Master Assignment
Optimisation of endometriosis care in MST with the use of process mining
Type: Master BIT/CS/Itech
Location: MST/UT
Period: Asap
Student: (preferred Dutch speaking)
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Background:
Medisch Spectrum Twente (MST) is a top-clinical hospital committed to improving health outcomes in the Twente region. As part of the Santeon network—an alliance of seven leading hospitals—MST places a strong emphasis on continuously improving and innovating healthcare. Within the Value Based HealthCare department, data-driven outcomes and patient experiences are used to measure and enhance the quality of care.
Endometriosis is a chronic and often painful condition in which tissue similar to the uterine lining grows outside the uterus. This can lead to inflammation, adhesions, and scarring, particularly in the pelvic area. The condition affects an estimated 1 in 10 women of reproductive age and has a significant impact on both physical and mental quality of life. Despite the severity of symptoms, it takes an average of 6 to 7 years for women to receive an accurate diagnosis.
MST is committed to transforming healthcare to ensure specialist medical care remains accessible and affordable. Endometriosis care has grown rapidly in recent years, driven by rising patient demand and MST’s recognition as a center of expertise. However, current capacity is no longer sufficient. To meet future needs, MST is focused on expanding and professionalizing this care to maintain quality and accessibility.
Problem Definition:
Currently, the processes within endometriosis care at MST lack sufficient transparency, making it difficult to identify deviations from the intended care pathway. This limits the ability to implement targeted improvements that are essential for faster diagnosis, more efficient treatment, and higher patient satisfaction. Waiting times remain relatively long and represent a significant bottleneck in the quality of care. At the same time, the hospital is striving to meet the nationally established target times for surgical procedures.
Objective:
To analyze the care pathway for endometriosis patients within MST using process mining techniques, and to formulate concrete optimizations that enable a faster and more streamlined flow of patients through the multidisciplinary care process. Where possible, we aim to compare these insights with data from other Santeon hospitals to identify best practices and benchmark performance.