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Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis
journal contribution
posted on 2023-06-09, 12:18 authored by Evangelos Kontopantelis, Mamas A Mamas, Harm van MarwijkHarm van Marwijk, Andrew M Ryan, Peter Bower, Bruce Guthrie, Tim DoranBackground 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.
History
Publication status
- Published
File Version
- Published version
Journal
BMC MedicineISSN
1741-7015Publisher
BioMed CentralExternal DOI
Issue
1Volume
16Page range
1-13Article number
a19Department affiliated with
- Primary Care and Public Health Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2018-02-21First Open Access (FOA) Date
2018-02-21First Compliant Deposit (FCD) Date
2018-02-21Usage metrics
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