Project description:BackgroundShared Decision-making (SDM), a medical decision-making model, was popularized in the late 1980s in reaction to then predominate paternalistic decision-making, aiming to better meet the needs of patients. Extensive research has been conducted internationally examining the benefits of SDM implementation; however, existing theory on how SDM works, for whom, in which circumstances, and why is limited. While literature has shown positive patient, health care provider, and system benefits (SDM outputs), further research is required to understand the nuances of this type of decision-making. As such, we set out to address: "In which situations, how, why, and for whom does SDM between patients and health care providers contribute to improved engagement in the Shared Decision-making process?"MethodsTo achieve our study goals we conducted a seven-step realist synthesis process, which included: (1) preliminary program theory development, (2) search strategy development, (3) selection and appraisal of literature in accordance with realist methodology, (4) data extraction, (5) identification of relevant formal theories, (6) data analysis and synthesis, and (7) formation of a revised program theory with the input of stakeholders. This process was done in accordance with RAMESES guidelines and publication standards for a realist synthesis. Expert consultations were also held to ensure consistency within the SDM literature.ResultsThrough our realist synthesis, we developed a program theory of SDM which includes three contexts (pre-existing relationship, difficulty of decision, and system support), eight mechanism sets (anxiety, trust, perception of other party capacity, perception of time, self-efficacy, world view, perception of capacity to external support, and recognition of decision), and one outcome (engagement in SDM).ConclusionsAs far as the authors of this paper are aware, this paper is the first to begin unpacking how SDM works, for whom, in which circumstances, and why. By examining key mechanism sets and exploring how they facilitate or inhibit SDM, we have produced a program theory that may assist health care professionals, policy makers, and patients. While further research is suggested to further unpack the concepts identified within this paper, this provides an initial understanding into the theory behind SDM.RegistrationPROSPERO: CRD42017062609.

Project description:BackgroundShared decision-making (SDM) has been shown to improve healthcare outcomes and is a recognized right of patients. Policy requires health services to implement SDM. However, there is limited research into what interventions work and for what reasons. The aim of the study was to develop a series of interventions to increase the use of SDM in maternity care with stakeholders.MethodsInterventions to increase the use of SDM in the setting of pregnancy care were developed using Behaviour Change Wheel and Theoretical Domains Framework and building on findings of an in-depth qualitative study which were inductively analysed. Intervention development workshops involved co-design, with patients, clinicians, health service administrators and decision-makers, and government policy makers. Workshops focused on identifying viable SDM opportunities and tailoring interventions to the local context (the Royal Women's Hospital) and salient qualitative themes.ResultsPain management options during labour were identified by participants as a high priority for application of SDM, and three interventions were developed including patient and clinician access to the Victorian Government's maternity record via the patient portal and electronic medical records (EMR); a multi-layered persuasive communications campaign designed; and clinical champions and SDM simulation training. Factors identified by participants for successful implementation included having alignment with strategic direction of the service, support of leaders, using pre-standing resources and workflows, using clinical champions, and ensuring equity.ConclusionThree interventions co-designed to increase the use of SDM for pain management during labour address key barriers and facilitators to SDM in maternity care. This study exemplifies how health services can use behavioural science and co-design principles to increase the use of SDM. Insights into the co-design of interventions to implement SDM in routine practice provide a framework for other health services, policy makers and researchers.

Project description:BackgroundShared decision-making (SDM) is widely recommended and required by the Centers for Medicare and Medicaid for patients considering lung cancer screening (LCS).ObjectiveWe examined clinicians' communication practices and perceived barriers of SDM for LCS at three medical centers with established screening programs.DesignMulticenter qualitative study of clinicians participating in LCS.ApproachWe performed semi-structured interviews, which were transcribed and analyzed using directed content analysis, guided by a theoretical model of patient-clinician communication.ParticipantsWe interviewed 24 clinicians including LCS coordinators (2), pulmonologists (3), and primary care providers (17), 4 of whom worked for the LCS program, a thoracic surgeon, and a radiologist.ResultsAll clinicians agreed with the goal of SDM, to ensure the screening decision was congruent with the patient's values. The depth and type of information presented by each clinician role varied considerably. LCS coordinators presented detailed information including numeric estimates of benefit and harm. Most PCPs explained the process more generally, focusing on logistics and the high rate of nodule detection. No clinician explicitly elicited values or communication preferences. Many PCPs tailored the conversation based on their implicit understanding of patients' values and preferences, gained from past experiences. PCPs reported that time, lack of detailed personal knowledge of LCS, and patient preferences were barriers to SDM. Many clinicians perceived that a significant proportion of patients were not interested in specific percentages and preferred to receive a clinician recommendation.ConclusionsOur results suggest that clinicians support the goal of SDM for LCS decisions but PCPs may not perform some of its elements. The lack of completion of some elements, such as PCPs' lack of in-depth information exchange, may reflect perceived patient preferences for communication. As LCS is implemented, further research is needed to support a personalized, patient-centered approach to produce better outcomes.

