From: Clinical and operational insights from data-driven care pathway mapping: a systematic review
References | Notable for |
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Williams et al. [125] Weber et al. [126] Boytcheva et al. [127] Dauxais et al. [128] Guyet et al. [129] | Clinical process models utilising prescription data, focussing on therapeutic decisions [125], polypharmacy [126], chronic comorbidities [127], and drug interactions in chronic disease [128, 129]. [126] identifies potential strong drug interactions in nearly 40% of patients, while [127] finds a statistical association between a particular initial treatment and a subsequent comorbidity. [128, 129] identify a particular change of medication associated with a subsequent acute episode in previously stable patients |
Dabek et al. [130] | Visualisation tool allowing exploration of treatment pathways and comorbidities of a very large patient cohort |
Blum et al. [132] | Clinical process models deriving workflows from transcribed video. [131] assesses utility of a checklist in improving guideline conformance, while [132,133,134] derive consensus surgical workflows. These are linked to video in [132], and are editable and mergeable in [133, 134] |
Rojas and Capurro [135] Chen et al. [136] Movahedi et al. [137] | Patterns of treatment [135, 136] or adverse events [137]. [137] further determines clinically meaningful Markov Chain models of grouped adverse events |
Riaño et al. [138] | State-Decision-Action model, where clinical practice is mined from treatment records to construct a data-derived clinical algorithm |