Visualising linked health data to explore health events around preventable hospitalisations in NSW Australia

Falster, M. O., Jorm, L. R. and Leyland, A. H. (2016) Visualising linked health data to explore health events around preventable hospitalisations in NSW Australia. BMJ Open, 6(9), e012031. (doi:10.1136/bmjopen-2016-012031) (PMID:27604087) (PMCID:PMC5020859)

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Abstract

Objective: To explore patterns of health service use in the lead-up to, and following, admission for a ‘preventable’ hospitalisation. Setting: 266 950 participants in the 45 and Up Study, New South Wales (NSW) Australia Methods: Linked data on hospital admissions, general practitioner (GP) visits and other health events were used to create visual representations of health service use. For each participant, health events were plotted against time, with different events juxtaposed using different markers and panels of data. Various visualisations were explored by patient characteristics, and compared with a cohort of non-admitted participants matched on sociodemographic and health characteristics. Health events were displayed over calendar year and in the 90 days surrounding first preventable hospitalisation. Results: The visualisations revealed patterns of clustering of GP consultations in the lead-up to, and following, preventable hospitalisation, with 14% of patients having a consultation on the day of admission and 27% in the prior week. There was a clustering of deaths and other hospitalisations following discharge, particularly for patients with a long length of stay, suggesting patients may have been in a state of health deterioration. Specialist consultations were primarily clustered during the period of hospitalisation. Rates of all health events were higher in patients admitted for a preventable hospitalisation than the matched non-admitted cohort. Conclusions: We did not find evidence of limited use of primary care services in the lead-up to a preventable hospitalisation, rather people with preventable hospitalisations tended to have high levels of engagement with multiple elements of the healthcare system. As such, preventable hospitalisations might be better used as a tool for identifying sicker patients for managed care programmes. Visualising longitudinal health data was found to be a powerful strategy for uncovering patterns of health service use, and such visualisations have potential to be more widely adopted in health services research.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Leyland, Professor Alastair
Authors: Falster, M. O., Jorm, L. R., and Leyland, A. H.
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:2044-6055
ISSN (Online):2044-6055
Published Online:07 September 2016
Copyright Holders:Copyright © 2016 The Authors
First Published:First published in BMJ Open 6(9):e012031
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