Self-Care Interventions Meta-Analysis—Heart Failure (SCIMA-HF)

Research Team

Todd Ruppar, Principal Investigator, Rush CON

Vicki Conn, Co-Investigator, University of Missouri

Barbara Riegel, Co-Investigator, University of Pennsylvania

Award Period

07/01/17 – 06/30/19

Funding Source

American Heart Association (AHA) Grant-in-Aid


Heart failure (HF) is associated with high morbidity, mortality, hospitalization rates, and costs, along with impaired function and quality of life. Better HF self-care practices are linked with improved patient outcomes, but research has not established the comparative effectiveness of existing interventions to enhance HF self-care. The specific aims of this project are to 1) investigate the impact of interventions to enhance HF self-care on behavioral and clinical outcomes, and 2) distinguish factors that moderate effects of HF self-care interventions on outcomes. In achieving these aims, we will determine the overall effectiveness of HF self-care interventions on key behavioral, clinical, and patient-centered outcomes, and also quantify the comparative effectiveness of different intervention components—the key information needed to advance the science of HF self-care to develop more effective intervention programs and provide empirical evidence for current self-care practice recommendations. Meta-analysis is a recognized method for quantitatively synthesizing study outcomes across a body of related literature. We will use systematic, exhaustive search methods to identify intervention studies designed to improve HF self-care, and then code these studies with a high degree of reliability, specificity, and detail. The planned data analysis includes calculation of standardized effect sizes for each study, weighting effect sizes by (statistical) precision, and random-effects model meta-analyses. The analysis also includes assessments for study homogeneity (Q and I2) and publication bias. Where possible, results will be converted to original metrics to facilitate interpretation and applicability to future research and clinical practice. Risk of bias will be assessed and tested for potential effects on effect size estimates. Moderator analyses using meta-regression and ANOVA will evaluate efficacy based on intervention components and sample characteristics.

Findings from these meta-analyses will have an immediate effect on research and clinical practice by identifying intervention characteristics associated with the best behavioral and clinical outcomes. These comparative-effectiveness results will enable health care professionals to design more effective HF self-care intervention programs to improve health outcomes, reduce disparities, and move toward achieving Healthy People 2020 goals of improving cardiovascular health and preventing cardiovascular events.