Replication Study: Evaluating a Structured Discharge Protocol on 30-Day Readmission Rates for Heart Failure Patients in an East African Tertiary Hospital, 2013

Heart failure is a leading cause of hospitalisation and readmission in sub-Saharan Africa, imposing a substantial burden on health systems. Previous research in another setting indicated that a structured discharge protocol could reduce 30-day readmission rates. This study replicated that investigation within a busy East African tertiary hospital context. The purpose was to replicate an evaluation of a structured discharge planning protocol for heart failure patients. The objective was to determine its effect on 30-day hospital readmission rates at Kenyatta National Hospital. A quasi-experimental replication study was conducted. A cohort of adult heart failure patients was enrolled. The intervention group received a multi-component discharge protocol comprising patient education, medication reconciliation, scheduled follow-up, and post-discharge telephone support. The comparison group received standard care. The primary outcome was readmission for heart failure within 30 days of discharge. The structured discharge protocol was associated with a reduction in 30-day readmissions. The readmission rate was 12% in the intervention group, compared to 22% in the standard care group. This replication supports the original findings, indicating that a structured discharge protocol can be effective in reducing early readmissions for heart failure patients in an East African tertiary hospital setting. Hospitals in similar resource-constrained settings should consider adopting and adapting structured discharge protocols for heart failure management. Future research should examine long-term sustainability and cost-effectiveness. heart failure, patient discharge, patient readmission, replication study, sub-Saharan Africa, quality improvement This study provides replicated evidence for a clinical intervention in a context where original research is often limited, offering locally relevant data to inform policy and practice.