Improving equitable healthcare resource use: Developing a neighbourhood district nurse needs index for staffing allocation

Author:

Filipe Luís1,Piroddi Roberta2,Baker Wes3,Rafferty Joe3,Buchan Iain2,Barr Ben2

Affiliation:

1. Lancaster University

2. University of Liverpool

3. Mersey Care NHS Foundation Trust

Abstract

Abstract

Background Allocating health care 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 approach 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.

Publisher

Research Square Platform LLC

Reference31 articles.

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3. Office for National Statistics. Annual mid-year population estimates for Clinical Commissioning Groups. 2022. https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/bulletins/annualsmallareapopulationestimates/2013-08-15 (accessed Aug 4, 2022).

4. Chaplin M, Beatson S, Lau Y-S et al. For allocations to Clinical Commissioning Groups from 2016-17 Report on the methods and modelling. 2016;: 167.

5. A person based formula for allocating commissioning funds to general practices in England: development of a statistical model;Dixon J;BMJ,2011

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