Dataset Information

Shared Decision-Making as the Future of Emergency Cardiology.

ABSTRACT: Shared decision-making is playing an increasingly large role in emergency cardiovascular care. Although there are many challenges to successfully performing shared decision-making in the emergency department, there are numerous clinical scenarios in which it should be used. In this article, we explore new research and emerging decision aids in the following emergency care scenarios: (1) low-risk chest pain; (2) new-onset atrial fibrillation; and (3) moderate-risk syncope. These decision aids are designed to engage patients and facilitate shared decision-making for specific treatment and disposition (admit vs discharge) decisions. We then offer a 3-step, practical approach to performing shared decision-making in the acute care setting, on the basis of broad stakeholder input and previous conceptual work. Step 1 involves simply acknowledging that a clinical decision needs to be made. Step 2 involves a shared discussion about the working diagnosis and the options for care in the context of the patient's values, preferences, and circumstances. The third and final step requires the patient and provider to agree on a plan of action regarding further medical care. The implementation of shared decision-making in emergency cardiology has the potential to shift the paradigm of clinical practice from paternalism toward mutualism and improve the quality and experience of care for our patients.

SUBMITTER: Probst MA

PROVIDER: S-EPMC5800967 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Shared Decision-Making as the Future of Emergency Cardiology.

Probst Marc A MA Noseworthy Peter A PA Brito Juan P JP Hess Erik P EP

The Canadian journal of cardiology 20170922 2

Shared decision-making is playing an increasingly large role in emergency cardiovascular care. Although there are many challenges to successfully performing shared decision-making in the emergency department, there are numerous clinical scenarios in which it should be used. In this article, we explore new research and emerging decision aids in the following emergency care scenarios: (1) low-risk chest pain; (2) new-onset atrial fibrillation; and (3) moderate-risk syncope. These decision aids are ...[more]

PMID: 29289400

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Project description:ImportanceEngaging in shared decision-making (SDM) can help patients understand and choose treatments according to their values and has been shown to improve patient satisfaction and adherence with treatment. It is well suited for conditions like eczema for which several medically appropriate treatment options exist. However, little is known about the use and experience of SDM in eczema.ObjectiveTo understand experiences, preferences, and expectations for SDM in eczema care settings from the patient and caregiver perspective.Design, setting, and participantsThe National Eczema Association conducted an online survey in January 2021 among self-selected patients and caregivers. Inclusion criteria (US resident, patient with eczema or caregiver of a patient with eczema aged ≤17 years, respondent age ≥18 years) were met by 1313 of 1387 respondents (94.7%). Data analysis was performed from May 2021 to November 2021.Main outcomes and measuresOutcomes were past SDM (using a 9-item SDM questionnaire [SDMQ9]; score ranges transformed to 0-100), present SDM (Control Preferences Scale), and future SDM (self-reported confidence and motivation to engage in SDM) behavior.ResultsAmong the 1313 respondents included in the study, most were female (1046 of 1313 [79.7%]) adult (1086 of 1313 [82.7%]) patients with a mean (SD) patient Recap of Atopic Eczema score of 11.7 (7.2), mean (SD) patient age of 39.5 (22.2) years, and mean (SD) SDMQ9 score of 65.1 (27.4). For present SDM, 479 of 966 (49.6%) reported "I prefer to make the final decision after seriously considering my doctor's opinion," and 655 of 955 (69.4%) reported being very or extremely confident to engage in SDM in the future. Those who reported feeling "very well informed" about the causes of eczema had a 14.7-point higher (95% CI, 9.2-20.2; P < .001, multiple linear regression) SDMQ9 score than those "not adequately informed" and were 3.4 times more likely (95% CI, 2.1-5.7; P < .001, multiple logistic regression) to be confident to engage in future SDM. Respondents reported that they would be motivated to engage in SDM if the clinician initiated SDM, valued input from the patient, and acknowledged that patients are experts on their own bodies or if a treatment is no longer working.Conclusions and relevanceResults of this survey study suggest that a majority of patients with eczema and caregivers prefer a large role in decision-making for their care and that clinicians can initiate and facilitate SDM to improve patient satisfaction with care.

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:OBJECTIVES:As shared decision making (SDM) has received increased attention as a method to improve the patient-centeredness of emergency department (ED) care, we sought to determine patients' desired level of involvement in medical decisions and their perceptions of potential barriers and facilitators to SDM in the ED. METHODS:We surveyed a cross-sectional sample of adult ED patients at three academic medical centers across the United States. The survey included 32 items regarding patient involvement in medical decisions including a modified Control Preference Scale and questions about barriers and facilitators to SDM in the ED. Items were developed and refined based on prior literature and qualitative interviews with ED patients. Research assistants administered the survey in person. RESULTS:Of 797 patients approached, 661 (83%) agreed to participate. Participants were 52% female, 45% white, and 30% Hispanic. The majority of respondents (85%-92%, depending on decision type) expressed a desire for some degree of involvement in decision making in the ED, while 8% to 15% preferred to leave decision making to their physician alone. Ninety-eight percent wanted to be involved with decisions when "something serious is going on." The majority of patients (94%) indicated that self-efficacy was not a barrier to SDM in the ED. However, most patients (55%) reported a tendency to defer to the physician's decision making during an ED visit, with about half reporting they would wait for a physician to ask them to be involved. CONCLUSION:We found that the majority of ED patients in our large, diverse sample wanted to be involved in medical decisions, especially in the case of a "serious" medical problem, and felt that they had the ability to do so. Nevertheless, many patients were unlikely to actively seek involvement and defaulted to allowing the physician to make decisions during the ED visit. After fully explaining the consequences of a decision, clinicians should make an effort to explicitly ascertain patients' desired level of involvement in decision making.

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.

Dataset Information

Shared Decision-Making as the Future of Emergency Cardiology.

Publications

Shared Decision-Making as the Future of Emergency Cardiology.

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