Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis
| Autor: | Peter Bower, Andrew M. Ryan, Tim Doran, Evangelos Kontopantelis, Bruce Guthrie, Mamas A. Mamas, Harm W.J. van Marwijk |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Male
Chronic condition Chronic conditions Deprivation lcsh:Medicine 030204 cardiovascular system & hematology Medical care History 21st Century Primary care funding Quality and Outcomes Framework global sum allocation formula 03 medical and health sciences 0302 clinical medicine Environmental health Area deprivation Medicine Humans 030212 general & internal medicine UK QOF Carr–Hill formula Aged Primary Health Care primary care funding Carr-Hill formula business.industry Quality and Outcomes Framework (QOF) lcsh:R 1. No poverty Equity (finance) Regression analysis General Medicine Global sum allocation formula RC666 chronic conditions Spatial clustering R1 3. Good health Cross-Sectional Studies Regional variation England Chronic Disease Female Morbidity business Delivery of Health Care Research Article |
| Zdroj: | Kontopantelis, E, Mamas, M, Van Marwijk, H, Ryan, A M, Bower, P, Guthrie, B & Doran, T 2018, ' Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis ', BMC Medicine, vol. 16, no. 1, 19 . https://doi.org/10.1186/s12916-017-0996-0 BMC Medicine, Vol 16, Iss 1, Pp 1-13 (2018) BMC Medicine |
| ISSN: | 1741-7015 |
| DOI: | 10.1186/s12916-017-0996-0 |
| Popis: | 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. Electronic supplementary material The online version of this article (10.1186/s12916-017-0996-0) contains supplementary material, which is available to authorized users. |
| Databáze: | OpenAIRE |
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