Evidence map›Paper›PMID 39392535›Full record

ArticleHealth economics review2024

Waiting times spillovers in a National Health Service hospital network: a little organizational diversity can go a long way.

Joana Daniela Ferreira Cima, Alvaro Fernando Santos Almeida

Abstract read
In one paragraph

Article in Health economics review, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

2 authors.

Joana Daniela Ferreira CimaDepartment of Economics/NIPE, Escola de Economia e Gestão, Universidade do Minho, Campus de Gualtar, 4710-057, Braga, Portugal. joana.cima@eeg.uminho.pt.ORCID http://orcid.org/0000-0002-2780-7467
Alvaro Fernando Santos AlmeidaFaculdade de Economia, Universidade do Porto, cef.up Center for Economics and Finance at UPorto, Porto, Portugal.ORCID http://orcid.org/0000-0002-3604-0931

Funding

Fundação para a Ciência e a Tecnologia Project "UIDB/03182/2020"Fundação para a Ciência e a Tecnologia Project "UIDB/04105/2020"
6 · The paper itself

Abstract

backgroundThe objective of this study is to assess if waiting times for elective surgeries within the Portuguese National Health Service (NHS) are influenced by the waiting times at neighboring hospitals. Recognizing these interdependencies, and their extent, is crucial for understanding how hospital network dynamics affect healthcare delivery efficiency and patient access.

methodsWe utilized patient-level data from all elective surgeries conducted in Portuguese NHS hospitals to estimate a hospital-specific index for waiting times. This index served as the dependent variable in our analysis. We applied a spatial lag model to examine the potential strategic interactions between hospitals concerning their waiting times.

resultsOur analysis revealed a significant positive endogenous spatial dependence, indicating that waiting times in NHS hospitals are strategic complements. Furthermore, we found that NHS contracts with private not-for-profit hospitals not only reduce waiting times within these hospitals but also exert positive spillover effects on other NHS hospitals.

conclusionsThe findings suggest that diversifying the organization of the NHS hospital network, particularly through contracts with private entities for marginal patients, can significantly enhance competitive dynamics and reduce waiting times. This effect persists even when patient choice is confined to a small fraction of the patient population, highlighting a strategic avenue for policy optimization in healthcare service delivery.

Indexed as

Hospital competitionMixed marketsNot-for-profit hospitalsWaiting times

Identifiers

PMID39392535
PMCPMC11468064

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.