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dc.contributor.authorLebcir, Mohamed
dc.contributor.authorAhmad, Raheelah
dc.contributor.authorAtun, Rifat A.
dc.contributor.authorZhu, Nina J
dc.contributor.authorHolmes, Alison
dc.date.accessioned2020-08-29T00:07:34Z
dc.date.available2020-08-29T00:07:34Z
dc.date.issued2020-08-07
dc.identifier.citationLebcir , M , Ahmad , R , Atun , R A , Zhu , N J & Holmes , A 2020 , ' System Dynamics modelling to formulate policy interventions to optimise antibiotic prescribing in hospitals ' , Journal of the Operational Research Society , vol. 2020 , 1796537 . https://doi.org/10.1080/01605682.2020.1796537
dc.identifier.issn0160-5682
dc.identifier.otherPURE: 22473073
dc.identifier.otherPURE UUID: e9397422-9721-4b57-ab1b-ebfe45a1f523
dc.identifier.otherScopus: 85089252270
dc.identifier.urihttp://hdl.handle.net/2299/23090
dc.description© 2020 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.description.abstractMultiple strategies have been used in the National Health System (NHS) in England to reduce inappropriate antibiotic prescribing and consumption in order to tackle antimicrobial resistance. These strategies have included, among others, restricting dispensing, introduction of prescribing guidelines, use of clinical audit, and performance reviews as well as strategies aimed at changing the prescribing behaviour of clinicians. However, behavioural interventions have had limited effect in optimising doctors’ antibiotic prescribing practices. This study examines the determinants of decision-making for antibiotic prescribing in hospitals in the NHS. A system dynamics model was constructed to capture structural and behavioural influences to simulate doctors’ prescribing practices. Data from the literature, patient records, healthcare professional interviews and survey responses were used to parameterise the model. The scenario simulation shows maximum improvements in guideline compliance are achieved when compliance among senior staff is increased, combined with fast laboratory turnaround of blood cultures, and microbiologist review. Improving guideline compliance of junior staff alone has limited impact. This first use of system dynamics modelling to study antibiotic prescribing decision-making demonstrates the applicability of the methodology for design and evaluation of future policies and interventions.en
dc.language.isoeng
dc.relation.ispartofJournal of the Operational Research Society
dc.subjectSystem dynamics
dc.subjectantimicrobial resistance
dc.subjectantimicrobial stewardship
dc.subjectdecision-making
dc.subjectsystems thinking
dc.subjectManagement Information Systems
dc.subjectStrategy and Management
dc.subjectManagement Science and Operations Research
dc.subjectMarketing
dc.titleSystem Dynamics modelling to formulate policy interventions to optimise antibiotic prescribing in hospitalsen
dc.contributor.institutionHertfordshire Business School
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85089252270&partnerID=8YFLogxK
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1080/01605682.2020.1796537
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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