Process-Oriented Data Science for Healthcare 2019 (PODS4H19)

Dear Colleagues,

The world’s most valuable resource is no longer oil, but data. The ultimate goal of data science techniques is not to collect more data, but to extract knowledge and insights from existing data in various forms. Event data is the main source of information for the analysis and improvement of processes. In recent years, a new research area has emerged combining traditional process analysis and data-centric analysis: process-oriented data science (PODS). The interdisciplinary nature of this new research area has resulted in its application for the analysis of processes in different domains, especially healthcare.

This Special Issue aims at providing a high-quality forum for interdisciplinary researchers and practitioners (both data/process analysts and a medical audience) to exchange research findings and ideas on healthcare process analysis techniques and practices. Process-oriented data science for healthcare (PODS4H) research includes a wide range of topics from process mining techniques adapted for healthcare processes, to practical issues on implementing PODS methodologies in the analysis units of healthcare centres.

This Special Issue includes the extended versions of accepted articles from the ‘International Workshop on Process-Oriented Data Science 2019’, presenting novel research that demonstrates the potential of PODS approaches in analysing the way healthcare is delivered.

Dr. Jorge Munoz-Gama
Dr. Carlos Fernandez-Llatas
Dr. Niels Martin
Dr. Owen Johnson
Guest Editors

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