Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/9481
Title: Applying Process Mining in Population Health Management
Authors: Neira, Quintano, Ricardo
Gert-Jan de Vries
S. Mans, Ronny
Sokoreli, Ioanna
Keywords: Population health, Quadruple aim, Process analytics
Issue Date: 24-Sep-2020
Series/Report no.: ISSN 1857-7288;
Conference: ICT Innovations 2020
Abstract: Healthcare 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.
URI: http://hdl.handle.net/20.500.12188/9481
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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