Project description:BackgroundClinical trial recruitment is a continuing challenge for medical researchers. Previous efforts to improve study recruitment have rarely been informed by theories of human decision making and behavior change. We investigate the trial recruitment strategies reported by study recruiters, guided by two influential theoretical frameworks: shared decision-making (SDM) and the Theoretical Domains Framework (TDF) in order to explore the utility of these frameworks in trial recruitment.MethodsWe interviewed all nine active study recruiters from a multi-site, open-label pilot trial assessing the feasibility of a large-scale randomized trial. Recruiters were primarily nurses or master's-level research assistants with a range of 3 to 30 years of experience. The semi-structured interviews included questions about the typical recruitment encounter, questions concerning the main components of SDM (e.g. verifying understanding, directive vs. non-directive style), and questions investigating the barriers to and drivers of their recruitment activities, based on the TDF. We used directed content analysis to code quotations into TDF domains, followed by inductive thematic analysis to code quotations into sub-themes within domains and overarching themes across TDF domains. Responses to questions related to SDM were aggregated according to level of endorsement and informed the thematic analysis.ResultsThe analysis helped to identify 28 sub-themes across 11 domains. The sub-themes were organized into six overarching themes: coordinating between people, providing guidance to recruiters about challenges, providing resources to recruiters, optimizing study flow, guiding the recruitment decision, and emphasizing the benefits to participation. The SDM analysis revealed recruiters were able to view recruitment interactions as successful even when enrollment did not proceed, and most recruiters took a non-directive (i.e. providing patients with balanced information on available options) or mixed approach over a directive approach (i.e. focus on enrolling patient in study). Most of the core SDM constructs were frequently endorsed.ConclusionsIdentified sub-themes can be linked to TDF domains for which effective behavior change interventions are known, yielding interventions that can be evaluated as to whether they improve recruitment. Despite having no formal training in shared decision-making, study recruiters reported practices consistent with many elements of SDM. The development of SDM training materials specific to trial recruitment could improve the informed decision-making process for patients.

Project description:Background. Accurate diagnosis of patients' preferences is central to shared decision making. Missing from clinical practice is an approach that links pretreatment preferences and patient-reported outcomes. Objective. We propose a Bayesian collaborative filtering (CF) algorithm that combines pretreatment preferences and patient-reported outcomes to provide treatment recommendations. Design. We present the methodological details of a Bayesian CF algorithm designed to accomplish 3 tasks: 1) eliciting patient preferences using conjoint analysis surveys, 2) clustering patients into preference phenotypes, and 3) making treatment recommendations based on the posttreatment satisfaction of like-minded patients. We conduct a series of simulation studies to test the algorithm and to compare it to a 2-stage approach. Results. The Bayesian CF algorithm and 2-stage approaches performed similarly when there was extensive overlap between preference phenotypes. When the treatment was moderately associated with satisfaction, both methods made accurate recommendations. The kappa estimates measuring agreement between the true and predicted recommendations were 0.70 (95% confidence interval = 0.052-0.88) and 0.73 (0.56-0.90) under the Bayesian CF and 2-stage approaches, respectively. The 2-stage approach failed to converge in settings in which clusters were well separated, whereas the Bayesian CF algorithm produced acceptable results, with kappas of 0.73 (0.56-0.90) and 0.83 (0.69-0.97) for scenarios with moderate and large treatment effects, respectively. Limitations. Our approach assumes that the patient population is composed of distinct preference phenotypes, there is association between treatment and outcomes, and treatment effects vary across phenotypes. Findings are also limited to simulated data. Conclusion. The Bayesian CF algorithm is feasible, provides accurate cluster treatment recommendations, and outperforms 2-stage estimation when clusters are well separated. As such, the approach serves as a roadmap for incorporating predictive analytics into shared decision making.

