Treatment pathways as petri nets in patient workflow management

Boudko, Svetlana; Leister, Wolfgang

doi:10.1145/3151759.3151778

Cited by 2 publications

(1 citation statement)

References 32 publications

(27 reference statements)

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“…In the last decades, part of the medical informatics community has, therefore, been working extensively to develop computing structures that could be exploited to convey such knowledge, to support the educational needs of clinicians and medical students [12][13][14]. In particular, Petri Nets have widely been used in the medical domain for workflows modelling [15,16], access to services management [17], resource management [18], or guidelines [19], to figure out the flow of planned and executed activities to accomplish specific tasks, or to solve clinical problems. On the other hand, the deployment of technology-enhanced education has been in evolutionary development since the second half of the last century, and it is currently acknowledged as playing a pivotal role in delivering education to health professionals for the development of knowledge, skills, and behavior [20,21].…”

Section: Introductionmentioning

confidence: 99%

The Friendly Health Issue Network to Support Computer-Assisted Education for Clinical Reasoning in Multimorbidity Patients

et al. 2021

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Clinical reasoning in multimorbidity conditions asks for the ability to anticipate the possible evolutions of the overall health state of a patient and to identify the interactions among the concurrent health issues and their treatments. The HIN (Health Issue Network) approach, as Petri Nets-based formal language, is introduced as capable of providing a novel perspective to facilitate the acquisition of such competencies, graphically representing the network among a set of health issues (HIs) that affect a person throughout their life, and describing how HIs evolve over time. The need to provide a more immediate user-oriented interface has led to the development of f-HIN (friendly HIN), a lighter version based on the same mathematical properties as HIN, from which stems in turn the f-HINe (friendly HIN extracted) model, used to represent networks related to either real patients’ clinical experiences extracted from electronic health records, or from teacher-designed realistic clinical histories. Such models have also been designed to be embedded in a software learning environment that allows drawing a f-HIN diagram, checking for its format correctness, as well as designing clinical exercises for the learners, including their computer-assisted assessment. The present paper aims at introducing and discussing the f-HIN/f-HINe models and their educational use. It also introduces the main features of the software learning environment it was built upon, pointing out its importance to: (i) help medical teachers in designing and representing the context of a learning outcome; and (ii) handle the complex history of a multimorbidity patient, to be conveyed in Case-Based Learning (CBL) exercises.

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