Kontopantelis, E, Mamas, MA ORCID: https://orcid.org/0000-0001-9241-8890, van Marwijk, H, Ryan, A, Bower, P, Guthrie, B and Doran, T (2018) Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis. BMC Medicine, 16 (19).

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Abstract

Background
Primary care provides the foundation for most modern health-care systems, and in the interests of equity, it should be resourced according to local need. We aimed to describe spatially the burden of chronic conditions and primary medical care funding in England at a low geographical level, and to measure how much variation in funding is explained by chronic condition prevalence and other patient and regional factors.

Methods
We used multiple administrative data sets including chronic condition prevalence and management data (2014/15), funding for primary-care practices (2015-16), and geographical and area deprivation data (2015). Data were assigned to a low geographical level (average 1500 residents). We investigated the overall morbidity burden across 19 chronic conditions and its regional variation, spatial clustering and association with funding and area deprivation. A linear regression model was used to explain local variation in spending using patient demographics, morbidity, deprivation and regional characteristics.

Results
Levels of morbidity varied within and between regions, with several clusters of very high morbidity identified. At the regional level, morbidity was modestly associated with practice funding, with the North East and North West appearing underfunded. The regression model explained 39% of the variability in practice funding, but even after adjusting for covariates, a large amount of variability in funding existed across regions. High morbidity and, especially, rural location were very strongly associated with higher practice funding, while associations were more modest for high deprivation and older age.

Conclusions
Primary care funding in England does not adequately reflect the contemporary morbidity burden. More equitable resource allocation could be achieved by making better use of routinely available information and big data resources. Similar methods could be deployed in other countries where comparable data are collected, to identify morbidity clusters and to target funding to areas of greater need.

Item Type: Article
Additional Information: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Uncontrolled Keywords: Primary care funding; Chronic conditions; Morbidity; Deprivation; Spatial clustering; Quality and Outcomes framework; QOF; England; UK; Carr Hill formula; Global sum allocation formula
Subjects: R Medicine > R Medicine (General)
R Medicine > RC Internal medicine > RC666 Diseases of the circulatory (Cardiovascular) system
Divisions: Faculty of Medicine and Health Sciences > Institute for Applied Clinical Sciences
Depositing User: Symplectic
Date Deposited: 19 Feb 2018 11:54
Last Modified: 08 Mar 2019 14:05
URI: http://eprints.keele.ac.uk/id/eprint/4480

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