Process mining in healthcare: A literature review.

J Biomed Inform

Internal Medicine Department, School of Medicine, Pontificia Universidad Católica de Chile, Chile. Electronic address:

Published: June 2016

AI Article Synopsis

  • Process Mining involves analyzing data from corporate systems to understand and improve executed processes, showing promise in the healthcare sector through various case studies.
  • A literature review was conducted on 74 papers, examining key aspects like process types, common questions, techniques, and implementation strategies in healthcare.
  • The review offers a comprehensive overview of current research, aids researchers in selecting appropriate methodologies, and highlights ways to enhance healthcare processes using process mining.

Article Abstract

Process Mining focuses on extracting knowledge from data generated and stored in corporate information systems in order to analyze executed processes. In the healthcare domain, process mining has been used in different case studies, with promising results. Accordingly, we have conducted a literature review of the usage of process mining in healthcare. The scope of this review covers 74 papers with associated case studies, all of which were analyzed according to eleven main aspects, including: process and data types; frequently posed questions; process mining techniques, perspectives and tools; methodologies; implementation and analysis strategies; geographical analysis; and medical fields. The most commonly used categories and emerging topics have been identified, as well as future trends, such as enhancing Hospital Information Systems to become process-aware. This review can: (i) provide a useful overview of the current work being undertaken in this field; (ii) help researchers to choose process mining algorithms, techniques, tools, methodologies and approaches for their own applications; and (iii) highlight the use of process mining to improve healthcare processes.

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Source
http://dx.doi.org/10.1016/j.jbi.2016.04.007DOI Listing

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