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Process mining-driven analysis of COVID-19's impact on vaccination patterns.
Adriano Augusto1, Timothy Deitz1, Noel Faux1
1The University of Melbourne, Australia.
Journal of Biomedical Informatics
|May 7, 2022
Summary
Process mining techniques were adapted for healthcare event logs, revealing distinct patient service utilization patterns during the COVID-19 pandemic. Notably, vaccinations surged in 2020, contrasting with other healthcare interactions.
Area of Science:
- Process mining
- Data mining
- Healthcare analytics
Background:
- Process mining, bridging data mining and process science, analyzes event logs.
- While beneficial in business, its application in healthcare presents unique challenges.
- Existing research highlights the potential of process mining in healthcare contexts.
Purpose of the Study:
- To develop a methodology for preparing and analyzing healthcare process data using process mining.
- To identify challenges and benefits of process mining techniques with complex healthcare data.
- To compare patient health service utilization patterns in 2020 (COVID-19 pandemic) with 2016-2019.
Main Methods:
- Data preparation for general practice healthcare process mining.
- Selection and application of suitable process mining tools.
- Integration of process mining with traditional data mining techniques.
Main Results:
- Identified key challenges in applying process mining to healthcare data, particularly with high variability and large datasets.
- Highlighted benefits and limitations of current process mining techniques in healthcare.
- Demonstrated a surge in influenza and pneumococcus vaccinations in Victoria during 2020, contrary to general trends.
Conclusions:
- The developed methodology enables effective process mining analysis of healthcare data.
- Process mining can reveal specific utilization patterns, such as increased vaccinations during the pandemic.
- Findings contrast with other studies, emphasizing geographical and contextual differences in healthcare utilization.
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