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The Adoption of Video Visits During the COVID ‐19 Pandemic by VA Home Based Primary Care

电视会议 医学 时间轴 远程医疗 大流行 政府(语言学) 退伍军人事务部 宣言 护理部 远程医疗 医疗急救 医疗保健 2019年冠状病毒病(COVID-19) 电信 经济增长 哲学 语言学 政治学 疾病 内科学 传染病(医学专业) 经济 考古 病理 法学 计算机科学 历史
作者
Mike K.W. Cheng,Theresa A. Allison,Brian W. McSteen,Chloe J. Cattle,Daphne Lo
出处
期刊:Journal of the American Geriatrics Society [Wiley]
卷期号:69 (2): 318-320 被引量:15
标识
DOI:10.1111/jgs.16982
摘要

The Department of Veterans Affairs (VA) Home Based Primary Care (HBPC) program delivers in-home care to chronically ill geriatric veterans.1 During the COVID-19 pandemic, older adults were required to minimize in-person contact, and the home-based care delivery model became untenable.2, 3 National VA leadership encouraged replacing in-person visits with videoconferencing. This posed challenges for HBPC, for which video visits represented only 0.3% of over 1 million national HBPC visits from January 2019 to February 2020 despite efforts to promote adoption. Before the pandemic, national VA and HBPC leadership had developed structural changes, defined as changes related to resources, management systems, and policy guidelines,4 which laid the groundwork for video visit adoption. This included development of the VA Video Connect (VVC) videoconferencing software, investment in support lines to troubleshoot software issues, creation of a health record provider note template, and provision of government-issued laptops and cell phones to providers. Providers could enroll patients in a program distributing video-capable tablets to veterans with need.5 National leadership developed VVC training modules and incentivized replacing in-person visits with videoconferencing. Nevertheless, it was not until additional key local and national changes occurred around the time of the pandemic declaration that adoption rapidly increased in the San Francisco VA Health Care System's (SFVAHCS) HBPC from February to June 2020. We highlight key changes facilitating this increase. We developed a timeline of changes and categorized changes guided by the COM-B model of behavior change, a framework used to demonstrate how behavior (B) change occurs when individuals have the physical and mental capability (C) to seize available opportunities (O) if there is sufficient motivation (M) for change.6 Utilizing VA national (Corporate Data Warehouse) data, we trended video visits as a percentage of total visits between January 2020 and June 2020 in relation to the timeline. We trended percentages of providers who became video visit capable. The SFVAHCS with the University of California San Francisco IRB granted this project quality improvement exemption. Changes involved augmenting provider capability (leadership encouraging providers to upgrade computing hardware and complete training modules, temporary expansion of allowable videoconferencing platforms besides VVC), opportunity (large group didactics as well as individual tutorials and biweekly virtual office hours for VVC training, encouragement of peer education, triage changes to favor VVC visits), and motivation (local mandate for all clinicians to become VVC capable, heightened desire to keep patients healthy during the pandemic) (Figure 1). Behavior change occurred rapidly, as clinician video visit capability increased from 12% to 94% from March 1 to 27 and video visits increased from 0% to 2% of total visits from February to March and to 8% in April onward. This surpassed the regional Sierra Pacific Network to which SFVAHCS HBPC belongs, where video visits similarly increased from 0% to 2% from February to March but increased to only 6% to 7% in April onward. This project showed that improving video visit adoption required multiple domains of change. The combination of national structural changes and local changes addressing provider capability, opportunity, and motivation led to increased adoption. Given the diverse organizational, technological, and social barriers impacting telemedicine adoption,7 a multi-dimensional approach to change is vital. Our findings support those of another study, which found that changes in multiple domains, including workflow processes and technology infrastructure, correlated with increased telehealth adoption.8 However, our study is unique as it examines the correlation of these changes with telemedicine adoption in the distinct HBPC older adult population that typically receives high-touch in-home care. This study also highlights the skillful use of different modes of education to efficiently train providers to host video visits. This aligns with a recent educational review supporting the use of diverse educational methods within a single intervention as a key feature of effective faculty development education.9 These various training options accommodated the varying levels of provider expertise and knowledge gaps. Didactic trainings benefitted providers needing to learn the basics of VVC software utilization and virtual patient interaction, whereas individual tutorials and office hours catered to seasoned learners seeking advanced expertise. The SFVAHCS HBPC program, which cares for a particularly vulnerable geriatric population, increased video visit adoption exponentially and rapidly through a combination of national structural interventions and local changes addressing provider capability, opportunities, and motivation. This paper shows how these changes were operationalized on a local level, shedding light on national trends. Similar clinics may likewise benefit from changes enacted in various domains and levels to decrease the digital divide for patients.10 Future steps will focus on addressing behavior change from the patient perspective. We thank the SFVAHCS HBPC program team for their dedication to patient care and quick adaptation to unprecedented challenges. We thank Darlene M. Davis for her manuscript feedback and her efforts procuring data from the VA Corporate Data Warehouse on our behalf. We thank Dayna Cooper for her manuscript feedback. The authors do not have any financial disclosures to report. The authors do not have any financial or personal conflicts of interest to report. Conceptualization and design: Cheng, Allison, Lo. Data analysis and interpretation of results: Cheng, Allison, Lo. Preparation of manuscript: All authors. Unfunded quality improvement project. Dr. Allison's time was supported in part by the National Institute on Aging (K23AG062613-01). No sponsors had any role in the design, methods, subject recruitment, data collection, analysis, and preparation of the paper.
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