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Identifying Patterns of Primary Care In-Person and Telemedicine Use in the Veterans Health Administration: A Latent Class Analysis.
Staloff, Jonathan; Gunnink, Eric; Rojas, Jorge; Wong, Edwin S; Nelson, Karin; Reddy, Ashok.
Affiliation
  • Staloff J; Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, WA, USA. Jonathan.Staloff@va.gov.
  • Gunnink E; Department of Family Medicine, University of Washington, Seattle, WA, USA. Jonathan.Staloff@va.gov.
  • Rojas J; Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, WA, USA.
  • Wong ES; Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, WA, USA.
  • Nelson K; Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, WA, USA.
  • Reddy A; Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA, USA.
J Gen Intern Med ; 2024 Apr 15.
Article in En | MEDLINE | ID: mdl-38619738
ABSTRACT

BACKGROUND:

The Veterans Health Administration increased synchronous telemedicine (video and telephone visits) in primary care in response to the COVID-19 pandemic.

OBJECTIVE:

Our objective was to determine veteran use patterns of in-person and telemedicine primary care when all modalities were available.

DESIGN:

A retrospective cohort analysis. We performed a latent class analysis of primary care visits over a 1-year period to identify veteran subgroup (i.e., class) membership based on amount of primary care use and modality used. Then, we used multinomial logistic regression with a categorical outcome to identify patient characteristics associated with class identification.

PARTICIPANTS:

A random national sample consisting of 564,580 primary care empaneled veterans in June 2021. MAIN

MEASURES:

Latent class membership. KEY

RESULTS:

We identified three latent classes those with few primary care visits that were predominantly telephone-based (45%), intermediate number of visits of all modalities (50%), and many visits of all modalities (5%). In an adjusted model, characteristics associated with the "few" visits class, compared to the intermediate class, were older age, male sex, White race, further driving distance to primary care, higher Gagne, optimal internet speed, and unmarried status (OR 1.002, 1.52, 1.13, 1.004, 1.04, 1.05, 1.06, respectively; p < .05). Characteristics associated with membership in the "many" visits class, compared to the intermediate class, were Hispanic race, higher JEN Frailty Index and Gagne (OR 1.12, 1.11, 1.02, respectively; p < .05), and higher comorbidity by Care Assessment Need score quartile (Q2 1.73, Q3 2.80, Q4 4.12; p < 0.05).

CONCLUSIONS:

Veterans accessing primary care in-person or via telemedicine do so primarily in three ways (1) few visits, predominantly telephone; (2) intermediate visits, all modalities, (3) many visits, all modalities. We found no groups of veterans receiving a majority of primary care through video.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Gen Intern Med Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: J Gen Intern Med Year: 2024 Document type: Article