Abstract
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(a)
Situation faced: Given the forecasted growth of osteoarthritis patients and the scarcity of resources, the Maastricht UMC+ is looking for opportunities to improve the efficiency of the inter-organizational care process for knee osteoarthritis patients. Currently, noncomplex and complex knee osteoarthritis patients use the same costly facilities and highly specialized staff. Substantial gains in efficiency can be expected from unraveling these trajectories and using resource substitution (especially for noncomplex trajectories).
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(b)
Action taken: We show how an innovative, data-driven, three-step methodology can be used to unravel and improve the inter-organizational knee osteoarthritis care process. The three-step methodology provides guidelines on how to preprocess and integrate data sets and outlines data-clustering and data-reduction techniques that can be applied prior to process mining.
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(c)
Results achieved: We show how this advanced approach supported the unraveling of a spaghetti-like model of the complete process into easy-to-interpret subprocess models of the knee osteoarthritis care process. We also show how the subsequent analysis of these visualizations led us to pinpoint and quantify concrete options for improving the efficiency of the knee osteoarthritis care process.
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(d)
Lessons learned: To foster uptake of the data-driven, three-step methodology, future research should focus on developing further assistance with the selection of the best-performing clustering algorithm.
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Canjels, K.F., Imkamp, M.S.V., Boymans, T.A.E.J., Vanwersch, R.J.B. (2021). Improving the Arthrosis Care Process at Maastricht UMC+: Unraveling Complex and Noncomplex Cases by Data and Process Mining. In: vom Brocke, J., Mendling, J., Rosemann, M. (eds) Business Process Management Cases Vol. 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-63047-1_11
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DOI: https://doi.org/10.1007/978-3-662-63047-1_11
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