Evidence map›Paper›PMID 39511606›Full record

ArticleBMC health services research2024

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

Luís Filipe, Roberta Piroddi, Wes Baker, Joe Rafferty, Iain Buchan, Ben Barr

Abstract read
In one paragraph

Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Improving Primary Healthcare: Applying Grapevine (Healthcare (Basel, Switzerland) · 2026
    Article
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Luís FilipeDepartment of Health Research, Lancaster University, Lancaster, UK. l.filipe@lancaster.ac.uk.
Roberta PiroddiDepartment of Public Health, Policy, and Systems, Institute of Population Health, University of Liverpool, Liverpool, UK.
Wes BakerMersey Care NHS Foundation Trust, Prescot, UK.
Joe RaffertyMersey Care NHS Foundation Trust, Prescot, UK.
Iain BuchanDepartment of Public Health, Policy, and Systems, Institute of Population Health, University of Liverpool, Liverpool, UK.
Ben BarrDepartment of Public Health, Policy, and Systems, Institute of Population Health, University of Liverpool, Liverpool, UK.

Funding

National Institute for Health and Care Research MHF106National Institute for Health and Care Research NIHR205131National Institute for Health and Care Research Policy Research Programme NIHR202484
6 · The paper itself

Abstract

backgroundAllocating 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.

methodsUsing 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.

resultsKey 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.

conclusionA 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.

Indexed as

Resource AllocationAdolescentAdultAgedCommunity Health NursingEnglandFemaleHealth Care RationingHealth Services Needs and DemandHumansMaleMiddle AgedNeeds AssessmentPersonnel Staffing and SchedulingResidence CharacteristicsState MedicineCommunity health servicesDistrict nursingInequalitiesNeighbourhood-level modelResource allocationUnmet needsUtilization formula

Identifiers

PMID39511606
PMCPMC11545996

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.