Evidence map›Paper›PMID 41401991›Full record

ArticleBMJ open2025

Leveraging COVID-19 to modernise depression care for VA primary care populations: protocol for a sequential explanatory mixed method evaluation.

Lucinda B Leung, Catherine E Brayton, Robyn L Shepardson, Caroline P Gray, Martin L Lee, Jennifer S Funderburk, John C Fortney

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Lucinda B LeungCenter for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California, USA lleung@mednet.ucla.edu.ORCID http://orcid.org/0000-0002-8103-8611
Catherine E BraytonCenter for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California, USA.
Robyn L ShepardsonCenter for Integrated Healthcare, Syracuse VA Medical Center, Syracuse, New York, USA.
Caroline P GrayCenter for Innovation to Implementation, VA Palo Alto Health Care System, Palo Alto, California, USA.
Martin L LeeCenter for the Study of Healthcare Innovation, Implementation and Policy, VA Greater Los Angeles Healthcare System, Los Angeles, California, USA.
Jennifer S FunderburkCenter for Integrated Healthcare, Syracuse VA Medical Center, Syracuse, New York, USA.
John C FortneyCenter of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, Washington, USA.

Funding

HSRD VA I01 HX003635HSRD VA IK2 HX002867
6 · The paper itself

Abstract

backgroundThe Veterans Health Administration (VA) integrated mental and physical health services to better detect and treat depression. Primary care nurses conduct screening annually. Clinicians, including Primary Care Mental Health Integration (PCMHI) specialists, follow-up as needed for treatment. Depression detection and management processes are complex, involve multilevel stakeholders, and are subject to significant disruption from COVID-19 and from the resulting expansion of telehealth, aiming to preserve care access. This study aimed to examine whether the COVID-19 pandemic worsened depression-related care quality and/or patient outcomes (eg, suicide).

methodsGiven hypothesised care disruption (lowered care quality) during COVID-19, we will first assess the VA population's trajectory from a new positive depression (and suicide risk) screen to appropriate treatment (ie, medication, therapy) in the Fiscal Year 2019-2323. We will also examine the changing mix of virtual and in-person depression care delivered. Second, we will use interrupted time series analyses to explore the extent to which psychiatric emergency visits and hospitalisations may be mitigated by clinician detection of depression. As well as compare mental health-related mortality rates between patients detected and not detected to have depression. Subanalyses will reveal where (eg, clinics with low PCMHI access) and for whom (eg, minorities) detection does not systematically occur, and downstream negative sequelae, to guide future intervention. Finally, we will interview 40 veterans, half of whom were detected and half not detected to have depression and 40 VA primary care and PCMHI providers about changes brought on by the pandemic and the expansion of virtual care across three VA facilities. In addition to contextualising disrupted care findings, qualitative data will help identify best practices on patient-to-provider and provider-to-provider interactions in hybrid in-person/telehealth depression care models. ETHICS AND DISSEMINATION: Ethics approval was granted by the VA Greater Los Angeles Healthcare System Institutional Review Board. Alongside journal publications, dissemination activities include briefings to our policy and operational partners, and presentations to clinical, research and policy-oriented audiences.

Indexed as

COVID-19DepressionMental Health ServicesPrimary Health CareVeteransHumansQuality of Health CareResearch DesignSARS-CoV-2TelemedicineUnited StatesUnited States Department of Veterans AffairsCOVID-19MENTAL HEALTHPrimary Care

Identifiers

PMID41401991
PMCPMC12706195

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.