Background
Implementing complex interventions, such as use of shared decision making (SDM) tools, within clinical encounters requires participation from patients and clinicians. Despite evidence of their effectiveness and enthusiastic policymaker endorsement, the real-world uptake of tools to promote SDM has been limited [
1]. Process evaluations of practical or effectiveness trials can contribute to understanding how complex interventions, such as use of SDM tools, may be implemented beyond the trial period [
2].
Normalization Process Theory (NPT) provides a framework for understanding the process of implementing complex interventions in healthcare [
3,
4]. NPT proposes that complex interventions (e.g., SDM tools in practice) become routinely embedded (implemented and integrated) in their organizational and professional contexts as a result of people working, individually and collectively, to implement them. It involves four domains: (1) making sense of the intervention, (2) getting people involved, (3) doing the work, and (4) evaluating the intervention in daily practice (Table
1). NPT can be used as a framework to understand how healthcare interventions interact with the existing clinic processes, clinical practice, and patient–clinician encounters and the work professionals do to enact them [
3,
4].
Table 1Domains of Normalization Process Theory
Coherence | Making sense of the proposed intervention |
Cognitive participation | Getting people involved in the implementation project, buy-in |
Collective action | Doing the work to make the intervention part of daily practice, organizational resources, training, and division of labor; confidence, expertise, and intervention workability |
Reflexive monitoring | Evaluating the use of the intervention in daily practice and monitoring its value |
Although the barriers and facilitators for the implementation of patient-facing decision aids have been reported, less is known about the factors that promote or hinder the implementation of SDM conversation aids, which are used by the patient–clinician dyad during the clinical encounter [
5]. The implementation of SDM tools during the consultation involves the execution and orchestration of individual and collective work and the work that is promoted or hindered as integration into routine practice takes place. The persistent difference between enthusiasm for SDM and limited documented use of SDM tools in practice strongly suggests the presence of hindering factors (e.g., clinician burnout, lack of organizational support, logistical barriers). Here, we explore the factors that promote or hinder this work within an ongoing practical randomized trial requiring the integration of an SDM conversation tool in practice to evaluate its effectiveness against usual care. This SDM conversation tool, the Anticoagulation Choice Decision Aid, was designed to assist patients with atrial fibrillation and their clinicians with the decision of whether and how to use anticoagulants to prevent thromboembolic strokes [
6]. We report on the participating clinicians’ characteristics and professional roles, levels of burnout, and perspectives on normalizing the use of the Anticoagulation Choice Decision Aid tool within the workflow of their clinical practices.
Discussion
Summary of findings
Embedding an intervention in clinical routines is necessary to evaluate its effectiveness in practice. This process takes individual and collective work subject to barriers and facilitators. Identifying and addressing these factors is critical in the design and implementation of practical clinical trials. This is particularly important when barriers and facilitators may differ across sites of a multisite trial. Here, we explored the embedding of an SDM intervention in routine clinical consultations as we recruited clinicians for a multicenter trial evaluating it. Clinicians rated the normalization potential of the intervention highly; for cardiologists, using the SDM tool in care made more sense than for other types of clinicians. Clinicians endorsed all domains of normalization to the same extent, regardless of site, clinician characteristics, or burnout or callousness ratings. Ninety-two percent of clinicians saw the value of using the Anticoagulation Choice Decision Aid tool, and 96% were open to working with colleagues to improve the use of it in practice. Fewer clinicians saw how the Anticoagulation Choice Decision Aid tool differed from their normal work (72%), agreed that there were drivers leading the implementation of the conversation aid (75%), or responded in agreement with items related to collective action (70–77%). Qualitatively, clinicians paid most attention to making sense of the tool. Tool buy-in seemed to depend heavily on clinicians’ ability to see the tool as accurate and “evidence-based” and on their having time to use it during consultations. They mentioned that the Anticoagulation Choice Decision Aid tool might lead to standardization of clinical encounters. Collective action issues focused on who has time and information to use the tool (e.g., enrolling pharmacists and the information to which they have access when including patient out-of-pocket costs in SDM conversations). Few clinicians commented on the concept of “shared decision making” per se (less than 1% of clinician utterances).
