PND78 PATIENT REPORTED OUTCOMES TOOLS AND SHARED DECISION-MAKING IN PEDIATRIC EPILEPSY POPULATION AND THEIR CAREGIVERS: A SYSTEMATIC REVIEW

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.

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512-P: Desire for and Experience of Shared Decision-Making and Associations with Patient-Reported Outcomes in Those with Diabetes

Diabetes ◽

10.2337/db21-512-p ◽

2021 ◽

Vol 70 (Supplement 1) ◽

pp. 512-P

Author(s):

EMILY SYVERUD ◽

SARAH T. MANSER ◽

STEVEN ARRIAZA ◽

ELIZABETH A. ROGERS

Keyword(s):

Decision Making ◽

Shared Decision Making ◽

Patient Reported Outcomes ◽

Shared Decision ◽

Patient Reported

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Strategies to evaluate healthcare provider trainings in shared decision-making (SDM): a systematic review of evaluation studies

BMJ Open ◽

10.1136/bmjopen-2018-026488 ◽

2019 ◽

Vol 9 (6) ◽

pp. e026488 ◽

Cited By ~ 7

Author(s):

Evamaria Müller ◽

Alena Strukava ◽

Isabelle Scholl ◽

Martin Härter ◽

Ndeye Thiab Diouf ◽

...

Keyword(s):

Systematic Review ◽

Decision Making ◽

Healthcare Provider ◽

Shared Decision Making ◽

Evaluation Studies ◽

Quality Criteria ◽

Evaluation Framework ◽

Shared Decision ◽

Evaluation Strategies ◽

Patient Reported

Design and objectivesWe performed a systematic review of studies evaluating healthcare provider (HCP) trainings in shared decision-making (SDM) to analyse their evaluation strategies.Setting and participantsHCP trainings in SDM from all healthcare settings.MethodsWe searched scientific databases (Medline, PsycInfo, CINAHL), performed reference and citation tracking, contacted experts in the field and scanned the Canadian inventory of SDM training programmes for healthcare professionals. We included articles reporting data of summative evaluations of HCP trainings in SDM. Two reviewers screened records, assessed full-text articles, performed data extraction and assessed study quality with the integrated quality criteria for review of multiple study designs (ICROMS) tool. Analysis of evaluation strategies included data source use, use of unpublished or published measures and coverage of Kirkpatrick’s evaluation levels. An evaluation framework based on Kirkpatrick’s evaluation levels and the Quadruple Aim framework was used to categorise identified evaluation outcomes.ResultsOut of 7234 records, we included 41 articles reporting on 30 studies: cluster-randomised (n=8) and randomised (n=9) controlled trials, controlled (n=1) and non-controlled (n=7) before-after studies, mixed-methods (n=1), qualitative (n=1) and post-test (n=3) studies. Most studies were conducted in the USA (n=9), Germany (n=8) or Canada (n=7) and evaluated physician trainings (n=25). Eleven articles met ICROMS quality criteria. Almost all studies (n=27) employed HCP-reported outcomes for training evaluation and most (n=19) additionally used patient-reported (n=12), observer-rated (n=10), standardised patient-reported (n=2) outcomes or training process and healthcare data (n=10). Most studies employed a mix of unpublished and published measures (n=17) and covered two (n=12) or three (n=10) Kirkpatrick’s levels. Identified evaluation outcomes covered all categories of the proposed framework.ConclusionsStrategies to evaluate HCP trainings in SDM varied largely. The proposed evaluation framework maybe useful to structure future evaluation studies, but international agreement on a core set of outcomes is needed to improve evidence.PROSPERO registration numberCRD42016041623.

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Knowledge is not power for patients: A systematic review and thematic synthesis of patient-reported barriers and facilitators to shared decision making

Patient Education and Counseling ◽

10.1016/j.pec.2013.10.031 ◽

2014 ◽

Vol 94 (3) ◽

pp. 291-309 ◽

Cited By ~ 443

Author(s):

Natalie Joseph-Williams ◽

Glyn Elwyn ◽

Adrian Edwards

Keyword(s):

Systematic Review ◽

Decision Making ◽

Shared Decision Making ◽

Barriers And Facilitators ◽

Shared Decision ◽

Thematic Synthesis ◽

Patient Reported

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Patient-reported outcomes in RA care improve patient communication, decision-making, satisfaction and confidence: qualitative results

Rheumatology ◽

10.1093/rheumatology/kez506 ◽

2019 ◽

Vol 59 (7) ◽

pp. 1662-1670 ◽

Cited By ~ 8

Author(s):

Susan J Bartlett ◽

Elaine De Leon ◽

Ana-Maria Orbai ◽

Uzma J Haque ◽

Rebecca L Manno ◽

...

Keyword(s):

Decision Making ◽

Focus Groups ◽

Shared Decision Making ◽

Patient Reported Outcomes ◽

Medical Decision ◽

Measurement Information ◽

Shared Decision ◽

Clinic Staff ◽

Patient Reported ◽

The Impact

Abstract Objective To evaluate the impact of integrating patient-reported outcomes (PROs) into routine clinics, from the perspective of patients with RA, clinicians and other staff. Methods We conducted a prospective cohort study using a mixed methods sequential explanatory design at an academic arthritis clinic. RA patients completed selected Patient-Reported Outcomes Measurement Information System measures on tablets in the waiting room. Results were immediately available to discuss during the visit. Post-visit surveys with patients and physicians evaluated topics discussed and their impact on decision making; patients rated confidence in treatment. Focus groups or interviews with patients, treating rheumatologists and clinic staff were conducted to understand perspectives and experiences. Results Some 196 patients and 20 rheumatologists completed post-visit surveys at 816 and 806 visits, respectively. Focus groups were conducted with 24 patients, 10 rheumatologists and 4 research/clinic staff. PROs influenced medical decision-making and RA treatment changes (38 and 18% of visits, respectively). Patients reported very high satisfaction and treatment confidence. Impact on clinical workflow was minimal after a period of initial adjustment. PROs were valued by patients and physicians, and provided new insight into how patients felt and functioned over time. Reviewing results together improved communication, and facilitated patient-centred care, shared decision making, and the identification of new symptoms and contributing psychosocial/behavioural factors. Conclusion PRO use at RA visits was feasible, increased understanding of how disease affects how patients feel and function, facilitated shared decision-making, and was associated with high patient satisfaction and treatment confidence.

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