# Engineering the mind-body medicine: making a case for a trauma-informed primary care system

**Authors:** Satish Boregowda, Inga Eanes, Rodney Handy

PMC · DOI: 10.25122/jml-2025-0129 · Journal of Medicine and Life · 2025-12-01

## TL;DR

This paper suggests integrating trauma screening into primary care to improve patient outcomes through a structured, value-based system.

## Contribution

The novel contribution is an engineering framework for a trauma-informed primary care system using ACEs screening and stress response data.

## Key findings

- A trauma-informed primary care system can be modeled using ACEs screening and psychophysiological data.
- Mental health professionals embedded in primary care settings can improve trauma evaluation and treatment referral processes.
- An engineering-based design methodology is proposed to guide the implementation of trauma-informed care.

## Abstract

This narrative study proposes an engineering framework to model a value-based, trauma-informed primary care system. It is based on the premise that effective patient outcomes could be achieved by screening for adverse childhood experiences (ACEs). The protocol involves the administration of the ACE survey and an in-person trauma evaluation by mental health professionals embedded within the primary care settings. The ACE evaluation is then followed by the collection of psychophysiological stress response data. Depending on the level of symptomatic somatization, patients are then referred to appropriate treatment modalities. An engineering-based robust design methodology is utilized to demonstrate a model of a trauma-informed primary care system. To be deployed, the proposed value-based systems model of medicine warrants further investigation with clinical and empirical studies.

## Full-text entities

- **Genes:** AP2B1 (adaptor related protein complex 2 subunit beta 1) [NCBI Gene 163] {aka ADTB2, AP105B, AP2-BETA, CLAPB1}
- **Diseases:** trauma (MESH:D014947)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12863106/full.md

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12863106/full.md

## References

25 references — full list in the complete paper: https://tomesphere.com/paper/PMC12863106/full.md

---
Source: https://tomesphere.com/paper/PMC12863106