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dc.contributor.authorAllen, M
dc.contributor.authorJames, C
dc.contributor.authorFrost, J
dc.contributor.authorLiabo, K
dc.contributor.authorPearn, K
dc.contributor.authorMonks, T
dc.contributor.authorEverson, R
dc.contributor.authorStein, K
dc.contributor.authorJames, M
dc.date.accessioned2022-11-04T10:44:46Z
dc.date.issued2022-07-15
dc.date.updated2022-11-04T07:31:44Z
dc.description.abstractBACKGROUND: Expert opinion is that about 20% of emergency stroke patients should receive thrombolysis. Currently, 11% to 12% of patients in England and Wales receive thrombolysis, ranging from 2% to 24% between hospitals. The aim of this study was to assess how much variation is due to differences in local patient populations, and how much is due to differences in clinical decision-making and stroke pathway performance, while estimating a realistic target thrombolysis use. METHODS: Anonymised data for 246 676 emergency stroke admissions to 132 acute hospitals in England and Wales between 2016 and 2018 was obtained from the Sentinel Stroke National Audit Programme data. We used machine learning to learn decisions on who to give thrombolysis to at each hospital. We used clinical pathway simulation to model effects of changing pathway performance. Qualitative research was used to assess clinician attitudes to these methods. Three changes were modeled: (1) arrival-to-treatment in 30 minutes, (2) proportion of patients with determined stroke onset times set to at least the national upper quartile, (3) thrombolysis decisions made based on majority vote of a benchmark set of hospitals. RESULTS: Of the modeled changes, any single change was predicted to increase national thrombolysis use from 11.6% to between 12.3% to 14.5% (clinical decision-making having the most effect). Combined, these changes would be expected to increase thrombolysis to 18.3%, but there would still be significant variation between hospitals depending on local patient population. Clinicians engaged well with the modeling, but those from hospitals with lower thrombolysis use were most cautious about the methods. CONCLUSIONS: Machine learning and clinical pathway simulation may be applied at scale to national stroke audit data, allowing extended use and analysis of audit data. Stroke thrombolysis rates of at least 18% look achievable in England and Wales, but each hospital should have its own target.en_GB
dc.description.sponsorshipNational Institute for Health Researchen_GB
dc.format.extent2758-2767
dc.format.mediumPrint-Electronic
dc.identifier.citationVol. 53, No. 9, pp. 2758-2767en_GB
dc.identifier.doihttps://doi.org/10.1161/STROKEAHA.121.038454
dc.identifier.urihttp://hdl.handle.net/10871/131628
dc.identifierORCID: 0000-0002-8746-9957 (Allen, Michael)
dc.identifierScopusID: 57188766014 (Allen, Michael)
dc.identifierORCID: 0000-0002-3503-5911 (Frost, Julia)
dc.identifierScopusID: 8856263500 (Frost, Julia)
dc.identifierORCID: 0000-0002-7052-1261 (Liabo, Kristin)
dc.identifierScopusID: 12766078500 (Pearn, Kerry)
dc.identifierORCID: 0000-0003-2631-4481 (Monks, Thomas)
dc.identifierScopusID: 55335012000 (Monks, Thomas)
dc.identifierORCID: 0000-0002-3964-1150 (Everson, Richard)
dc.identifierScopusID: 7006615147 (Everson, Richard)
dc.identifierORCID: 0000-0002-5842-9972 (Stein, Ken)
dc.language.isoenen_GB
dc.publisherWolters Kluwer Health / American Heart Associationen_GB
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pubmed/35862194en_GB
dc.rights© 2022 The Authors. Stroke is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.en_GB
dc.subjectclinical pathwaysen_GB
dc.subjectdecision makingen_GB
dc.subjecthospitalsen_GB
dc.subjectmachine learningen_GB
dc.subjectqualitative researchen_GB
dc.titleUse of clinical pathway simulation and machine learning to identify key levers for maximizing the benefit of intravenous thrombolysis in acute stroke.en_GB
dc.typeArticleen_GB
dc.date.available2022-11-04T10:44:46Z
dc.identifier.issn0039-2499
exeter.place-of-publicationUnited States
dc.descriptionThis is the final version. Available from Wolters Kluwer Health via the DOI in this record. en_GB
dc.identifier.eissn1524-4628
dc.identifier.journalStrokeen_GB
dc.relation.ispartofStroke, 53(9)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-05-02
dc.rights.licenseCC BY
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-07-15
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-11-04T10:37:27Z
refterms.versionFCDVoR
refterms.dateFOA2022-11-04T10:44:51Z
refterms.panelAen_GB
refterms.dateFirstOnline2022-07-15


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© 2022 The Authors. Stroke is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.
Except where otherwise noted, this item's licence is described as © 2022 The Authors. Stroke is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.