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Published in: BMC Medical Informatics and Decision Making 1/2024

Open Access 01-12-2024 | Research

Decision discovery using clinical decision support system decision log data for supporting the nurse decision-making process

Authors: Matthijs Berkhout, Koen Smit, Johan Versendaal

Published in: BMC Medical Informatics and Decision Making | Issue 1/2024

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Abstract

Background

Decision-making in healthcare is increasingly complex; notably in hospital environments where the information density is high, e.g., emergency departments, oncology departments, and psychiatry departments. This study aims to discover decisions from logged data to improve the decision-making process.

Methods

The Design Science Research Methodology (DSRM) was chosen to design an artifact (algorithm) for the discovery and visualization of decisions. The DSRM’s different activities are explained, from the definition of the problem to the evaluation of the artifact. During the design and development activities, the algorithm itself is created. During the demonstration and evaluation activities, the algorithm was tested with an authentic synthetic dataset.

Results

The results show the design and simulation of an algorithm for the discovery and visualization of decisions. A fuzzy classifier algorithm was adapted for (1) discovering decisions from a decision log and (2) visualizing the decisions using the Decision Model and Notation standard.

Conclusions

In this paper, we show that decisions can be discovered from a decision log and visualized for the improvement of the decision-making process of healthcare professionals or to support the periodic evaluation of protocols and guidelines.
Appendix
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Metadata
Title
Decision discovery using clinical decision support system decision log data for supporting the nurse decision-making process
Authors
Matthijs Berkhout
Koen Smit
Johan Versendaal
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2024
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-024-02486-3

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