Comparison with previous studies
While clinicians found coherence between their job and using the SDM conversation tool, they were less likely to agree that using the Anticoagulation Choice Decision Aid tool differed from their normal work. This is consistent with a metasynthesis of qualitative studies which found that for conversations about anticoagulation for atrial fibrillation, clinicians reported engaging in SDM routinely, even when patients were more likely to report a less participatory approach [
14]. This was also supported by an evaluation of real-world distribution of decision aids; qualitative data suggested that clinicians did not have a shared understanding of the purpose of the decision aid [
1].
Similar to the findings of the systematic review by Legaré et al., who documented that clinicians identify time constraints and lack of pertinence of the SDM intervention to patients and clinical situations as barriers to SDM implementation [
5]. The design of the Anticoagulation Choice Decision Aid tool as an SDM conversation aid enables clinicians to tailor the tool to the patient’s situation [
6], dealing with the latter barriers, and it may, in fact, efficiently guide a complex conversation and save time. Although SDM conversation tools demand dedicated and structured work that may change the way the clinician feels about time during the encounter, a recent systematic review of these tools demonstrated that, on average, these tools do not significantly prolong the clinical encounter [
15].
Previous studies have also found burnout to be negatively associated with adaptive reserve [
16], “practice features that enhance resilience, such as relationships” [
17]. Burnout has also been associated with less empathic concern and decreased “effort to adopt the point of view of another person” [
18]. While SDM has been proposed as an intervention to increase meaningful encounters and decrease burnout [
19], our findings do not directly support an association between burnout and enthusiasm regarding SDM. However, given the highly positive response by clinicians to openness to collaboration with colleagues, their multiple inquiries regarding other clinicians using the Anticoagulation Choice Decision Aid tool, encouraging collaboration and innovation between team members, and involving local leadership may improve implementation of complex interventions such as SDM tools.
Limitations
Process evaluations during trials may provide insights about the factors that promote or inhibit the implementation of complex interventions that are different from those gained from evaluations performed outside of research endeavors [
2]. Research studies are temporary, require participant consent, and allow participant withdrawal without penalties (Fig.
1). Temporary add-on trial procedures, for instance, may overwhelm clinicians, who then opt out of the research, or, conversely, they may elicit weaker responses than permanent or mandatory practice changes. Similarly, clinicians choosing to participate in the trial may have been more enthusiastic about the intervention than those who declined. This study was conducted at the beginning of the trial, before participating clinicians had an opportunity to use the tool with patients. Therefore, we captured mostly clinicians’ expectations about using the SDM tool, informed by very brief training and demonstration when clinicians may have been more enthusiastic about the process. We did not assess “reflexive monitoring,” the fourth domain of NPT, which requires responding to questions after having regularly used the intervention, such as, “Given the changes observed as a result of the intervention, should we keep doing it?” For example, the organic monitoring, appraisal, and endorsement by clinical staff (represented by white arrows and white panel in Fig.
1) were not measured in our study. These limitations affect inferences about the normalization of SDM tools in practice to a greater extent than about the procedures for ongoing clinician recruitment into our trial, the purpose with which we designed this process evaluation. Finally, while participants were informed that the results would be anonymized, it is possible that clinicians may have felt uncomfortable reporting high levels of burnout for fear of stigma or professional repercussions.
Implications for research and practice
It has been suggested that SDM may decrease clinician burnout by creating more meaningful patient–clinician encounters [
19]. A clinician communication skills training intervention was associated with a significant and small decrease in burnout [
20]. Yet, trials testing SDM tools rarely collect the clinician perspective, with no trials collecting measures of burnout or clinician well-being [
15,
19,
21]. Our study explored the interplay between SDM implementation and contextual factors such as burnout and practice resources such as time in consultation. A key insight that participants offered and deserves further exploration is that the normalization of SDM tools in practice may benefit from supporting collective action. We found that people were enthusiastic about working with colleagues, a process hindered by their lack of awareness of who else was participating in it and who was driving the implementation of the tool in their clinics. Perhaps future research should ascertain not just clinician burnout but also isolation.
