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Protocol for the health economic evaluation of increasing the weekend specialist to patient ratio in hospitals in England

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Watson, Samuel I., Chen, Y-F.‏‎, Bion, Julian F, Aldridge, Cassie P., Girling, Alan and Lilford, Richard (2018) Protocol for the health economic evaluation of increasing the weekend specialist to patient ratio in hospitals in England. BMJ Open, 8 (2). e015561. doi:10.1136/bmjopen-2016-015561 ISSN 2044-6055.

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Official URL: http://dx.doi.org/10.1136/bmjopen-2016-015561

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Abstract

Introduction: This protocol concerns the evaluation of increased specialist staffing at weekends in hospitals in England. Seven-day health services are a key policy for the UK government and other health systems trying to improve use of infrastructure and resources. A particular motivation for the 7-day policy has been the observed increase in the risk of death associated with weekend admission, which has been attributed to fewer hospital specialists being available at weekends. However, the causes of the weekend effect have not been adequately characterised; many of the excess deaths associated with the ‘weekend effect’ may not be preventable, and the presumed benefits of improved specialist cover might be offset by the cost of implementation.

Methods/design: The Bayesian-founded method we propose will consist of four major steps. First, the development of a qualitative causal model. Specialist presence can affect multiple, interacting causal processes. One or more models will be developed from the results of an expert elicitation workshop and probabilities elicited for each model and relevant model parameters. Second, systematic review of the literature. The model from the first step will provide search limits for a review to identify relevant studies. Third, a statistical model for the effects of specialist presence on care quality and patient outcomes. Fourth, valuation of outcomes. The expected net benefits of different levels of specialist intensity will then be evaluated with respect to the posterior distributions of the parameters.

Item Type: Journal Article
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences
Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences > Population, Evidence & Technologies (PET)
Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH): Hospital care -- Great Britain, Medical personnel -- Supply and demand -- Great Britain, Medicine -- Specialties and specialists -- Great Britain, Bayesian statistical decision theory
Journal or Publication Title: BMJ Open
Publisher: BMJ
ISSN: 2044-6055
Official Date: 23 February 2018
Dates:
DateEvent
23 February 2018Published
27 November 2017Accepted
20 April 2017Submitted
Volume: 8
Number: 2
Article Number: e015561
DOI: 10.1136/bmjopen-2016-015561
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 19 March 2018
Date of first compliant Open Access: 20 March 2018
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
Health Services and Delivery Research Grant: 12/128/17National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
Collaboration for Leadership in Applied Health Research and CareNational Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
Open Access Version:
  • Publisher
Contributors:
ContributionNameContributor ID
Research GroupHiSLAC Collaboration, UNSPECIFIED

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