Caroline K. Yoo’s research while affiliated with VA Greater Los Angeles Healthcare System and other places

Objectives We examined how individual-level turnover among Veterans Health Administration primary care providers (PCPs) from fiscal years 2017 to 2021 was associated with health care system-level burnout and turnover intent. Background Burnout among PCPs has been well documented in recent studies, but less is known about the potential relationship between burnout and turnover. Methods We identified a national cohort of 6444 PCPs (physicians, nurse practitioners, and physician assistants) in 129 Veterans Health Administration health care systems in the first quarter of fiscal year 2017 and tracked their employment status for 20 quarters. PCP employment data on turnover were linked to annual health care system-level employee survey data on burnout, turnover intent, and other covariates. We performed logistic regression to estimate the impact of health care system-level burnout and turnover intent on individual PCP turnover, controlling for individual and health care system-level covariates and adjusting for clustering at the health care system level. Results Median health care system-level burnout ranged from 42.5% to 52.0% annually, and turnover among PCPs ranged from 6.3% to 8.4% (mean = 7.0%; SD = 0.9%). Separation from employment was higher among employees at health care systems with the highest burnout (odds ratio =1.14; 95% CI = 1.01–1.29) and turnover intent (OR = 1.18; 95% CI = 1.03–1.35). Conclusions PCPs in health care systems with high burnout are more likely to separate from employment. Policymakers and administrators seeking to improve retention should consider system-level interventions to address organizational drivers of burnout.

Objective To examine primary care (PC) team members’ characteristics associated with video use at the Veterans Health Administration (VA). Methods VA electronic data were used to identify PC team characteristics associated with any video-based PC visit, during the three-year study period (3/15/2019-3/15/2022). Multilevel mixed-effects logistic regression models on repeated yearly observations were used, adjusting for patient- and healthcare system-level characteristics, and study year. We included five PC team categories: 1.PC providers (PCP), which includes physicians, nurse practitioners, physician assistants, 2.Nurses (RN/LVN/LPN/other nurses), 3.Mental health (MH) specialists, 4.Social workers (SW), and 5.Clinical pharmacists (PharmD). Population 54,494 PC care team members nationwide (61,728,154 PC visits; 4,916,960 patients), including 14,422 PCPs, 30,273 nurses, 2,721 MH specialists, 4,065 SWs, and 3,013 PharmDs. Results The mean age was 46.1(SD = 11.3) years; 77.1% were women. Percent of video use among PC team members varied from 24 to 84%. In fully adjusted models, older clinicians were more likely to use video compared to the youngest age group (18–29 years old) (example: 50–59 age group: OR = 1.12,95%CI:1.07–1.18). Women were more likely to use video (OR = 1.18, 95%CI:1.14–1.22) compared to men. MH specialists (OR = 7.87,95%CI:7.32–8.46), PharmDs (OR = 1.16,95%CI:1.09–1.25), and SWs (OR = 1.51,95%CI:1.41–1.61) were more likely, whereas nurses (OR = 0.65,95%CI:0.62–0.67) were less likely to use video compared to PCPs. Conclusions This study highlights more video use among MH specialists, SWs, and PharmDs, and less video use among nurses compared to PCPs. Older and women clinicians, regardless of their role, used more video. This study helps to inform the care coordination of video-based delivery among interdisciplinary PC team members.

Many healthcare systems have implemented intensive outpatient primary care programs with the hopes of reducing healthcare costs. The Veterans Health Administration (VHA) piloted primary care intensive management (PIM) for patients at high risk for hospitalization or death, or “high-risk.” We evaluated whether a referral model would decrease high-risk patient costs. Retrospective cohort study using a quasi-experimental design comparing 456 high-risk patients referred to PIM from October 2017 to September 2018 to 415 high-risk patients matched on propensity score. Veterans in the top 10th percentile of risk for 90-day hospitalization or death and recent hospitalization or emergency department (ED) visit. PIM consisted of interdisciplinary teams that performed comprehensive assessments, intensive case management, and care coordination services. Change in VHA and non-VHA outpatient utilization, inpatient admissions, and costs 12 months pre- and post-index date. Of the 456 patients referred to PIM, 301 (66%) enrolled. High-risk patients referred to PIM had a marginal reduction in ED visits (− 0.7; [95% CI − 1.50 to 0.08]; p = 0.08) compared to propensity-matched high-risk patients; overall outpatient costs were similar. High-risk patients referred to PIM had similar number of medical/surgical hospitalizations (− 0.2; [95% CI, − 0.6 to 0.16]; p = 0.2), significant increases in length of stay (6.36; [CI, − 0.01 to 12.72]; p = 0.05), and higher inpatient costs ($22,628, [CI,$3587 to $41,669]; p = 0.02) than those not referred to PIM. VHA intensive outpatient primary care was associated with higher costs. Referral to intensive case management programs targets the most complex patients and may lead to increased utilization and costs, particularly in an integrated healthcare setting with robust patient-centered medical homes. PIM 2.0: Patient Aligned Care Team (PACT) Intensive Management (PIM) Project (PIM2). NCT04521816. https://clinicaltrials.gov/study/NCT04521816

