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Evaluating the safety and patient impacts of an artificial intelligence command centre in acute hospital care: a mixed-methods protocol

Yes / This paper presents a mixed-methods study protocol that will be used to evaluate a recent implementation of a real-time, centralised hospital command centre in the UK. The command centre represents a complex intervention within a complex adaptive system. It could support better operational decision-making and facilitate identification and mitigation of threats to patient safety. There is, however, limited research on the impact of such complex health information technology on patient safety, reliability and operational efficiency of healthcare delivery and this study aims to help address that gap.
We will conduct a longitudinal mixed-method evaluation that will be informed by public-and-patient involvement and engagement. Interviews and ethnographic observations will inform iterations with quantitative analysis that will sensitise further qualitative work. Quantitative work will take an iterative approach to identify relevant outcome measures from both the literature and pragmatically from datasets of routinely collected electronic health records.
This protocol has been approved by the University of Leeds Engineering and Physical Sciences Research Ethics Committee (#MEEC 20-016) and the National Health Service Health Research Authority (IRAS No.: 285933). Our results will be communicated through peer-reviewed publications in international journals and conferences. We will provide ongoing feedback as part of our engagement work with local trust stakeholders. / National Institute for Health Research Health Service and Delivery Research Programme (NIHR129483)

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/19491
Date19 June 2023
CreatorsCiarĂ¡n,McInerney,, Carolyn,McCrorie,, Jonathan,Benn,, Ibrahim,Habli,, Tom,Lawton,, Teumzghi F,Mebrahtu,, Randell, Rebecca, Naeem,Sheikh,, Owen,Johnson,
Source SetsBradford Scholars
LanguageEnglish
Detected LanguageEnglish
TypeArticle, Published version
Rights(c) 2022 The Authors. This is an Open Access article distributed under the Creative Commons CC-BY license (https://creativecommons.org/licenses/by/4.0/), CC-BY

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