Quality Improvement Interventions to Prevent the Use of Hospital Services Among Nursing Home Residents: Protocol for a Systematic Review and Meta-analysis

Overview

Journal BMJ Open

Specialty General Medicine

Date 2023 Sep 27

PMID 37758680

Authors

Ines Basso

Silvia Gonella

Erika Bassi

Silvia Caristia

Sara Campagna

Alberto Dal Molin

Affiliations

Soon will be listed here.

Abstract

Introduction: Quality improvement interventions are a promising strategy for reducing hospital services use among nursing home residents. However, evidence for their effectiveness is limited. It is unclear which characteristics of the quality improvement intervention and activities planned to facilitate implementation may promote fidelity to organisational and system changes. This systematic review and meta-analysis will assess the effectiveness of quality improvement interventions and implementation strategies aimed at reducing hospital services use among nursing home residents.

Methods And Analysis: The MEDLINE, CINAHL, Cochrane Library, Embase and Web of Science databases will be comprehensively searched in September 2023. The eligible studies should focus on the implementation of a quality improvement intervention defined as the systematic, continuous approach that designs, tests and implements changes using real-time measurement to reduce hospitalisations or emergency department visits among long-stay nursing home residents. Quality improvement details and implementation strategies will be deductively categorised into effective practice and organisation of care taxonomy domains for delivery arrangements and implementation strategies. Quality and bias assessments will be completed using the Quality Improvement Minimum Quality Criteria Set and the Joanna Briggs Institute Critical Appraisal Tools.The results will be pooled in a meta-analysis, by combining the natural logarithms of the rate ratios across the studies or by calculating the rate ratio using the generic inverse-variance method. Heterogeneity will be assessed using the I or H statistics if the number of included studies will be less than 10. Raw data will be requested from the authors, as required.

Ethics And Dissemination: Ethical approval is not required. The results will be published in a peer-review journal and presented at (inter)national conferences.

Prospero Registration Number: CRD42022364195.

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