Recommendations for enhancing the usability and understandability of process mining in healthcare

Niels Martin (Corresponding author), Jochen De Weerdt, Carlos Fernández-Llatas, Avigdor Gal, Roberto Gatta, Gema Ibáñez, Owen Johnson, Felix Mannhardt, Luis Marco-Ruiz, Steven Mertens, Jorge Munoz-Gama, Fernando Seoane, Jan Vanthienen, Moe Thandar Wynn, David Baltar Boilève, Jochen Bergs, Mieke Joosten-Melis, Stijn Schretlen, Bart Van Acker

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

Healthcare organizations are confronted with challenges including the contention between tightening budgets and increased care needs. In the light of these challenges, they are becoming increasingly aware of the need to improve their processes to ensure quality of care for patients. To identify process improvement opportunities, a thorough process analysis is required, which can be based on real-life process execution data captured by health information systems. Process mining is a research field that focuses on the development of techniques to extract process-related insights from process execution data, providing valuable and previously unknown information to instigate evidence-based process improvement in healthcare. However, despite the potential of process mining, its uptake in healthcare organizations outside case studies in a research context is rather limited. This observation was the starting point for an international brainstorm seminar. Based on the seminar's outcomes and with the ambition to stimulate a more widespread use of process mining in healthcare, this paper formulates recommendations to enhance the usability and understandability of process mining in healthcare. These recommendations are mainly targeted towards process mining researchers and the community to consider when developing a new research agenda for process mining in healthcare. Moreover, a limited number of recommendations are directed towards healthcare organizations and health information systems vendors, when shaping an environment to enable the continuous use of process mining.
Original languageEnglish
Article number101962
Number of pages14
JournalArtificial Intelligence in Medicine
Volume109
DOIs
Publication statusPublished - Sep 2020

Keywords

  • Event log
  • Health information system
  • Healthcare processes
  • Hospital information system
  • Process analysis
  • Process execution data
  • Process improvement
  • Process mining

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