Do hospitals influence geographic variation in admission for preventable hospitalisation? A data linkage study in New South Wales, Australia

Falster, M. O., Leyland, A. H. and Jorm, L. R. (2019) Do hospitals influence geographic variation in admission for preventable hospitalisation? A data linkage study in New South Wales, Australia. BMJ Open, 9(2), e027639. (doi:10.1136/bmjopen-2018-027639) (PMID:30798320) (PMCID:PMC6398792)

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Objective: Preventable hospitalisations are used internationally as a performance indicator for primary care, but the influence of other health system factors remains poorly understood. This study investigated between-hospital variation in rates of preventable hospitalisation. Setting: Linked health survey and hospital admissions data for a cohort study of 266 826 people aged over 45 years in the state of New South Wales, Australia. Method: Between-hospital variation in preventable hospitalisation was quantified using cross-classified multiple-membership multilevel Poisson models, adjusted for personal sociodemographic, health and area-level contextual characteristics. Variation was also explored for two conditions unlikely to be influenced by discretionary admission practice: emergency admissions for acute myocardial infarction (AMI) and hip fracture. Results: We found significant between-hospital variation in adjusted rates of preventable hospitalisation, with hospitals varying on average 26% from the state mean. Patients served more by community and multipurpose facilities (smaller facilities primarily in rural areas) had higher rates of preventable hospitalisation. Community hospitals had the greatest between-hospital variation, and included the facilities with the highest rates of preventable hospitalisation. There was comparatively little between-hospital variation in rates of admission for AMI and hip fracture. Conclusions: Geographic variation in preventable hospitalisation is determined in part by hospitals, reflecting different roles played by community and multipurpose facilities, compared with major and principal referral hospitals, within the community. Care should be taken when interpreting the indicator simply as a performance measure for primary care.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Leyland, Professor Alastair
Authors: Falster, M. O., Leyland, A. H., and Jorm, L. R.
College/School:College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > MRC/CSO SPHSU
Journal Name:BMJ Open
Publisher:BMJ Publishing Group
ISSN (Online):2044-6055
Published Online:22 February 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in BMJ Open 9(2): e027639
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
727651SPHSU Core Renewal: Measuring and Analysing Socioeconomic Inequalities in Health Research ProgrammeAlastair LeylandMedical Research Council (MRC)MC_UU_12017/13IHW - MRC/CSO SPHU