Joint Bachelor Thesis - Erasmus MC / RWTH PADS Comparative Process Mining in Nursing-Care
Nursing is a vital key element of the treatment path of hospitalized patients. Whether one visits an emergency department or gets a treatment to cancer, throughout the patient’s treatment, nursing is omnipresent. Hence, in order to deliver the best possible care to a patient, a solid understanding of nursing processes is of utmost importance.
Over the past year, within Erasmus MC (University Medical Center Rotterdam, the Netherlands), the activities executed by several nurses have been tracked in great detail. The data tracks what activity a specific nurse is executing at what particular point in time. What is of particular interest w.r.t. this data is the fact that multi-tasking, i.e., concurrency, is explicitly captured. Furthermore, the nursing data is captured, due to the move to a new building, in two situations: A) hospital building with multi-bedded wards; and B) hospital with 100% single rooms.
|Building A (multi-bedded wards)||Building B (Single rooms)|
Feb. 2018 - May 2018
Nov 2018 - Apr. 2019
258 Working hours;
76% Day shifts;
24% Evening shifts;
498 Working hours;
71% Day shifts;
21% Evening shifts;
9% Night shifts
|9 Different Departments||7 Different Departments|
In this BSc thesis project, i.e., a joint project Erasmus MC and the RWTH PADS chair, the student is asked to investigate the application of comparative process mining, in the context of the captured nursing data. The main goal of this project is to investigate potential differences between the executions of the nursing process in the two different buildings. These differences need to be expressed in terms of control-flow, i.e., process execution, as well as performance. Of particular interest is the activity distribution of the nursing process on a day-to-day basis, i.e., is the hospital following an appropriate work distribution? Other questions are: Do departments differ substantially and how does the work process vary across the day and evening?
The student is expected to execute the project at the PADS group in Aachen. Regular web-meetings with the supervisory team of Erasmus MC, as well as visits to the Erasmus premises will be facilitated as well. This project is a unique opportunity to work on real data and get experience in performing a research project. Moreover, it is very likely that the results obtained by this case study will be used in practice and will results in an international peer reviewed publication!
Knowledge of basic computer science concepts, good programming skills (Java/Python) and an interest in theoretical and practical aspects of process mining (i.e. conformance checking) and business process management recommended.
- Process Mining Book
- Coursera Process Mining Course
- Process Mining in Healthcare; A case study
- Process Mining in Healthcare: A literature review
Primary Academic Supervisors
Prof.dr.ir. Wil van der Aalst (RWTH)
Prof.dr. Monique van Dijk (Erasmus MC)
Dr. Erwin Ista (Erasmus MC)
Primary Daily Supervision
Dr.ir. Sebastiaan van Zelst (RWTH)
Send an e-mail to Sebastiaan van Zelst. Make sure to include detailed information about your background and scores for completed courses.