Process Mining for Healthcare: The PM4H manifesto

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Announced by the Process-Oriented Data Science in Healthcare Alliance

Despite the considerable volume of data generated and stored in hospitals by staff members and computing systems alike, process mining has been leveraged primarily for targeted case studies in a research context thus far. In an interview with Jorge Munoz-Gama and Niels Martin, we discussed the benefits that process mining would bring to healthcare processes in this very newsletter!

Recently, the Process-Oriented Data Science in Healthcare Alliance has thus been established to foster novel research and innovative application of techniques targeting the data-driven improvement of healthcare processes with a systematic approach. Process mining for healthcare: Characteristics and challenges (a.k.a. the PM4H manifesto for short) is an initiative of the alliance within the IEEE Task Force on Process Mining. It presents the key characteristics of the healthcare domain to be considered to achieve a successful uptake of process mining, alongside challenges to be addressed by the research community in the future.

Jorge, Niels and more colleagues are the co-authors of the article in this cross-fertilizing research area following a five-year work. Published in the Journal of Biomedical Informatics (Elsevier), it is fully open access and available at (the figure on the right is taken from the paper, released under the CC-BY license). Don’t miss it!

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  • This article has been updated on April 29 2022, 15:14.
  • Announced by the Process-Oriented Data Science in Healthcare Alliance