Use of population health data to promote equitable recruitment for a primary care practice implementation trial addressing unhealthy alcohol use.

Background: Recruiting underrepresented people and communities in research is essential for generalizable findings. Ensuring representative participants can be particularly challenging for practice-level dissemination and implementation trials. Novel use of real-world data about practices and the communities they serve could promote more equitable and inclusive recruitment. Methods: We used a comprehensive primary care clinician and practice database, the Virginia All-Payers Claims Database, and the HealthLandscape Virginia mapping tool with community-level socio-ecological information to prospectively inform practice recruitment for a study to help primary care better screen and counsel for unhealthy alcohol use. Throughout recruitment, we measured how similar study practices were to primary care on average, mapped where practices' patients lived, and iteratively adapted our recruitment strategies. Results: In response to practice and community data, we adapted our recruitment strategy three times; first leveraging relationships with residency graduates, then a health system and professional organization approach, followed by a community-targeted approach, and a concluding approach using all three approaches. We enrolled 76 practices whose patients live in 97.3% (1844 of 1907) of Virginia's census tracts. Our overall patient sample had similar demographics to the state for race (21.7% vs 20.0% Black), ethnicity (9.5% vs 10.2% Hispanic), insurance status (6.4% vs 8.0% uninsured), and education (26.0% vs 32.5% high school graduate or less). Each practice recruitment approach uniquely included different communities and patients. Discussion: Data about primary care practices and the communities they serve can prospectively inform research recruitment of practices to yield more representative and inclusive patient cohorts for participation.

External Validation of the COVID-NoLab and COVID-SimpleLab Prognostic Tools.

Our objective was to externally validate 2 simple risk scores for mortality among a mostly inpatient population with COVID-19 in Canada (588 patients for COVID-NoLab and 479 patients for COVID-SimpleLab). The mortality rates in the low-, moderate-, and high-risk groups for COVID-NoLab were 1.1%, 9.6%, and 21.2%, respectively. The mortality rates for COVID-SimpleLab were 0.0%, 9.8%, and 20.0%, respectively. These values were similar to those in the original derivation cohort. The 2 simple risk scores, now successfully externally validated, offer clinicians a reliable way to quickly identify low-risk inpatients who could potentially be managed as outpatients in the event of a bed shortage. Both are available online (https://ebell-projects.shinyapps.io/covid_nolab/ and https://ebell-projects.shinyapps.io/COVID-SimpleLab/).

Virtual engagement of under-resourced communities: Lessons learned during the COVID-19 pandemic for creating crisis-resistant research infrastructure.

The COVID-19 pandemic led to an increased need to conduct research and community engagement using digital methods. Unfortunately, the shift away from in-person research activities can make it difficult to engage and recruit participants from under-resourced communities that lack adequate digital infrastructure. At the beginning of the pandemic, our team recognized that imminent lockdowns would significantly disrupt ongoing engagement with low-income housing resident community partners and that we would ultimately bear responsibility if that occurred. This manuscript outlines the development of methods designed to create capacity for virtual engagement with a community advisory board that were subsequently applied to a longitudinal mixed-methods study. We describe how our experience engaging low-income housing residents during the height of the pandemic influenced the approach and offer guidelines useful for engaging under-resourced communities regardless of setting. Of these, a strong commitment to providing technology, unlimited data connectivity, and basic digital literacy training/technical support is most important. While each of these is essential and failure in any one area will reduce overall effectiveness of the effort, providing adequate technical support while maintaining ongoing relationships with community members is the most important and resource-intensive.

Development and Validation of a Two-Step Predictive Risk Stratification Model for Coronavirus Disease 2019 In-hospital Mortality: A Multicenter Retrospective Cohort Study.

Objectives: An accurate prognostic score to predict mortality for adults with COVID-19 infection is needed to understand who would benefit most from hospitalizations and more intensive support and care. We aimed to develop and validate a two-step score system for patient triage, and to identify patients at a relatively low level of mortality risk using easy-to-collect individual information. Design: Multicenter retrospective observational cohort study. Setting: Four health centers from Virginia Commonwealth University, Georgetown University, the University of Florida, and the University of California, Los Angeles. Patients: Coronavirus Disease 2019-confirmed and hospitalized adult patients. Measurements and Main Results: We included 1,673 participants from Virginia Commonwealth University (VCU) as the derivation cohort. Risk factors for in-hospital death were identified using a multivariable logistic model with variable selection procedures after repeated missing data imputation. A two-step risk score was developed to identify patients at lower, moderate, and higher mortality risk. The first step selected increasing age, more than one pre-existing comorbidities, heart rate >100 beats/min, respiratory rate ≥30 breaths/min, and SpO2 <93% into the predictive model. Besides age and SpO2, the second step used blood urea nitrogen, absolute neutrophil count, C-reactive protein, platelet count, and neutrophil-to-lymphocyte ratio as predictors. C-statistics reflected very good discrimination with internal validation at VCU (0.83, 95% CI 0.79-0.88) and external validation at the other three health systems (range, 0.79-0.85). A one-step model was also derived for comparison. Overall, the two-step risk score had better performance than the one-step score. Conclusions: The two-step scoring system used widely available, point-of-care data for triage of COVID-19 patients and is a potentially time- and cost-saving tool in practice.

