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dc.contributor.authorHarper, A
dc.date.accessioned2021-01-19T08:53:28Z
dc.date.issued2021-01-18
dc.description.abstractIn healthcare, opportunities to use real-time data to support quick and effective decision-making are expanding rapidly, as data increases in volume, velocity and variety. In parallel, the need for short-term decision-support to improve system resilience is increasingly relevant, with the recent COVID-19 crisis underlining the pressure that our healthcare services are under to deliver safe, effective, quality care in the face of rapidly-shifting parameters. A real-time hybrid model (HM) which combines real-time data, predictions, and simulation, has the potential to support short-term decision-making in healthcare. Considering decision-making as a consequence of situation awareness focuses the HM on what information is needed where, when, how, and by whom with a view toward sustained implementation. However the articulation between real-time decision-support tools and a sociotechnical approach to their development and implementation is currently lacking in the literature. Having identified the need for a conceptual framework to support the development of real-time HMs for short-term decision-support, this research proposed and tested the Integrated Hybrid Analytics Framework (IHAF) through an examination of the stages of a Design Science methodology and insights from the literature examining decision-making in dynamic, sociotechnical systems, data analytics, and simulation. Informed by IHAF, a HM was developed using real-time Emergency Department data, time-series forecasting, and discrete-event simulation. The application started with patient questionnaires to support problem definition and to act as a formative evaluation, and was subsequently evaluated using staff interviews. Evaluation of the application found multiple examples where the objectives of people or sub-systems are not aligned, resulting in inefficiencies and other quality problems, which are characteristic of complex adaptive sociotechnical systems. Synthesis of the literature, the formative evaluation, and the final evaluation found significant themes which can act as antecedents or evaluation criteria for future real-time HM studies in sociotechnical systems, in particular in healthcare. The generic utility of IHAF is emphasised for supporting future applications in similar domains.en_GB
dc.identifier.urihttp://hdl.handle.net/10871/124426
dc.publisherUniversity of Exeteren_GB
dc.subjectSimulationen_GB
dc.subjectForecastingen_GB
dc.subjectShort-term decision-supporten_GB
dc.subjectHealthcareen_GB
dc.subjectHybrid modellingen_GB
dc.titleA Hybrid Modelling Framework for Real-time Decision-support for Urgent and Emergency Healthcareen_GB
dc.typeThesis or dissertationen_GB
dc.date.available2021-01-19T08:53:28Z
dc.contributor.advisorMustafee, Nen_GB
dc.contributor.advisorPitt, Men_GB
dc.publisher.departmentBusiness Schoolen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dc.type.degreetitlePhD in Management Studiesen_GB
dc.type.qualificationlevelDoctoralen_GB
dc.type.qualificationnameDoctoral Thesisen_GB
rioxxterms.versionNAen_GB
rioxxterms.licenseref.startdate2021-01-18
rioxxterms.typeThesisen_GB
refterms.dateFOA2021-01-19T08:53:32Z


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