Customizable Rule-Based System for Enhanced Clinical Decision-Making in Dementia Risk Reduction

This study presents the development of a customizable rule-based engine, integrated into the LETHE Clinical Trial Management System (CTMS), designed to enhance clinical decision-making in a multidomain intervention for dementia risk reduction. The rule engine allows health professionals to create and personalize rules based on patient-specific profiles and evolving clinical knowledge, enabling more precise interventions. The system was developed through a collaborative approach with one health professional and employs a JSON based rules engine for flexible rule creation and implementation. Its application in the LETHE project, a randomized control trial involving 156 participants across multiple centers, demonstrates the potential of tailored digital interventions in improving clinical outcomes. Future enhancements will focus on broadening the system's usability and automating patient-specific tasks to streamline care.

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Publication Details

Journal
Studies in health technology and informatics
Published
2025-05-15
DOI
https://doi.org/10.3233/shti250276
Primary Topic
Pharmacy and Medical Practices
Type
article
Field-Weighted Citation Impact
0.00

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article

Customizable Rule-Based System for Enhanced Clinical Decision-Making in Dementia Risk Reduction

Markus Bödenler, Helena Untersteiner, Sten Hanke, Hannes Hilberger et al.
Studies in health technology and informatics
Pharmacy and Medical Practices
article

Customizable Rule-Based System for Enhanced Clinical Decision-Making in Dementia Risk Reduction

Markus Bödenler, Helena Untersteiner, Sten Hanke, Hannes Hilberger, Laura Pluch
article en

Abstract

This study presents the development of a customizable rule-based engine, integrated into the LETHE Clinical Trial Management System (CTMS), designed to enhance clinical decision-making in a multidomain intervention for dementia risk reduction. The rule engine allows health professionals to create and personalize rules based on patient-specific profiles and evolving clinical knowledge, enabling more precise interventions. The system was developed through a collaborative approach with one health professional and employs a JSON based rules engine for flexible rule creation and implementation. Its application in the LETHE project, a randomized control trial involving 156 participants across multiple centers, demonstrates the potential of tailored digital interventions in improving clinical outcomes. Future enhancements will focus on broadening the system's usability and automating patient-specific tasks to streamline care.

Studies in health technology and informaticsVol. 327
FH JOANNEUM University of Applied Sciences (AT), Medical University of Graz (AT), Medical University of Vienna (AT)
European Commission, Universiteit Maastricht, Universität Wien, Karolinska Institutet, Medizinische Universität Wien
Openalex Percentile: Top 74%
Pharmacy and Medical Practices
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