The Distressed State of Primary Care in Virginia Pre-Medicaid Expansion and Pre-Pandemic.

BACKGROUND: Primary care is crucial to the health of individuals and communities, but it faces numerous structural and systemic challenges. Our study assessed the state of primary care in Virginia to prepare for Medicaid expansion. It also provides insight into the frontline of health care prior to an unprecedented global COVID-19 pandemic. METHODS: We surveyed 1622 primary care practices to understand organizational characteristics, scope of care, capacity, and organizational stress. RESULTS: Practices (484) varied in type, ownership, location, and care for medically underserved and diverse patient populations. Most practices accepted uninsured and Medicaid patients. Practices reported a broad scope of care, including offering behavioral health and medication-assisted therapy for opioid addiction. Over half addressed social needs like transportation and unstable housing. One in three practices experienced a significant stress in 2019, prepandemic, and only 18.8% of practices anticipated a stress in 2020. CONCLUSIONS: Primary care serves as the foundation of our health care system and is an essential service, but it is severely stressed, under-resourced, and overburdened in the best of times. Primary care needs strategic workforce planning, adequate access to resources, and financial investment to sustain its value and innovation.

Screening for Vitamin D Deficiency in Adults: US Preventive Services Task Force Recommendation Statement.

Importance: Vitamin D is a fat-soluble vitamin that performs an important role in calcium homeostasis and bone metabolism and also affects many other cellular regulatory functions outside the skeletal system. Vitamin D requirements may vary by individual; thus, no one serum vitamin D level cutpoint defines deficiency, and no consensus exists regarding the precise serum levels of vitamin D that represent optimal health or sufficiency. Objective: To update its 2014 recommendation, the US Preventive Services Task Force (USPSTF) commissioned a systematic review on screening for vitamin D deficiency, including the benefits and harms of screening and early treatment. Population: Community-dwelling, nonpregnant adults who have no signs or symptoms of vitamin D deficiency or conditions for which vitamin D treatment is recommended. Evidence Assessment: The USPSTF concludes that the overall evidence on the benefits of screening for vitamin D deficiency is lacking. Therefore, the balance of benefits and harms of screening for vitamin D deficiency in asymptomatic adults cannot be determined. Recommendation: The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening for vitamin D deficiency in asymptomatic adults. (I statement).

Development and Validation of the COVID-NoLab and COVID-SimpleLab Risk Scores for Prognosis in 6 US Health Systems.

PURPOSE: Develop and validate simple risk scores based on initial clinical data and no or minimal laboratory testing to predict mortality in hospitalized adults with COVID-19. METHODS: We gathered clinical and initial laboratory variables on consecutive inpatients with COVID-19 who had either died or been discharged alive at 6 US health centers. Logistic regression was used to develop a predictive model using no laboratory values (COVID-NoLab) and one adding tests available in many outpatient settings (COVID-SimpleLab). The models were converted to point scores and their accuracy evaluated in an internal validation group. RESULTS: We identified 1340 adult inpatients with complete data for nonlaboratory parameters and 741 with complete data for white blood cell (WBC) count, differential, c-reactive protein (CRP), and serum creatinine. The COVID-NoLab risk score includes age, respiratory rate, and oxygen saturation and identified risk groups with 0.8%, 11.4%, and 40.4% mortality in the validation group (AUROCC = 0.803). The COVID-SimpleLab score includes age, respiratory rate, oxygen saturation, WBC, CRP, serum creatinine, and comorbid asthma and identified risk groups with 1.0%, 9.1%, and 29.3% mortality in the validation group (AUROCC = 0.833). CONCLUSIONS: Because they use simple, readily available predictors, developed risk scores have potential applicability in the outpatient setting but require prospective validation before use.

Redesigning Primary Care to Address the COVID-19 Pandemic in the Midst of the Pandemic.

During a pandemic, primary care is the first line of defense. It is able to reinforce public health messages, help patients manage at home, and identify those in need of hospital care. In response to the COVID-19 pandemic, primary care scrambled to rapidly transform itself and protect clinicians, staff, and patients while remaining connected to patients. Using the established public health framework for addressing a pandemic, we describe the actions primary care needs to take in a pandemic. Recommended actions are based on observed experiences of the authors' primary care practices and networks. Early in the COVID-19 pandemic, tasks focused on promoting physical distancing and encouraging patients with suspected illness or exposure to self-quarantine. Testing was not available and contract tracing was not possible. As the pandemic spread, in-person care was converted to virtual care using telehealth. Practices remained connected to patients using registries to reach out to those at risk for infection, with uncontrolled chronic conditions, or were socially vulnerable. Practices managed most patients with suspected COVID-19 at home. As the pandemic decelerates, practices are now preparing to address the direct and indirect consequences-complications from COVID-19 infections, missed treatment for acute problems, inadequate prevention, uncontrolled chronic disease, mental illness, and greater social needs. Throughout, practices bore tremendous financial burden, laying off staff or even closing at a time when most needed. Primary care must learn from this experience and be ready for the next pandemic. Policymakers and payers cannot fail primary care during their next time of need.