[DSRP Evidence](https://dsrpevidence.org/)

# Utilizing Systems Thinking Approach to Enhance Veteran Outreach and Physician Wellness for the Development of an AI Assisting Tool

Branson Owens, Kayla Sin, Dylan D’Agostino, Reginal Sarsah, Joseph DeMartino, and Dr. Ahmed Bahabry, 2025, Annual General Donald R. Keith Memorial Conference, United States Military Academy, West Point — Engineering

Patterns: [Distinctions](https://dsrpevidence.org/pattern/distinctions), [Systems](https://dsrpevidence.org/pattern/systems), [Relationships](https://dsrpevidence.org/pattern/relationships), [Perspectives](https://dsrpevidence.org/pattern/perspectives)

## In short

Uses DSRP as the organizing methodology for analyzing AI-assisted physician decision-making within the pharmaceutical and military healthcare system.

## What they found (results)

DSRP analysis identifies the distinctions, system structure, stakeholder relationships, and perspectives needed to design an AI assistant that could reduce physician administrative workload while supporting prescription decisions, patient safety, insurance integration, and regulatory compliance.

## What they set out to do (purpose)

A West Point Systems Engineering capstone paper using DSRP and a Systemigram to analyze the pharmaceutical healthcare system and translate that analysis into a functional design for a generative AI tool to assist Army physicians.

## In more detail

The authors explicitly work through all four DSRP patterns. They distinguish AI assistance from autonomous clinical decision-making; model AI as part of the larger pharmaceutical and healthcare system; analyze action-reaction relationships among AI, physicians, pharmacists, patients, insurers, and other actors; and compare the perspectives of physicians, administrators, patients, policymakers, and regulators. They then convert this DSRP analysis into a Systemigram and, from that, a functional hierarchy specifying six major functions for the proposed AI system: collect patient data, secure patient data, analyze symptoms and medical history, generate treatment plans, manage insurance integration, and comply with healthcare regulation. The paper proposes small-scale development and testing as future work; it does not report an empirical test of the AI tool itself.

## Abstract

Artificial Intelligence (AI) is reshaping decision-making within the healthcare sector and operational efficiency within the Department of Defense (DoD). AI accomplishes this by supporting physicians in diagnostics. AI can enhance physician wellness by reducing administrative burdens and providing decision support. Within the DoD, AI's ability to efficiently process large datasets can improve access to care for service members. This paper captures the complexity of the pharmaceutical industry interactions using the system thinking DSRP (Distinctions, Systems, Relationships, and Perspectives) methodology, adding the perspective of leveraging AI in provider prescription practices. This paper uses a Systemigram to visualize the development of an AI to assist Army medical providers, which is translated into a functional hierarchy as a blueprint for this generative AI tool. This tool would document notes and generate recommendations for physicians to reduce physician workload. This paper synthesizes current research to identify AI's potential development and application in future work. Keywords: Artificial Intelligence (AI), DSRP Methodology, Systemigram, Stakeholder Analysis, Physician, Pharmaceutical Industry, Visual Model.

These researchers were not testing DSRP. The finding is theirs; the correspondence to DSRP is drawn by this site.

[Source](https://ieworldconference.org/content/WP2025/Papers/GDRKMCC25_8.pdf)