Impact of COVID-19 on Primary Care Practice Sites and Their Vulnerable Patients.

Purpose: While COVID-19 has upended lives, it has also catalyzed innovation with potential to advance health delivery. Yet, we know little about how the delivery system, and primary care in particular, has responded and how this has impacted vulnerable patients. We aimed to understand the impact of COVID-19 on primary care practice sites and their vulnerable patients and to identify explanations for variation. Approach: We developed and administered a survey to practice managers and physician leaders from 173 primary care practice sites, October-November 2020. We report and graphically depict results from univariate analysis and examine potential explanations for variation in practices' process innovations in response to COVID-19 by assessing bivariate relationships between seven dependent variables and four independent variables. Findings: Among 96 (55.5%) respondents, primary care practice sites on average took more safety (8.5 of 12) than financial (2.5 of 17) precautions in response to COVID-19. Practice sites varied in their efforts to protect patients with vulnerabilities, providing care initially postponed, and experience with virtual visits. Financial risk, practice size, practitioner age, and emergency preparedness explained variation in primary care practices' process innovations. Many practice sites plan to sustain virtual visits, dependent mostly on patient and provider preference and continued reimbursement. Value: While findings indicate rapid and substantial innovation, conditions must enable primary care practice sites to build on and sustain innovations, to support care for vulnerable populations, including those with multiple chronic conditions and socio-economic barriers to health, and to prepare primary care for future emergencies.

The COVID-19 Pandemic as an Opportunity for Operational Innovation at 2 Student-Run Free Clinics.

The onset of the COVID-19 pandemic and subsequent county shelter-in-place order forced the Cardinal Free Clinics (CFCs), Stanford University's 2 student-run free clinics, to close in March 2020. As student-run free clinics adhering to university-guided COVID policies, we have not been able to see patients in person since March of 2020. However, the closure of our in-person operations provided our student management team with an opportunity to innovate. In consultation with Stanford's Telehealth team and educators, we rapidly developed a telehealth clinic model for our patients. We adapted available telehealth guidelines to meet our patient care needs and educational objectives, which manifested in 3 key innovations: reconfigured clinic operations, an evidence-based social needs screen to more effectively assess and address social needs alongside medical needs, and a new telehealth training module for student volunteers. After 6 months of piloting our telehealth services, we believe that these changes have made our services and operations more robust and provided benefit to both our patients and volunteers. Despite an uncertain and evolving public health landscape, we are confident that these developments will strengthen the future operations of the CFCs.

COVID-19 antibody seroprevalence in Santa Clara County, California.

BACKGROUND: Measuring the seroprevalence of antibodies to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is central to understanding infection risk and fatality rates. We studied Coronavirus Disease 2019 (COVID-19)-antibody seroprevalence in a community sample drawn from Santa Clara County. METHODS: On 3 and 4 April 2020, we tested 3328 county residents for immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies to SARS-CoV-2 using a rapid lateral-flow assay (Premier Biotech). Participants were recruited using advertisements that were targeted to reach county residents that matched the county population by gender, race/ethnicity and zip code of residence. We estimate weights to match our sample to the county by zip, age, sex and race/ethnicity. We report the weighted and unweighted prevalence of antibodies to SARS-CoV-2. We adjust for test-performance characteristics by combining data from 18 independent test-kit assessments: 14 for specificity and 4 for sensitivity. RESULTS: The raw prevalence of antibodies in our sample was 1.5% [exact binomial 95% confidence interval (CI) 1.1-2.0%]. Test-performance specificity in our data was 99.5% (95% CI 99.2-99.7%) and sensitivity was 82.8% (95% CI 76.0-88.4%). The unweighted prevalence adjusted for test-performance characteristics was 1.2% (95% CI 0.7-1.8%). After weighting for population demographics, the prevalence was 2.8% (95% CI 1.3-4.2%), using bootstrap to estimate confidence bounds. These prevalence point estimates imply that 53 000 [95% CI 26 000 to 82 000 using weighted prevalence; 23 000 (95% CI 14 000-35 000) using unweighted prevalence] people were infected in Santa Clara County by late March-many more than the ∼1200 confirmed cases at the time. CONCLUSION: The estimated prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that COVID-19 was likely more widespread than indicated by the number of cases in late March, 2020. At the time, low-burden contexts such as Santa Clara County were far from herd-immunity thresholds.