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dc.contributor.authorBowles, J.
dc.contributor.authorCaminati, M. B.
dc.contributor.authorCha, S.
dc.contributor.authorMendoza, J.
dc.date.accessioned2020-02-04T12:30:06Z
dc.date.available2020-02-04T12:30:06Z
dc.date.issued2019-08-01
dc.identifier.citationBowles , J , Caminati , M B , Cha , S & Mendoza , J 2019 , ' A framework for automated conflict detection and resolution in medical guidelines ' , Science of Computer Programming , vol. 182 , pp. 42-63 . https://doi.org/10.1016/j.scico.2019.07.002en
dc.identifier.issn0167-6423
dc.identifier.otherPURE: 259673549
dc.identifier.otherPURE UUID: 51c15793-9762-42e3-aa69-4e5e9f71971d
dc.identifier.otherRIS: urn:5E35C35908D9F3BE8A27B58E17FEC416
dc.identifier.otherORCID: /0000-0002-5918-9114/work/59698694
dc.identifier.otherScopus: 85069509594
dc.identifier.otherORCID: /0000-0002-4529-5442/work/68281665
dc.identifier.otherWOS: 000487570800002
dc.identifier.urihttps://hdl.handle.net/10023/19404
dc.descriptionThis research is supported by the MRC-funded UK Research and Innovation grant MR/S003819/1 and by EPSRC grant EP/M014290/1.en
dc.description.abstractCommon chronic conditions are routinely treated following standardised procedures known as clinical guidelines. For patients suffering from two or more chronic conditions, known as multimorbidity, several guidelines have to be applied simultaneously, which may lead to severe adverse effects when the combined recommendations and prescribed medications are inconsistent or incomplete. This paper presents an automated formal framework to detect, highlight and resolve conflicts in the treatments used for patients with multimorbidities focusing on medications. The presented extended framework has a front-end which takes guidelines captured in a standard modelling language and returns the visualisation of the detected conflicts as well as suggested alternative treatments. Internally, the guidelines are transformed into formal models capturing the possible unfoldings of the guidelines. The back-end takes the formal models associated with multiple guidelines and checks their correctness with a theorem prover, and inherent inconsistencies with a constraint solver. Key to our approach is the use of an optimising constraint solver which enables us to search for the best solution that resolves/minimises conflicts according to medication efficacy and the degree of severity in case of harmful combinations, also taking into account their temporal overlapping. The approach is illustrated throughout with a real medical example.
dc.format.extent22
dc.language.isoeng
dc.relation.ispartofScience of Computer Programmingen
dc.rightsCopyright © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CCBY license.en
dc.subjectClinical guidelinesen
dc.subjectFormal methodsen
dc.subjectSMT solversen
dc.subjectTheorem proversen
dc.subjectIsabelle/HOLen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectRM Therapeutics. Pharmacologyen
dc.subjectT-NDASen
dc.subjectBDCen
dc.subjectR2Cen
dc.subject~DC~en
dc.subject.lccQA75en
dc.subject.lccRMen
dc.titleA framework for automated conflict detection and resolution in medical guidelinesen
dc.typeJournal articleen
dc.contributor.sponsorMedical Research Councilen
dc.contributor.sponsorEPSRCen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.contributor.institutionUniversity of St Andrews. School of Medicineen
dc.identifier.doihttps://doi.org/10.1016/j.scico.2019.07.002
dc.description.statusPeer revieweden
dc.identifier.grantnumberMR/S003819/1en
dc.identifier.grantnumberEP/M014290/1en


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