Preventing 30-day hospital readmissions: a systematic review and meta-analysis of randomized trials

Abstract

Importance: Reducing early (<30 days) hospital readmissions is a policy priority aimed at improving health care quality. The cumulative complexity model conceptualizes patient context. It predicts that highly supportive discharge interventions will enhance patient capacity to enact burdensome self-care and avoid readmissions.

Objective: To synthesize the evidence of the efficacy of interventions to reduce early hospital readmissions and identify intervention features--including their impact on treatment burden and on patients' capacity to enact postdischarge self-care--that might explain their varying effects.

Data sources: We searched PubMed, Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, and Scopus (1990 until April 1, 2013), contacted experts, and reviewed bibliographies.

Study selection: Randomized trials that assessed the effect of interventions on all-cause or unplanned readmissions within 30 days of discharge in adult patients hospitalized for a medical or surgical cause for more than 24 hours and discharged to home.

Data extraction and synthesis: Reviewer pairs extracted trial characteristics and used an activity-based coding strategy to characterize the interventions; fidelity was confirmed with authors. Blinded to trial outcomes, reviewers noted the extent to which interventions placed additional work on patients after discharge or supported their capacity for self-care in accordance with the cumulative complexity model.

Main outcomes and measures: Relative risk of all-cause or unplanned readmission with or without out-of-hospital deaths at 30 days postdischarge.

Results: In 42 trials, the tested interventions prevented early readmissions (pooled random-effects relative risk, 0.82 [95% CI, 0.73-0.91]; P < .001; I² = 31%), a finding that was consistent across patient subgroups. Trials published before 2002 reported interventions that were 1.6 times more effective than those tested later (interaction P = .01). In exploratory subgroup analyses, interventions with many components (interaction P = .001), involving more individuals in care delivery (interaction P = .05), and supporting patient capacity for self-care (interaction P = .04) were 1.4, 1.3, and 1.3 times more effective than other interventions, respectively. A post hoc regression model showed incremental value in providing comprehensive, postdischarge support to patients and caregivers.

Conclusions and relevance: Tested interventions are effective at reducing readmissions, but more effective interventions are complex and support patient capacity for self-care. Interventions tested more recently are less effective.

Figure 1

The Cumulative Complexity Model. Patient context is represented as a balance between workload and capacity. This balance must be optimized to ensure care effectiveness and improve outcomes. In turn, the outcomes achieved feedback to affect the workload-capacity balance.

Figure 2

Summary of evidence search and selection. Note that typical papers initially set aside for author inclusion were those that did not report the outcome of interest within 30 days but reported other outcomes within this time, reported the outcome within a survival analysis graph but without information about the number of patients at risk, or reported the outcome as a component of a composite outcome.

Figure 3

Results of primary meta-analysis. RR=relative risk.