Health system influences on potentially avoidable hospital admissions by secondary mental health service use: A national ecological study

Author:

Woodhead Charlotte1ORCID,Martin Peter2,Osborn David3,Barratt Helen4,Raine Rosalind5

Affiliation:

1. Lecturer Society and Mental Health, ESRC Centre for Society and Mental Health, Department of Psychological Medicine, King’s College London, UK

2. Lecturer Applied Statistics, NIHR ARC North Thames, Department of Applied Health Research, University College London, UK

3. Professor of Psychiatric Epidemiology, Department of Epidemiology and Applied Clinical Research, Division of Psychiatry, University College London and Camden and Islington NHS Foundation Trust, UK

4. Senior Clinical Research Associate, NIHR ARC North Thames, Department of Applied Health Research, University College London, UK

5. Professor of Health Care Evaluation, NIHR ARC North Thames, Department of Applied Health Research, University College London, UK

Abstract

Objectives Potentially avoidable hospital admissions (PAAs) are costly to health services and potentially harmful for patients. This study aimed to compare area-level PAA rates among people using and not using secondary mental health services in England and to identify health system features that may influence between-area PAA variation. Methods National ecological study using linked English hospital admissions and secondary mental health services data (2016–2018). We calculated two-year average age-sex standardised area-level PAA rates according to primary admission diagnoses for 12 physical conditions, among, first, secondary mental health service users with any non-organic diagnosis, and, second, people not in contact with secondary mental health services. We used penalised regression analyses to identify predictors of area-level variation in PAA rates. Results Area-level PAA rates were over four times greater in the mental health group, at 7,594 per 100,000 population compared to 1,819 per 100,000 in the comparator group. Common predictors of variation were greater density of older age groups (lower PAA rates), higher underlying population morbidity of chronic obstructive pulmonary disease and, to a lesser extent, urbanity (higher PAA rates). For both groups, health system factors such as the number of general practitioners per capita or ambulance despatch rates were significant but weak predictors of variation. Mental health diagnosis data were available for half of secondary mental health care records only and sensitivity analyses found that urbanity remained the sole significant predictor for PAAs in this group. Conclusions Findings support the need for improved management of physical conditions for secondary mental health service users. Understanding and predicting variation in PAAs among mental health service users is constrained by availability of data on mental health diagnosis, physical health care and needs.

Publisher

SAGE Publications

Subject

Public Health, Environmental and Occupational Health,Health Policy

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