Background & Objective
Chronic pain is a common and complex health problem that places high demands on nursing care. Time pressure, extensive documentation and limited access to pain specialists can lead to inconsistent evidence-based pain management in routine practice [1]. Clinical decision support systems (CDSS) can help integrate clinical information and align care with evidence-based pathways [2].Objective: Developing a backend decision-logic component for a CDSS to assist nurses in chronic pain management, focusing on a pain localization assessment.
Research Design/Methodology
This work extends an existing frontend application by implementing backend decision logic as part of the N!CA project [3]. A hierarchical model developed by a certified pain expert was implemented as a decision tree. The decision tree was serialized into a structured JSON schema containing node definitions and condition attributes. A rule engine interprets this schema and performs the decision-making logic accordingly.
Results/Discussion
Pain localization assessment: a functional prototype that captures pain characteristics and produces an assessment output. The rule-based backend supports structured execution of the expert model and outputs a result indicating the most likely target structure (e.g., nerve, muscle, or bone).
Perspectives/Implications
Future research will expand the system to support identifying pain causes by combining patient-reported data with clinical indicators.
References
[1] Mayer S. et al. The societal costs of chronic pain and its determinants: The case of Austria. PLoS One. 2019;14(3).
[2] Chen Z. et al. Harnessing the power of clinical decision support systems: challenges and opportunities. Open Heart. 2023;10(2).
[3] Demarcsek D.D. et al. Design of a Decision Support System for Chronic Pain Management to Support and Empower Nursing Professionals. Studies in Health Technology and Informatics. 2025;324:190–191.
