Authors:
Alessandro Stefanini
1
;
Davide Aloini
2
;
Riccardo Dulmin
2
and
Valeria Mininno
2
Affiliations:
1
University of Rome Tor Vergata, Italy
;
2
University of Pisa, Italy
Keyword(s):
Healthcare, Process Discovery, Process Mining, Diagnostic-Related Group (DRG), Patient-flow.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Design and Development Methodologies for Healthcare IT
;
Enterprise Information Systems
;
Health Information Systems
;
Healthcare Management Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
The knowledge of patient-flow is very important for healthcare organizations, because strongly connected to effectiveness and efficiency of resource allocation. Unfortunately, traditional approaches to process analysis are scarcely effective and low efficient: they are very time-consuming and they may not provide an accurate picture of healthcare processes. Process mining techniques help to overcome these problems. This paper proposes a methodology for building a DRG related patient-flow using process mining. Findings show that it is possible to discover the different sequences of activities associated with a DRG related process. Managerial implications concern both process identification, analysis and improvement. A case study, based on a real open data set, is reported.