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A framework for automated conflict detection and resolution in medical guidelines
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dc.contributor.author | Bowles, J. | |
dc.contributor.author | Caminati, M. B. | |
dc.contributor.author | Cha, S. | |
dc.contributor.author | Mendoza, J. | |
dc.date.accessioned | 2020-02-04T12:30:06Z | |
dc.date.available | 2020-02-04T12:30:06Z | |
dc.date.issued | 2019-08-01 | |
dc.identifier.citation | Bowles , 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.2019.07.002 | en |
dc.identifier.issn | 0167-6423 | |
dc.identifier.other | PURE: 259673549 | |
dc.identifier.other | PURE UUID: 51c15793-9762-42e3-aa69-4e5e9f71971d | |
dc.identifier.other | RIS: urn:5E35C35908D9F3BE8A27B58E17FEC416 | |
dc.identifier.other | ORCID: /0000-0002-5918-9114/work/59698694 | |
dc.identifier.other | Scopus: 85069509594 | |
dc.identifier.other | ORCID: /0000-0002-4529-5442/work/68281665 | |
dc.identifier.other | WOS: 000487570800002 | |
dc.identifier.uri | https://hdl.handle.net/10023/19404 | |
dc.description | This 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.abstract | Common 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.extent | 22 | |
dc.language.iso | eng | |
dc.relation.ispartof | Science of Computer Programming | en |
dc.rights | Copyright © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CCBY license. | en |
dc.subject | Clinical guidelines | en |
dc.subject | Formal methods | en |
dc.subject | SMT solvers | en |
dc.subject | Theorem provers | en |
dc.subject | Isabelle/HOL | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | RM Therapeutics. Pharmacology | en |
dc.subject | T-NDAS | en |
dc.subject | BDC | en |
dc.subject | R2C | en |
dc.subject | ~DC~ | en |
dc.subject.lcc | QA75 | en |
dc.subject.lcc | RM | en |
dc.title | A framework for automated conflict detection and resolution in medical guidelines | en |
dc.type | Journal article | en |
dc.contributor.sponsor | Medical Research Council | en |
dc.contributor.sponsor | EPSRC | en |
dc.description.version | Publisher PDF | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.contributor.institution | University of St Andrews. School of Medicine | en |
dc.identifier.doi | https://doi.org/10.1016/j.scico.2019.07.002 | |
dc.description.status | Peer reviewed | en |
dc.identifier.grantnumber | MR/S003819/1 | en |
dc.identifier.grantnumber | EP/M014290/1 | en |
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