Resource allocation modelling for home-based health and social care services in areas having differential population density levels : A case study in Northern Ireland

Hindle, Tony and Hindle, Adam and Spollen, Martin (2000) Resource allocation modelling for home-based health and social care services in areas having differential population density levels : A case study in Northern Ireland. Health Services Management Research, 13 (3). pp. 164-169. ISSN 0951-4848

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Abstract

This project arose from deliberations within the Department of Health and Social Services (DHSS) in Northern Ireland concerning the acceptability of the revenue resource allocation methodology they were using. One problem with the method being used had been the absence of a component that adequately reflected the relative costs associated with the differential population densities of the four health boards into which the Province is divided. This study investigates a particular element of this issue, viz differences in the travelling distances and times of those health and social service professionals who provide visiting services to patients in their own homes. A modelling approach has been developed and used in conjunction with a comprehensive spatial and geographical information system for Northern Ireland. An important outcome of the study has been estimates of the targets that should be set for the annual health and social care travelling distances and times per head of population in the boards, for a range of home-based services. Also, the project has contributed to decisions made by the DHSS in Northern Ireland concerning the annual financial compensations required by boards for costs associated with their relative population densities.

Item Type:
Journal Article
Journal or Publication Title:
Health Services Management Research
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2700/2719
Subjects:
?? health policy ??
ID Code:
210042
Deposited By:
Deposited On:
14 Nov 2023 10:55
Refereed?:
Yes
Published?:
Published
Last Modified:
20 Nov 2024 01:55