Protocol for an overview of systematic reviews of interventions to reduce unscheduled hospital admissions among adults

INTRODUCTION: Unscheduled hospital admissions are an increasing burden on health systems worldwide. To date, initiatives to reduce admissions have had limited success as it is unclear which strategies effectively reduce admissions and are supported by a strong evidence-base. Therefore, we will conduct an overview to find, assess and summarise all published peer-reviewed systematic reviews of randomised controlled trials that examine the effect of an intervention on unplanned admissions among adults. METHODS AND ANALYSIS: This is a protocol for a systematic overview of reviews. We will search four databases: Ovid MEDLINE, PubMed, Cochrane Database of Systematic Reviews and the Cochrane Database of Abstracts of Reviews of Effects. We will consider systematic reviews and meta-analyses of randomised controlled trials in adults (≥16 years old) evaluating the effect of any intervention on unscheduled hospital admissions including those to treat, monitor, diagnose or prevent a health problem. We will only include reviews that identified unscheduled hospitalisations as a prespecified outcome. Two authors will independently screen articles for inclusion using a priori criteria. We will assess the quality of included reviews and extract ratings of the quality of evidence from within each review. We will create a hierarchical list of interventions based on estimates of absolute admission reductions and the quality of the evidence. Presentation of results will align with guidelines in the Cochrane Handbook of Systematic Reviews of Interventions and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement. ETHICS AND DISSEMINATION: Ethics approval is not required. We will submit the results of this study for peer-review publication. The results will inform future research and could be used by healthcare managers, administrators and policymakers to guide resource allocation decisions and inform local implementation and optimisation of interventions to reduce unscheduled hospital admissions.