Gaining insight from patient journey data using process-oriented analysis approach

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Perimal-Lewis, Lua
Qin, Shaowen
Thompson, Campbell Henry
Hakendorf, Paul Haylett
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Australian Computer Society
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Hospitals are continually struggling to cater for the increasing demand for inpatient services. This is due to increased population, aging, and the rising incidence of chronic diseases associated with modern life. The high demand for hospital services leads to unpredictable bed availability, longer waiting period for acute admission, difficulties in keeping planned admission, stressed hospital staff, undesirable patient and family experience, as well as unclear long term impact on health care capacity. This study aims to derive some correlation between various factors contributing to ward occupancy rate and operation efficiency. The aim is also to discover the inpatient flow process model proposing to use process mining techniques combined with data analysis to depict the relationships among inpatients, wards and Length of Stay (LOS) in an effort to gain insight into factors that could be focused to relieve access block. Open source process mining software - ProM is used for this study. The study is done in collaboration with Flinders Medical Centre (FMC) using data from their Patient Journey Database as case study.
Mathematics, Process mining, Hospital inpatients, Ward occupancy
Perimal-Lewis, L., Qin, S., Thompson, C. and Hakendorf, P., 2012. Gaining insight from patient journey data using process-oriented analysis approach. In K. Butler-Henderson and K. Gray, (Eds.) 5th Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2012), Melbourne, Australia. CRPIT, vol. 129, 59-66.