Certificate of Achievement

Camilla Strauch

has completed the following course:

Process Mining in Healthcare

Eindhoven University of Technology

Within healthcare there are thousands of complex and variable processes that generate data including treatment of patients, lab results and internal logistic processes. Analysing this data is vital for improving these processes and ending bottlenecks. We discuss how process mining can be used to turn healthcare data into valuable insights to improve patient care while reducing costs via topics such as event data extraction, process discovery, and compliance verification.

4 weeks, 4 hours per week

Renata Medeiros de Carvalho

Assistant Professor, process mining in healthcare

Eindhoven University of Technology

overall score


Learning outcomes

  • Explain how process mining can help in analysing and improving healthcare processes
  • Identify opportunities for process mining in a healthcare organisation
  • Describe the data requirements in order to apply process mining
  • Interpret the results of various process mining techniques in the ProM lite tool
  • Apply ProM lite on real data to obtain process mining results


Process mining provides a critical, process-centric perspective on data, which is not available with classical data mining or machine learning techniques. Applying process mining in the healthcare environment is extra beneficial since processes are complex, and costs are high.

This course contains 4 weeks:

Week 1 introduced the healthcare environment, discussing current problems and challenges in healthcare process execution. An overview of process mining was also provided, including hands-on experience with the free and open-source process mining tool ProM. A case study was also presented showing how process mining was applied in a healthcare setting.

Week 2 discussed what data is necessary for process mining, and how to obtain this from the health information systems. Opportunities for process mining in healthcare, and a generic project approach was also discussed. This week also discussed concretely how data can be converted to the event log format. A case study was also presented, showing real results on real health data.

Week 3 covered key process mining techniques such as event log inspection (for instance via the dotted chart), event log filtering. The key process mining technique of process discovery is also shown. This week also presented ways to do conformance checking. Another case study involving process discovery was also discussed.

Week 4 focusses more on performance and social network analysis as the final process mining techniques. This week also discusses how processes can be improved using process mining results. Current challenges for process mining in healthcare are also presented.

Issued on 26th May 2020

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Free online course:

Process Mining in Healthcare

Eindhoven University of Technology