Ве молиме користете го овој идентификатор да го цитирате или поврзете овој запис: http://hdl.handle.net/20.500.12188/9481
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dc.contributor.authorNeira, Quintano, Ricardoen_US
dc.contributor.authorGert-Jan de Vriesen_US
dc.contributor.authorS. Mans, Ronnyen_US
dc.contributor.authorSokoreli, Ioannaen_US
dc.date.accessioned2020-11-09T07:48:01Z-
dc.date.available2020-11-09T07:48:01Z-
dc.date.issued2020-09-24-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/9481-
dc.description.abstractHealthcare systems are facing challenges such as the increase in the number of chronically ill patients and the reduction in the availability of resources. This often leads to poor quality of clinical outcomes and increase of costs. One approach that contributes to minimizing the impacts of these challenges is to increase the adoption of preventive care. Population Health Management (PHM) develops and deploys healthcare programs aligned to the Quadruple Aim that promote the improvement of the population’s health, while trying to contain or reduce costs and improve patient and clinician satisfaction. In this paper, we explore and discuss the use of process mining techniques to support the development and evaluation of PHM programs. In addition, we discuss possible challenges and recommend solutions, and we reflect upon using process mining to support addressing the Quadruple Aim in PHM.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesISSN 1857-7288;-
dc.subjectPopulation health, Quadruple aim, Process analyticsen_US
dc.titleApplying Process Mining in Population Health Managementen_US
dc.typeProceedingsen_US
dc.relation.conferenceICT Innovations 2020en_US
item.grantfulltextopen-
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Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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