Abstract
Clinical pathway (CP), a standardized treatment process based on a clinical guideline, is widely used to reduce costs while maintaining or improving patient care quality. However, there is a gap between the actual clinical process and the guideline, that causes CP application to be disturbed. A study on developing a data-driven automated clinical pathway to obtain insight into real clinical processes has been conducted. Still, patient characteristics and conditions, which could cause a variation, have not been fully considered. In this study, we aimed to develop a framework to derive a sophisticated clinical pathway from electronic health records (EHRs) data by exploring process variations according to the patient characteristics and conditions. To validate the applicability of the proposed framework, We conducted a case study using the Total Laparoscopic Hysterectomy (TLH) CP data, which was retrieved from an EHR system of a tertiary general hospital in South Korea between January 2012 and April 2016. We found that diabetic TLH patients show different medical performances with other TLH patients. We developed a tailored CP that adds eleven orders over the standard TLH CP, and experts evaluated it as meaningful.
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Acknowledgement
This work was approved (IRB No. B-1609/361-105) by the Institutional Review Board of the SNUBH, which waived patients’ informed consent. This work was funded by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2020-2018-0-01441) supervised by the IITP (Institute for Information & Communications Technology Promotion).
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Lim, J. et al. (2021). Deriving a Sophisticated Clinical Pathway Based on Patient Conditions from Electronic Health Record Data. In: Leemans, S., Leopold, H. (eds) Process Mining Workshops. ICPM 2020. Lecture Notes in Business Information Processing, vol 406. Springer, Cham. https://doi.org/10.1007/978-3-030-72693-5_27
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DOI: https://doi.org/10.1007/978-3-030-72693-5_27
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