Shared Decision-Making in Cardiovascular Risk Factor Management: A Systematic Review and Meta-Analysis

Abstract

Importance: The effect of shared decision-making (SDM) and the extent of its use in interventions to improve cardiovascular risk remain unclear.

Objective: To assess the extent to which SDM is used in interventions aimed to enhance the management of cardiovascular risk factors and to explore the association of SDM with decisional outcomes, cardiovascular risk factors, and health behaviors.

Data sources: For this systematic review and meta-analysis, a literature search was conducted in the Medline, CINAHL, Embase, Cochrane, Web of Science, Scopus, and ClinicalTrials.gov databases for articles published from inception to June 24, 2022, without language restrictions.

Study selection: Randomized clinical trials (RCTs) comparing SDM-based interventions with standard of care for cardiovascular risk factor management were included.

Data extraction and synthesis: The systematic search resulted in 9365 references. Duplicates were removed, and 2 independent reviewers screened the trials (title, abstract, and full text) and extracted data. Data were pooled using a random-effects model. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline.

Main outcomes and measures: Decisional outcomes, cardiovascular risk factor outcomes, and health behavioral outcomes.

Results: This review included 57 RCTs with 88 578 patients and 1341 clinicians. A total of 59 articles were included, as 2 RCTs were reported twice. Nearly half of the studies (29 [49.2%]) tested interventions that targeted both patients and clinicians, and an equal number (29 [49.2%]) exclusively focused on patients. More than half (32 [54.2%]) focused on diabetes management, and one-quarter focused on multiple cardiovascular risk factors (14 [23.7%]). Most studies (35 [59.3%]) assessed cardiovascular risk factors and health behaviors as well as decisional outcomes. The quality of studies reviewed was low to fair. The SDM intervention was associated with a decrease of 4.21 points (95% CI, -8.21 to -0.21) in Decisional Conflict Scale scores (9 trials; I2 = 85.6%) and a decrease of 0.20% (95% CI, -0.39% to -0.01%) in hemoglobin A1c (HbA1c) levels (18 trials; I2 = 84.2%).

Conclusions and relevance: In this systematic review and meta-analysis of the current state of research on SDM interventions for cardiovascular risk management, there was a slight reduction in decisional conflict and an improvement in HbA1c levels with substantial heterogeneity. High-quality studies are needed to inform the use of SDM to improve cardiovascular risk management.

Figure 1.. Study Flow Diagram

CINAHL indicates Cumulative Index of Nursing and Allied Health Literature; CVD, cardiovascular disease; SDM, shared decision-making; and RCT, randomized clinical trial.

Figure 2.. Forest Plot of Mean Differences in Decisional Conflict Between the Shared Decision-Making (SDM)–Based Intervention Group and the Control Group

Results of the random-effects Hedges model are presented. The means (SDs) are the outcomes measured at the follow-up time points to perform meta-analyses. The size of the squares is proportional to the weight of each study. Horizontal lines indicate the 95% CI of each study, diamonds are the pooled estimate with 95% CI (weight, 100%), and the vertical dotted line is the line of no effect. Heterogeneity was assessed using the Cochran Q test (H²) and the Higgins I² statistic. Interpretation of I² values followed Cochrane guidelines (0% to 40%, might not be important; 30% to 60%, may represent moderate heterogeneity; 50% to 90%, may represent substantial heterogeneity; and 75% to 100%, considerable heterogeneity).