Luís Filipe, Roberta Piroddi, Wes Baker, Joe Rafferty, Iain Buchan, Ben Barr
{"title":"改善医疗资源的公平使用:为人员配置制定邻里地区护士需求指数。","authors":"Luís Filipe, Roberta Piroddi, Wes Baker, Joe Rafferty, Iain Buchan, Ben Barr","doi":"10.1186/s12913-024-11832-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Allocating healthcare resources to local areas in proportion to need is an important element of many universal health care systems, aiming to provide equal access for equal need. The UK National Health Service allocates resources to relatively large areas in proportion to need, using needs-weighted capitation formulae. However, within those planning areas, local providers and commissioners also require robust methods for allocating resources to neighbourhoods in proportion to need to ensure equitable access. We therefore developed a local resource allocation formula for NHS district nursing services for a City in the North West of England, demonstrating a novel application of the national formulae principles for equitable resource allocation to small areas.</p><p><strong>Methods: </strong>Using linked data from community health services, primary care, secondary care and social care, we used a zero-inflated Poisson regression to model the number of district nursing services contacts for each individual based on predictors of need, while including the supply of district nurses per head to account for historical supply induced patterns. Individual need was estimated based on the predictions from this model, keeping supply fixed at the average. We then compared the distribution of district nurses between neighbourhoods, based on our formula, to the current service staffing distribution.</p><p><strong>Results: </strong>Key predictors of need for district nursing services were age, deprivation, chronic diseases such as, cardiovascular disease, chronic liver disease, neurological disease, mental ill health, learning disability living in a nursing home, living alone, and receiving palliative care. Need for district nursing services was highly weighted towards older and more deprived populations. The current distribution of staff was, however, more correlated with age than deprivation. Moving to a needs-based staffing distribution would shift staff from less deprived areas to more deprived areas potentially reducing inequalities.</p><p><strong>Conclusion: </strong>A neighbourhood-level model for needs for district nursing is a useful tool that can potentially improve the allocation of resources, addressing unmet need and inequalities.</p>","PeriodicalId":9012,"journal":{"name":"BMC Health Services Research","volume":"24 1","pages":"1362"},"PeriodicalIF":2.7000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545996/pdf/","citationCount":"0","resultStr":"{\"title\":\"Improving equitable healthcare resource use: developing a neighbourhood district nurse needs index for staffing allocation.\",\"authors\":\"Luís Filipe, Roberta Piroddi, Wes Baker, Joe Rafferty, Iain Buchan, Ben Barr\",\"doi\":\"10.1186/s12913-024-11832-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Allocating healthcare resources to local areas in proportion to need is an important element of many universal health care systems, aiming to provide equal access for equal need. The UK National Health Service allocates resources to relatively large areas in proportion to need, using needs-weighted capitation formulae. However, within those planning areas, local providers and commissioners also require robust methods for allocating resources to neighbourhoods in proportion to need to ensure equitable access. We therefore developed a local resource allocation formula for NHS district nursing services for a City in the North West of England, demonstrating a novel application of the national formulae principles for equitable resource allocation to small areas.</p><p><strong>Methods: </strong>Using linked data from community health services, primary care, secondary care and social care, we used a zero-inflated Poisson regression to model the number of district nursing services contacts for each individual based on predictors of need, while including the supply of district nurses per head to account for historical supply induced patterns. Individual need was estimated based on the predictions from this model, keeping supply fixed at the average. We then compared the distribution of district nurses between neighbourhoods, based on our formula, to the current service staffing distribution.</p><p><strong>Results: </strong>Key predictors of need for district nursing services were age, deprivation, chronic diseases such as, cardiovascular disease, chronic liver disease, neurological disease, mental ill health, learning disability living in a nursing home, living alone, and receiving palliative care. Need for district nursing services was highly weighted towards older and more deprived populations. The current distribution of staff was, however, more correlated with age than deprivation. Moving to a needs-based staffing distribution would shift staff from less deprived areas to more deprived areas potentially reducing inequalities.</p><p><strong>Conclusion: </strong>A neighbourhood-level model for needs for district nursing is a useful tool that can potentially improve the allocation of resources, addressing unmet need and inequalities.</p>\",\"PeriodicalId\":9012,\"journal\":{\"name\":\"BMC Health Services Research\",\"volume\":\"24 1\",\"pages\":\"1362\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545996/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Health Services Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12913-024-11832-0\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Health Services Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12913-024-11832-0","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Improving equitable healthcare resource use: developing a neighbourhood district nurse needs index for staffing allocation.
Background: Allocating healthcare resources to local areas in proportion to need is an important element of many universal health care systems, aiming to provide equal access for equal need. The UK National Health Service allocates resources to relatively large areas in proportion to need, using needs-weighted capitation formulae. However, within those planning areas, local providers and commissioners also require robust methods for allocating resources to neighbourhoods in proportion to need to ensure equitable access. We therefore developed a local resource allocation formula for NHS district nursing services for a City in the North West of England, demonstrating a novel application of the national formulae principles for equitable resource allocation to small areas.
Methods: Using linked data from community health services, primary care, secondary care and social care, we used a zero-inflated Poisson regression to model the number of district nursing services contacts for each individual based on predictors of need, while including the supply of district nurses per head to account for historical supply induced patterns. Individual need was estimated based on the predictions from this model, keeping supply fixed at the average. We then compared the distribution of district nurses between neighbourhoods, based on our formula, to the current service staffing distribution.
Results: Key predictors of need for district nursing services were age, deprivation, chronic diseases such as, cardiovascular disease, chronic liver disease, neurological disease, mental ill health, learning disability living in a nursing home, living alone, and receiving palliative care. Need for district nursing services was highly weighted towards older and more deprived populations. The current distribution of staff was, however, more correlated with age than deprivation. Moving to a needs-based staffing distribution would shift staff from less deprived areas to more deprived areas potentially reducing inequalities.
Conclusion: A neighbourhood-level model for needs for district nursing is a useful tool that can potentially improve the allocation of resources, addressing unmet need and inequalities.
期刊介绍:
BMC Health Services Research is an open access, peer-reviewed journal that considers articles on all aspects of health services research, including delivery of care, management of health services, assessment of healthcare needs, measurement of outcomes, allocation of healthcare resources, evaluation of different health markets and health services organizations, international comparative analysis of health systems, health economics and the impact of health policies and regulations.