatment) are generally condition-specific and have been developed for a wide variety of conditions from breast cancer to hip osteoarthritis.⁸⁰ More generic measures of decision outcome include the Decision Regret Scale,⁷⁹ which examines distress and regret following a decision, and the Satisfaction with Decision scale,⁷⁸ which measures decision satisfaction. The link between SDM and health outcomes has been much more difficult to demonstrate, as SDM is often employed in situations where clinical equipoise exists. However, demonstrating the effect of SDM on clinical outcomes may be a key to increasing the buy-in and support of health systems for SDM programs.