Master Assignment
Advancing Healthcare Process Simulation: Automating Discrete Event Models from Process Data
Type: Master EE/CS/TPS/etc
Period: ASAP.
Student: (Unassigned)
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Background
Through the application of process mining in healthcare, insights can be gained from the event data that is stored in hospital information systems. This backward-looking approach can provide valuable information on executed patient pathways and the performance and compliance of health care processes. Process mining methods can also support forward-looking approaches to simulate or predict patient treatment steps or provide recommendations. However, most of the literature has focused on backward-looking approaches and there are few efforts on forward-looking methods. Some research has been conducted on the automatic generation of simulation models from event logs. Instead of directly using event logs to develop simulation models in an automated manner, most researchers tend to use the process discovery to construct the model in a manual way.
Research questions and assignment:
The aim of this assignment is to investigate the possibilities of automatically constructing simulation models using process data – i.e. event logs – from health information systems. For this research the following questions should be answered:
- What efforts have been made so far in the literature to construct data-driven simulation models? This should provide an overview of the existing techniques.
- What are the considerations in automatically constructing simulation models from healthcare process data? This should take into account the characteristics of healthcare data, such as high variability and infrequent behavior in treatment pathways.
- How can an algorithm be developed to automatically extract and transform process data from health information systems into a coherent and effective simulation model? The proposed algorithm should be applied to a case study and provide insights into real-world applications.
Profile of the student:
We are looking for a highly motivated Master’s/Bachelor’s student with a strong background in statistics, algorithms and simulation, good modelling and analytical skills and enthusiasm about for this task. A basic understanding of event logs and process mining is valuable.