A Patient-Level Simulation Tool to Inform Data-Driven Pain Treatment Decisions and Policy in the US Military Health...

Area of Science:

• Health Informatics
• Computational Modeling
• Pain Management

Background:

• Chronic pain presents a significant challenge within the US Military Health System (MHS).
• Existing pain management pathways require optimization for guideline and policy congruence.
• Effective decision support tools are needed to navigate complex pain care.

Purpose of the Study:

• To develop and validate a digital health decision platform for pain management.
• To ensure pain management pathways align with established guidelines and policies.
• To enable simulation-based testing of policy and resource allocation decisions.

Main Methods:

• A discrete-event, patient-level simulation model was developed, based on the Defense Health Agency Stepped Care Model for Pain.
• The model incorporated eleven nodes representing various care interactions and was parameterized using cross-validated methods.
• Validation included clinician review, alignment with guidelines/policies, and comparison with population statistics.

Main Results:

• The platform simulates patient journeys, predicting encounter types, care settings, and treatment receipt (e.g., procedures, prescriptions).
• Key outcomes like opioid use, emergency room visits, and pain episode duration were modeled.
• Capabilities for counterfactual analysis were developed to assess hypothetical policy impacts.

Conclusions:

• The developed simulation platform facilitates testing of counterfactual policies for chronic pain management within the MHS.
• It offers decision support for resource allocation and policy evaluation.
• Further application and validation are recommended for broader implementation.