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Author: Admin | 2025-04-27
Of the previous section, this section aims to highlight some typical use cases for process mining in healthcare as reported in published research articles. While many of the papers that will be referenced below make important methodological contributions, the focus of the discussion in this section is mainly on how process mining techniques were applied in a particular healthcare context. To structure the outline, the six process mining types introduced in Chapter 1 [1] are used: process discovery (Sect. 3.1), conformance checking (Sect. 3.2), performance analysis (Sect. 3.3), comparative process mining (Sect. 3.4), predictive process mining (Sect. 3.5), and action-oriented process mining (Sect. 3.6). At the end of the section, some recommendations for further reading are provided (Sect. 3.7).3.1 Process DiscoveryProcess discovery focuses on the discovery of a process model from an event log. As holds for process mining in general, process discovery is also, by far, the most prominent use case of process mining in healthcare [17, 37]. Papers on process discovery in healthcare typically center around the discovery of the control-flow, i.e. the order of activities, from an event log [17].When focusing on control-flow discovery, various algorithms have been used to automatically retrieve a visualisation of the activity order from an event log. Based on a literature review, Guzzo et al. [37] conclude that Heuristics Miner is the most commonly used algorithm, followed by Fuzzy Miner and Inductive Miner. Control-flow discovery has been applied in various healthcare contexts. For instance: Caron et al. [14] use the Heuristics Miner
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