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Discharge planning from hospital to home

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Abstract

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Background

Discharge planning is a routine feature of health systems in many countries. The aim of discharge planning is to reduce hospital length of stay and unplanned readmission to hospital, and improve the co‐ordination of services following discharge from hospital.

Objectives

To determine the effectiveness of planning the discharge of patients moving from hospital.

Search methods

We updated the review using the Cochrane EPOC Group Trials Register, MEDLINE, EMBASE and the Social Science Citation Index (last searched in March 2009).

Selection criteria

Randomised controlled trials (RCTs) that compared an individualised discharge plan with routine discharge care that was not tailored to the individual patient. Participants were hospital inpatients.

Data collection and analysis

Two authors independently undertook data analysis and quality assessment using a predesigned data extraction sheet. Studies are grouped according to patient group (elderly medical patients, surgical patients and those with a mix of conditions) and by outcome.

Main results

Twenty‐one RCTs (7234 patients) are included; ten of these were identified in this update. Fourteen trials recruited patients with a medical condition (4509 patients), four recruited patients with a mix of medical and surgical conditions (2225 patients), one recruited patients from a psychiatric hospital (343 patients), one from both a psychiatric hospital and from a general hospital (97 patients), and the final trial recruited patients admitted to hospital following a fall (60 patients). Hospital length of stay and readmissions to hospital were significantly reduced for patients allocated to discharge planning (mean difference length of stay ‐0.91, 95% CI ‐1.55 to ‐0.27, 10 trials; readmission rates RR 0.85, 95% CI 0.74 to 0.97, 11 trials). For elderly patients with a medical condition (usually heart failure) there was insufficient evidence for a difference in mortality (RR 1.04, 95% CI 0.74 to 1.46, four trials) or being discharged from hospital to home (RR 1.03, 95% CI 0.93 to 1.14, two trials). This was also the case for trials recruiting patients recovering from surgery and a mix of medical and surgical conditions. In three trials patients allocated to discharge planning reported increased satisfaction. There was little evidence on overall healthcare costs.

Authors' conclusions

The evidence suggests that a structured discharge plan tailored to the individual patient probably brings about small reductions in hospital length of stay and readmission rates for older people admitted to hospital with a medical condition. The impact of discharge planning on mortality, health outcomes and cost remains uncertain.

PICOs

Population
Intervention
Comparison
Outcome

The PICO model is widely used and taught in evidence-based health care as a strategy for formulating questions and search strategies and for characterizing clinical studies or meta-analyses. PICO stands for four different potential components of a clinical question: Patient, Population or Problem; Intervention; Comparison; Outcome.

See more on using PICO in the Cochrane Handbook.

Plain language summary

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Discharge planning from hospital to home

Discharge planning is the development of an individualised discharge plan for the patient prior to leaving hospital, with the aim of containing costs and improving patient outcomes. Discharge planning should ensure that patients are discharged from hospital at an appropriate time in their care and that, with adequate notice, the provision of other services will be organised.

A review of the effects of different discharge plans was conducted. After searching for relevant studies, 21 studies were found which compared discharge plans tailored to the individual patients with routine discharge care that was not individualised.

This review indicates that a structured discharge plan tailored to the individual patient probably brings about a small reduction in hospital length of stay and readmission rates, and an increase in patient satisfaction. The impact on health outcomes is uncertain.