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Expansion of telemedicine during COVID-19 at a VA specialty clinic.
Balut, Michelle D; Wyte-Lake, Tamar; Steers, William Neil; Chu, Karen; Dobalian, Aram; Ziaeian, Boback; Heyworth, Leonie; Der-Martirosian, Claudia.
  • Balut MD; Veterans Emergency Management Evaluation Center (VEMEC), U.S. Department of Veterans Affairs, 16111 Plummer St, North Hills, CA, USA. Electronic address: michelle.balut@va.gov.
  • Wyte-Lake T; Veterans Emergency Management Evaluation Center (VEMEC), U.S. Department of Veterans Affairs, 16111 Plummer St, North Hills, CA, USA.
  • Steers WN; Veterans Emergency Management Evaluation Center (VEMEC), U.S. Department of Veterans Affairs, 16111 Plummer St, North Hills, CA, USA.
  • Chu K; Veterans Emergency Management Evaluation Center (VEMEC), U.S. Department of Veterans Affairs, 16111 Plummer St, North Hills, CA, USA.
  • Dobalian A; Veterans Emergency Management Evaluation Center (VEMEC), U.S. Department of Veterans Affairs, 16111 Plummer St, North Hills, CA, USA; Division of Health Systems Management and Policy, University of Memphis School of Public Health, 3825 DeSoto Ave, Memphis, TN, USA.
  • Ziaeian B; Center for the Study of Healthcare Innovation, Implementation & Policy (CSHIIP), U.S. Department of Veterans Affairs, 16111 Plummer St, North Hills, CA, USA; Division of Cardiology, UCLA David Geffen School of Medicine, 10833 Le Conte Ave, Los Angeles, CA, USA.
  • Heyworth L; Office of Connected Care, Veterans Health Administration (VHA), US Department of Veterans Affairs, 50 Irving St. NW, Washington, DC, USA; Department of Medicine, University of California, 9500 Gilman Dr, San Diego, CA, USA.
  • Der-Martirosian C; Veterans Emergency Management Evaluation Center (VEMEC), U.S. Department of Veterans Affairs, 16111 Plummer St, North Hills, CA, USA.
Healthc (Amst) ; 10(1): 100599, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1536582
ABSTRACT

BACKGROUND:

COVID-19 rapidly accelerated the implementation of telemedicine in U.S. Department of Veterans Affairs (VA) specialty care clinics. This mixed-methods study was conducted at a VA medical center to understand the use of telemedicine, and the barriers and facilitators to its implementation, in cardiology outpatient clinics.

METHODS:

Quantitative analyses modeled monthly trends of telemedicine use over 24-months (March 2019-March 2021) with segmented logistic regression and adjusted for socio-demographic predictors of patient-level telemedicine use. Qualitative interviews were conducted (July-October 2020) with eight cardiology clinicians.

RESULTS:

At the onset of COVID-19, likelihood of telemedicine use was ∼12 times higher than it was pre-COVID-19 (p < 0.001). White (OR = 1.38, 95% CI1.23-1.54), married (OR = 1.25, 95% CI1.11-1.40), Veterans with other health insurance (OR = 1.19, 95% CI1.06-1.35), were more likely to use telemedicine. Veterans with higher health risk factors were less likely (OR = 0.95, 95% CI0.93-0.97). Facilitators to rapid expansion of telemedicine included prior telemedicine experience; provider trainings; and staff champions. In contrast, lack of technical support and scheduling grids for virtual visits and patient ability/preference served as barriers.

CONCLUSIONS:

Findings suggest that once mutable barriers were addressed, the medical center was able to expand its telemedicine efforts during COVID-19. Beyond the pandemic, a hybrid of virtual and face-to-face care might be feasible and likely beneficial for healthcare providers and patients in specialty care. IMPLICATIONS The ability to rapidly transition from in-person to virtual visits can potentially assist with the continuity of care and management of chronic disease during infectious outbreaks and other major disasters that obstruct traditional care models.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Telemedicine / COVID-19 Type of study: Prognostic study / Qualitative research Limits: Humans Language: English Journal: Healthc (Amst) Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Telemedicine / COVID-19 Type of study: Prognostic study / Qualitative research Limits: Humans Language: English Journal: Healthc (Amst) Year: 2022 Document Type: Article