Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis.
Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis.
复制标题
DOI：
10.1186/s12916-017-0996-0
复制
发表时间：
2018-02-14
期刊：
影响因子：
9.3
通讯作者：
Doran T
中科院分区：
文献类型：
--
作者：
Kontopantelis E;Mamas MA;van Marwijk H;Ryan AM;Bower P;Guthrie B;Doran T
初级保健是大多数现代卫生保健系统的基础，为了公平起见，应根据当地需要为其提供资源。我们的目的是在低地理水平上描述英格兰慢性疾病和初级医疗保健资金的空间负担，并衡量资金的变化有多大程度上是由慢性疾病患病率和其他患者和区域因素解释的。我们使用了多个行政数据集，包括慢性病患病率和管理数据（2014/15）、初级保健实践资金（2015-16）以及地理和地区贫困数据（2015）。数据分配到较低的地理水平（平均1500名居民）。我们调查了19种慢性病的总体发病率负担及其区域差异、空间聚类以及与资金和地区匮乏的关系。使用线性回归模型来解释使用患者人口统计学，发病率，剥夺和区域特征的地方差异。发病率在区域内和区域之间各不相同，有几个发病率非常高的群集。在区域一级，发病率与实践资金适度相关，东北和西北地区出现资金不足。回归模型解释了39%的实践资助变异性，但即使在调整协变量后，区域间的资助变异性仍然很大。高发病率，特别是农村地区，与较高的实践资金密切相关，而与高贫困和年龄较大的相关性较弱。英格兰的初级保健资金不能充分反映当代发病率负担。通过更好地利用常规信息和大数据资源，可以实现更公平的资源分配。在其他收集了可比数据的国家也可以采用类似的方法，以确定发病率群集，并将资金定向到更需要的领域。本文的在线版本（10.1186/s12916-017-0996-0）包含补充材料，可供授权用户使用。
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. 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. 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. 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. The online version of this article (10.1186/s12916-017-0996-0) contains supplementary material, which is available to authorized users.
登录
查看更多内容
影响因子：
2.1
作者：
Soljak M;Samarasundera E;Indulkar T;Walford H;Majeed A
通讯作者：
Majeed A
影响因子：
6.3
作者：
Asaria, Miqdad;Ali, Shehzad;Cookson, Richard
通讯作者：
Cookson, Richard
DOI：
10.1136/bmj.h904
发表时间：
2015-03-02
期刊：
BMJ (Clinical research ed.)
影响因子：
--
作者：
Kontopantelis E;Springate DA;Ashworth M;Webb RT;Buchan IE;Doran T
通讯作者：
Doran T
影响因子：
105.7
作者：
Ashworth, Mark;Medina, Jibby;Morgan, Myfanwy
通讯作者：
Morgan, Myfanwy
影响因子：
6.3
作者：
Buchan, Iain E.;Kontopantelis, Evangelos;Doran, Tim
通讯作者：
Doran, Tim