Project description:The ethical argument that shared decision-making is "the right" thing to do, however laudable, is unlikely to change how healthcare is organized, just as evidence alone will be an insufficient factor: practice change is governed by factors such as cost, profit margin, quality, and efficiency. It is helpful, therefore, when evaluating new approaches such as shared decision-making to conceptualize potential consequences in a way that is broad, long-term, and as relevant as possible to multiple stakeholders. Yet, so far, evaluation metrics for shared decision-making have been mostly focused on short-term outcomes, such as cognitive or affective consequences in patients. The goal of this article is to hypothesize a wider set of consequences, that apply over an extended time horizon, and include outcomes at interactional, team, organizational and system levels, and to call for future research to study these possible consequences.To date, many more studies have evaluated patient decision aids rather than other approaches to shared decision-making, and the outcomes measured have typically been focused on short-term cognitive and affective outcomes, for example knowledge and decisional conflict. From a clinicians perspective, the shared decision-making process could be viewed as either intrinsically rewarding and protective, or burdensome and impractical, yet studies have not focused on the impact on professionals, either positive or negative. At interactional levels, group, team, and microsystem, the potential long-term consequences could include the development of a culture where deliberation and collaboration are regarded as guiding principles, where patients are coached to assess the value of interventions, to trade-off benefits versus harms, and assess their burdens-in short, to new social norms in the clinical workplace. At organizational levels, consistent shared decision-making might boost patient experience evaluations and lead to fewer complaints and legal challenges. In the long-term, shared decision-making might lead to changes in resource utilization, perhaps to reductions in cost, and to modification of workforce composition. Despite the gradual shift to value-based payment, some organizations, motivated by continued income derived from achieving high volumes of procedures and contacts, will see this as a negative consequence.We suggest that a broader conceptualization and measurement of shared decision-making would provide a more substantive evidence base to guide implementation. We outline a framework which illustrates a hypothesized set of proximal, distal, and distant consequences that might occur if collaboration and deliberation could be achieved routinely, proposing that well-informed preference-based patient decisions might lead to safer, more cost-effective healthcare, which in turn might result in reduced utilization rates and improved health outcomes.

Project description:ObjectivesThis study uses the diffusion of innovations (DOI) theory to comprehensively understand the adoption of shared decision-making (SDM) in clinical practice, specifically focusing on the 'knowledge' and 'persuasion' stages within DOI. We aim to understand the challenges and dynamics associated with SDM adoption, offering insights for more patient-centred decision-making in healthcare.DesignThis qualitative study employs a modified framework analysis approach, integrating ethnographic and interview data from prior research, along with additional interviews. The framework used is based on the DOI theory.Study setting and participantsThis study was conducted in the obstetrics and gynaecology department of a tertiary teaching hospital in the Eastern region of the Netherlands. It included interviews with 20 participants, including gynaecologists, obstetrics registrars and junior doctors currently practising in the department. Additionally, data from prior research conducted within the same department were incorporated, ensuring the maintenance of contextual consistency.ResultsFindings reveal a complex interplay between SDM's benefits and challenges. Clinicians value SDM for upholding patient autonomy and enhancing medical practice, viewing it as valuable for medical decision-making. Decision aids are seen as advantageous in supporting treatment decisions. Challenges include compatibility issues between patient and clinician preferences, perceptions of SDM as time-consuming and difficult and limitations imposed by the rapid pace of healthcare and its swift decisions. Additionally, perceived complexity varies by situation, influenced by colleagues' attitudes, with limited trialability and sparsely observed instances of SDM.ConclusionsClinicians' decision to adopt or reject SDM is multifaceted, shaped by beliefs, cognitive processes and contextual challenges. Cognitive dissonance is critical as clinicians reconcile their existing practices with the adoption of SDM. Practical strategies such as practice assessments, open discussions about SDM's utility and reflective practice through professional development initiatives empower clinicians to make the best informed decision to adopt or reject SDM.

Dataset Information

Objectifying Priority Scoring and Shared Decision-Making in Head and Neck Cancer Reconstructive Surgery during the COVID-19 Pandemic: From Theory to Practice.

Publications

Objectifying Priority Scoring and Shared Decision-Making in Head and Neck Cancer Reconstructive Surgery during the COVID-19 Pandemic: From Theory to Practice.

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