Abstract
Healthcare processes frequently deviate from established treatment protocols due to unforeseen events and the complexities of illnesses. Many healthcare procedures do not account for variations in treatment paths across different diseases and patient subpopulations. Understanding the similarities and differences in treatment paths for different patient groups can provide valuable insights and potential process enhancements for various subgroups of concern. For hospitals, understanding various patient populations, such as severe or non-severe cases, is key for enhancing care paths. In this paper, we aim to compare treatment procedures for different subpopulations of patients using process mining techniques and identify indicators to improve the care path. We utilize the process mining for healthcare (PM 2HC) methodology to identify variations in treatment paths among different patient subgroups. We conducted a case study on sepsis, a complex illness with a wealth of available data, for in-depth analysis. Our findings indicate that various subpopulations exhibit different outcomes, offering promising directions for further research.
Original language | English |
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Title of host publication | Proceedings of the 26th International Conference on Enterprise Information Systems |
Editors | Joaquim Filipe, Michal Smialek, Alexander Brodsky, Slimane Hammoudi |
Publisher | SCITEPRESS |
Pages | 85-94 |
Number of pages | 10 |
Volume | 1 |
ISBN (Electronic) | 9789897586927 |
ISBN (Print) | 978-989-758-692-7 |
DOIs | |
Publication status | Published - 2024 |
Event | 26th International Conference on Enterprise Information Systems, ICEIS 2024 - Angers, France Duration: 28 Apr 2024 → 30 Apr 2024 Conference number: 26 |
Publication series
Name | International Conference on Enterprise Information Systems, ICEIS - Proceedings |
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Volume | 1 |
ISSN (Electronic) | 2184-4992 |
Conference
Conference | 26th International Conference on Enterprise Information Systems, ICEIS 2024 |
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Abbreviated title | ICEIS 2024 |
Country/Territory | France |
City | Angers |
Period | 28/04/24 → 30/04/24 |
Keywords
- Subpopulation Analysis
- Process Mining
- Healthcare Processes
- Sepsis