In Silico Evaluation of Algorithm-Based Clinical Decision Support Systems Based on Care Pathway Simulation Models:...

Area of Science:

• Health Informatics
• Computational Medicine
• Health Services Research

Background:

• In silico evaluation (ISE) creates digital twins of care pathways for assessing clinical decision support systems (CDSS).
• Despite numerous CDSS studies, fewer than 3% utilize ISE for evaluating broader clinical pathway impacts.
• A significant increase in ISE application for CDSS evaluation is observed, particularly post-2019.

Purpose of the Study:

• To review the scope of ISE methods for CDSS evaluation.
• Focus on simulation modeling, care pathway parameters, and outcomes within ISE.
• Identify gaps and potential of ISE in strengthening pre-implementation evidence for CDSS.

Main Methods:

• Scoping review following established methodological guidelines.
• Tailored search framework and a two-stage screening process for study identification.
• Extraction of CDSS characteristics and care pathway simulation modeling applications.

Main Results:

• Most ISE studies focused on patient, process, and cost-effectiveness outcomes.
• A critical gap exists in evaluating outcomes related to care provider well-being.
• Simulation approaches included dynamic and state-based models, categorized as decoupled or integrated.

Conclusions:

• ISE offers a resource-efficient, systems-level evaluation for CDSS before implementation.
• Care pathway simulation-based ISE strengthens pre-implementation evidence.
• ISE bridges model performance and clinical workflow impact for contextualized assessments.