This process evaluation contributed to the rollout of the trial. Clinicians were invited to provide feedback and ask questions about trial procedures and the tool. When study staff (research assistants and study coordinators) were unable to answer questions in real time (e.g., about bleeding risk estimates), questions were referred to the principal investigators. The principal investigators, topic experts at their own sites, contacted participating clinicians to respond to these queries, communicating their buy-in in the use of the SDM tool. Internally, study staff maintained a live database of questions and topics that came up during clinician consent or NPT interviews. The study staff recorded and regularly updated crowdsourced answers (Fig.
1) to maintain coherence regarding the tool and trial within the study team and between study sites. In these interactions, we had to maintain a balance between facilitating the use of the SDM tool and maintaining a sense of uncertainty about its relative efficacy (rather than advocating for its value), which justified the clinical trial.
Clinicians made several requests to modify the content of the tool. For example, the tool was designed to support a conversation between clinicians and their patients; patient and clinician expertise and experience should enhance the tool and tailor its effect to each patient and situation, contributing to a pertinent and useful SDM conversation. In this way, we resisted adding more information to the tool, a common request, because this may have reduced clinician participation in the conversation and promoted instead an interaction between the patient and the SDM tool. Other changes could be accommodated. For example, we added the ability to toggle between 5-year and 1-year risk estimates.
Finally, an apparent disconnect emerged between the communication goals of the research and of clinicians, the former more focused on cocreation and the latter on conveying information. A previous study showed that even within clinic teams, there are dissimilar interpretations of SDM [
22]. In our random sample of 30 recordings (112 clinicians), only 2 comments mentioned SDM, and these arose from making sense of using SDM tools rather than a philosophical discussion on the purpose of “shared decision making.” In this way, far from having arrived at a broad consensus of definition, purpose, and value of SDM, our study suggests that clinicians continue to negotiate the purpose and value of SDM in their practices. Future studies should continue to explore the clinician perspective, particularly when SDM implementation must take place within individual and collective workflows. Clinicians can both give meaning to SDM tools and preclude their presence in clinical encounters.
Acknowledgements
Shared Decision Making for Atrial Fibrillation (SDM4AFib) Trial Investigators: Steering committee—principal investigator: Victor Montori; study statistician: Megan E. Branda; coinvestigators: Juan Pablo Brito, Marleen Kunneman, and Ian Hargraves; study coordinator: Angela L. Sivly; study manager: Kirsten Fleming; site principal investigators: Bruce Burnett (Park Nicolette-HealthPartners, Minneapolis, MN, USA), Mark Linzer and Haeshik Gorr (Hennepin Healthcare System, Minneapolis, MN, USA), Elizabeth Jackson and Erik Hess (University of Alabama at Birmingham, Birmingham, AL, USA), Takeki Suzuki and James Hamilton IV (University of Mississippi Medical Center, Jackson, MS, USA), and Peter A. Noseworthy (Mayo Clinic, Rochester, MN, USA). Site teams (alphabetical order)—Hennepin Healthcare System: Haeshik Gorr, Alexander Haffke, Mark Linzer, Jule Muegge, Sara Poplau, Benjamin Simpson, Miamoua Vang, and Mike Wambua; Mayo Clinic: Joel Anderson, Emma Behnken, Fernanda Bellolio, Juan Pablo Brito, Renee Cabalka, Michael Ferrara, Kirsten Fleming, Rachel Giblon, Ian Hargraves, Jonathan Inselman, Marleen Kunneman, Annie LeBlanc, Victor Montori, Peter Noseworthy, Marc Olive, Paige Organick, Nilay Shah, Gabriela Spencer-Bonilla, Amy Stier, Anjali Thota, Henry Ting, Derek Vanmeter, and Claudia Zeballos-Palacios; Park Nicollet-HealthPartners: Carol Abullarde, Bruce Burnett, Lisa Harvey, and Shelly Keune; University of Alabama at Birmingham: Elizabeth Jackson, Erik Hess, Timothy Smith, Shannon Stephens; University of Mississippi Medical Center: Bryan Barksdale, James Hamilton IV, Theresa Hickey, Roma Peters, Memrie Price, Takeki Suzuki, Connie Watson, and Douglas Wolfe. Data safety and monitoring board—Gordon Guyatt, MD (chair), Brian Haynes, and George Tomlinson. Expert advisory panel—Paul Daniels, Bernard Gersh, Erik Hess, Thomas Jaeger, Robert McBane, and Peter Noseworthy (chair).
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