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Health Services Research & Development

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HSR&D In Progress

December 2020

In This Issue: Enhancing Primary Care for Veterans with Chronic Illness
» Table of Contents

Improving Depression Management in Primary Care

Feature Article

Takeaway: This research will result in the adaptation of a Primary Care Mental Health Integration (PC-MHI) collaborative care model that will be incorporated into computerized cognitive behavioral therapy (cCBT) that can improve access to psychotherapy and engage more than 400,000 untreated Veterans with depression who prefer psychotherapy.

VA invested to improve access to mental healthcare through the national Primary Care Mental Health Integration (PC-MHI) initiative. Through PC-MHI care models, primary care providers, mental health specialists, and/or care managers jointly manage mild-to-moderate psychiatric conditions directly in primary care settings. While PC-MHI enabled specialists to support medication treatment in primary care, timely and sufficient access to psychotherapy is unattainable, thus alternative therapy modalities are needed. Psychotherapy is preferred by Veterans with depression, but is fraught with multi-level barriers (i.e., staff availability, patient travel to clinic, limited clinic hours). Without enhancing existing PC-MHI models to enable better primary care patient access to effective psychotherapies, Veteran engagement in depression treatment is unlikely to improve.

The main objective of this ongoing HSR&D study (July 2020 – June 2025) is to close the gap in access to psychotherapy for VA primary care patients with depression by adapting PC-MHI collaborative care models to improve the uptake of computerized cognitive behavioral therapy (cCBT). cCBT is accessible 24/7 via the Internet and has effectively treated depression in more than 30 trials and, with modest specialist support, it is non-inferior to face-to-face psychotherapy. PC-MHI can facilitate Veteran uptake of cCBT, using an evidence-based collaborative care model to provide the follow-up care management and mental health specialist back-up that characterizes the most effective cCBT trials. Specifically, this study aims to:

  • Adapt PC-MHI collaborative care to improve uptake of cCBT among VA primary care patients with depression, based on input from multilevel stakeholders;
  • Pilot test the feasibility, acceptability, and potential effects of cCBT-enhanced collaborative care on Veterans’ depression symptoms and related outcomes in one primary care clinic, in preparation for a larger, multi-site hybrid effectiveness- implementation trial; and
  • Establish expert consensus on the translation of pilot findings into a design for cCBT-enhanced collaborative care that is feasible locally, regionally, and nationally in VA.


Interviews with several dozen mental health specialists and primary care clinicians confirmed high acceptability of the proposed cCBT-enhanced collaborative care model. Study investigators will continue to incorporate suggestions for PC-MHI care model improvement by conducting virtual focus groups with Veterans prior to pilot trial testing.


Adapting PC-MHI’s collaborative care model to incorporate cCBT can improve access to psychotherapy and engage the more than 400,000 untreated Veterans with depression who prefer psychotherapy, particularly Veterans who served in Iraq and/or Afghanistan who are seeking care that is convenient.

Principal Investigator: Lucinda Leung, MD, PhD, is an HSR&D Career Development Awardee and is part of HSR&D’s Center for the Study of Healthcare Innovation, Implementation and Policy (CSHIIP).


Leung L, Rubenstein L, Post E, et al.. Association of Veterans Affairs primary care mental health integration with care access among men and women Veterans. JAMA Network Open. October 20, 2020;3(10):e2020955.

Leung L, Young A, Heyworth L, et al. Do collaborative care managers and technology enhance primary care satisfaction with care from embedded mental health providers? Journal of General Internal Medicine. June 12, 2020; Epub ahead of print.

View study abstract


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