Background The COVID-19 pandemic involved a rapid change to the working conditions of all healthcare workers (HCW), including those in primary care. Organizational responses to the pandemic, including a shift to virtual care, changes in staffing, and reassignments to testing-related work, may have shifted more burden to these HCWs, increasing their burnout and turnover intent, despite their engagement to their organization. Our objectives were (1) to examine changes in burnout and intent to leave rates in VA primary care from 2017–2020 (before and during the pandemic), and (2) to analyze how individual protective factors and organizational context affected burnout and turnover intent among VA primary care HCWs during the early months of the pandemic. Methods We analyzed individual- and healthcare system-level data from 19,894 primary care HCWs in 139 healthcare systems in 2020. We modeled potential relationships between individual-level burnout and turnover intent as outcomes, and individual-level employee engagement, perceptions of workload, leadership, and workgroups. At healthcare system-level, we assessed prior-year levels of burnout and turnover intent, COVID-19 burden (number of tests and deaths), and the extent of virtual care use as potential determinants. We conducted multivariable analyses using logistic regression with standard errors clustered by healthcare system controlled for individual-level demographics and healthcare system complexity. Results In 2020, 37% of primary care HCWs reported burnout, and 31% reported turnover intent. Highly engaged employees were less burned out (OR = 0.57; 95% CI 0.52–0.63) and had lower turnover intent (OR = 0.62; 95% CI 0.57–0.68). Pre-pandemic healthcare system-level burnout was a major predictor of individual-level pandemic burnout (p = 0.014). Perceptions of reasonable workload, trustworthy leadership, and strong workgroups were also related to lower burnout and turnover intent (p < 0.05 for all). COVID-19 burden, virtual care use, and prior year turnover were not associated with either outcome. Conclusions Employee engagement was associated with a lower likelihood of primary care HCW burnout and turnover intent during the pandemic, suggesting it may have a protective effect during stressful times. COVID-19 burden and virtual care use were not related to either outcome. Future research should focus on understanding the relationship between engagement and burnout and improving well-being in primary care.

This survey study of physicians in the Veterans Health Administration examines the association of burnout with various telework arrangements.

Importance: Telemedicine can increase access to care, but uptake has been low among people living in rural areas. The Veterans Health Administration initially encouraged telemedicine uptake in rural areas, but telemedicine expansion efforts have broadened since the COVID-19 pandemic. Objective: To examine changes over time in rural-urban differences in telemedicine use for primary care and for mental health integration services among Veterans Affairs (VA) beneficiaries. Design, setting, and participants: This cohort study examined 63.5 million primary care and 3.6 million mental health integration visits across 138 VA health care systems nationally from March 16, 2019, to December 15, 2021. Statistical analysis took place from December 2021 to January 2023. Exposures: Health care systems with most clinic locations designated as rural. Main outcomes and measures: For every system, monthly visit counts for primary care and mental health integration specialties were aggregated from 12 months before to 21 months after pandemic onset. Visits were categorized as in person or telemedicine, including video. A difference-in-difference approach was used to examine associations in visit modality by health care system rurality and pandemic onset. Regression models also adjusted for health care system size as well as relevant patient characteristics (eg, demographic characteristics, comorbidities, broadband internet access, and tablet access). Results: The study included 63 541 577 primary care visits (6 313 349 unique patients) and 3 621 653 mental health integration visits (972 578 unique patients) (6 329 124 unique patients among the cohort; mean [SD] age, 61.4 [17.1] years; 5 730 747 men [90.5%]; 1 091 241 non-Hispanic Black patients [17.2%]; and 4 198 777 non-Hispanic White patients [66.3%]). In fully adjusted models for primary care services before the pandemic, rural VA health care systems had higher proportions of telemedicine use than urban ones (34% [95% CI, 30%-38%] vs 29% [95% CI, 27%-32%]) but lower proportions of telemedicine use than urban health care systems after pandemic onset (55% [95% CI, 50%-59%] vs 60% [95% CI, 58%-62%]), signifying a 36% reduction in the odds of telemedicine use (odds ratio [OR], 0.64; 95% CI, 0.54-0.76). The rural-urban telemedicine gap was even larger for mental health integration (OR, 0.49; 95% CI, 0.35-0.67) than for primary care services. Few video visits occurred across rural and urban health care systems (unadjusted percentages: before the pandemic, 2% vs 1%; after the pandemic, 4% vs 8%). Nonetheless, there were rural-urban divides for video visits in both primary care (OR, 0.28; 95% CI, 0.19-0.40) and mental health integration services (OR, 0.34; 95% CI, 0.21-0.56). Conclusions and relevance: This study suggests that, despite initial telemedicine gains at rural VA health care sites, the pandemic was associated with an increase in the rural-urban telemedicine divide across the VA health care system. To ensure equitable access to care, the VA health care system's coordinated telemedicine response may benefit from addressing rural disparities in structural capacity (eg, internet bandwidth) and from tailoring technology to encourage adoption among rural users.