Care Quality and Equity in Health Centers During and After the COVID-19 Pandemic.

INTRODUCTION: Federally Qualified Community Health Centers (FQHCs) are on the frontline of efforts to improve healthcare equity and reduce disparities exacerbated by the COVID-19 pandemic. This study assesses the provision and equity of preventive care and chronic disease management by FQHCs before, during, and after the pandemic. METHODS: Using electronic health record data from 210 FQHCs nationwide and employing segmented regression in an interrupted time series design, preventive screening and chronic disease management were assessed for 939,053 patients from 2019 to 2022. Care measures included cancer screenings, blood pressure control, diabetes control, and childhood immunizations; patient-level factors including race and ethnicity, language preference, and multimorbidity status were analyzed for equitable care provision. Analyses were conducted in 2023-2024. RESULTS: Cancer screening rates and blood pressure control initially declined after the onset of the pandemic but later rebounded, while diabetes control showed a slight increase, later stabilizing. Racial and ethnic disparities persisted, with Asian individuals having a higher prevalence of screenings and blood pressure control, and Black/African American individuals facing a lower prevalence for most screenings but a higher prevalence for cervical cancer screening. Hispanic/Latino individuals had a higher prevalence of various screenings and diabetes control. Disparities persisted for Native Hawaiian/Other Pacific Islander and American Indian/Alaska Native individuals and were observed based on language and multimorbidity status. CONCLUSIONS: While preventive screening and chronic disease management in FQHCs have largely rebounded to pre-pandemic levels following an initial decline, persistent disparities highlight the need for targeted interventions to support FQHCs in addressing healthcare inequities.

Pandemic-related practice changes and CVD risk management in community clinics.

OBJECTIVES: Understanding how the COVID-19 pandemic affected cardiovascular disease (CVD) risk monitoring in primary care may inform new approaches for addressing modifiable CVD risks. This study examined how pandemic-driven changes in primary care delivery affected CVD risk management processes. STUDY DESIGN: This retrospective study used electronic health record data from patients at 70 primary care community clinics with scheduled appointments from September 1, 2018, to September 30, 2021. METHODS: Analyses examined associations between appointment type and select care process measures: appointment completion rates, time to appointment, and up-to-date documentation for blood pressure (BP) and hemoglobin A1c (HbA1c). RESULTS: Of 1,179,542 eligible scheduled primary care appointments, completion rates were higher for virtual care (VC) vs in-person appointments (10.7 percentage points [PP]; 95% CI, 10.5-11.0; P < .001). Time to appointment was shorter for VC vs in-person appointments (-3.9 days; 95% CI, -4.1 to -3.7; P < .001). BP documentation was higher for appointments completed pre- vs post pandemic onset (16.2 PP; 95% CI, 16.0-16.5; P < .001) and for appointments completed in person vs VC (54.9 PP; 95% CI, 54.6-55.2; P < .001). HbA1c documentation was higher for completed appointments after pandemic onset vs before (5.9 PP; 95% CI, 5.1-6.7; P < .001) and for completed VC appointments vs in-person appointments (3.9 PP; 95% CI, 3.0-4.7; P < .001). CONCLUSIONS: After pandemic onset, appointment completion rates were higher, time to appointment was shorter, HbA1c documentation increased, and BP documentation decreased. Future research should explore the advantages of using VC for CVD risk management while continuing to monitor for unintended consequences.

Cardiovascular disease risk management during COVID-19: in-person vs virtual visits.

OBJECTIVES: Limited research has assessed how virtual care (VC) affects cardiovascular disease (CVD) risk management, especially in community clinic settings. This study assessed change in community clinic patients' CVD risk management during the COVID-19 pandemic and CVD risk factor control among patients who had primarily in-person or primarily VC visits. STUDY DESIGN: Retrospective interrupted time-series analysis. METHODS: Data came from an electronic health record shared by 52 community clinics for index (March 1, 2019, to February 29, 2020) and follow-up (July 1, 2020, to February 28, 2022) periods. Analyses compared follow-up period changes in slope and level of population monthly means of 10-year reversible CVD risk score, blood pressure (BP), and hemoglobin A1c (HbA1c) among patients whose completed follow-up period visits were primarily in person vs primarily VC. Propensity score weighting minimized confounding. RESULTS: There were 10,028 in-person and 6593 VC patients in CVD risk analyses, 9874 in-person and 5390 VC patients in BP analyses, and 8221 in-person and 4937 VC patients in HbA1c analyses. The VC group was more commonly younger, female, White, and urban. Mean reversible CVD risk, mean systolic BP, and percentage of BP measurements that were 140/90 mm Hg or higher increased significantly from index to follow-up periods in both groups. Rate of change between these periods was the same for all outcomes in both groups, regardless of care modality. CONCLUSIONS: Among community clinic patients with CVD risk, receiving a majority of care in person vs a majority of care via VC was not significantly associated with longitudinal trends in reversible CVD risk score or key CVD risk factors.

Care Delivery in Community Health Centers Before, During, and After the COVID-19 Pandemic (2019-2022).

INTRODUCTION: Health centers provide primary and behavioral health care to the nation's safety net population. Many health centers served on the frontlines of the COVID-19 pandemic, which brought major changes to health center care delivery. OBJECTIVE: To elucidate primary care and behavioral health service delivery patterns in health centers before and during the COVID-19 public health emergency (PHE). METHODS: We compared annual and monthly patients from 2019 to 2022 for new and established patients by visit type (primary care, behavioral health) and encounter visits by modality (in-person, telehealth) across 218 health centers in 13 states. RESULTS: There were 1581,744 unique patients in the sample, most from health disparate populations. Review of primary care data over 4 years show that health centers served fewer pediatric patients over time, while retaining the capacity to provide to patients 65+. Monthly data on encounters highlights that the initial shift in March/April 2020 to telehealth was not sustained and that in-person visits rose steadily after November/December 2020 to return as the predominant care delivery mode. With regards to behavioral health, health centers continued to provide care to established patients throughout the PHE, while serving fewer new patients over time. In contrast to primary care, after initial uptake of telehealth in March/April 2020, telehealth encounters remained the predominant care delivery mode through 2022. CONCLUSION: Four years of data demonstrate how COVID-19 impacted delivery of primary care and behavioral health care for patients, highlighting gaps in pediatric care delivery and trends in telehealth over time.

Outcomes of A Virtual Practice-Tailored Medicare Annual Wellness Visit Intervention.

INTRODUCTION: Interventions are needed to promote utilization of the Medicare Annual Wellness Visit (AWV), an underused opportunity to perform screenings and plan individualized preventive health services. METHOD: Using remote practice redesign and electronic health record (EHR) support, we implemented the Practice-Tailored AWV intervention in 2021 (during the COVID-19 pandemic) in 3 small community-based practices. The intervention combines EHR-based tools with practice redesign approaches and resources. Outcomes included completion of AWV and fulfillment of recommended preventive services. RESULTS: At baseline the 3 practices had 1,513 Medicare patients with at least 1 visit in the past 12 months. AWV utilization went from 7% at baseline to 54% 8 months postintervention implementation; advance care planning increased 10.7% (from 7.9% to 18.6%); depression screening increased 16.3% (from 51.7% to 68.0%); and alcohol misuse screening increased 17.3% (from 42.6% to 59.9%). Every individual preventive health service was received more often by patients with an AWV than those without. At the patient level, fulfillment of all eligible preventive services (of a maximum of 12 evaluated) went from 47.5% to 53.8% (P < .001). Subgroup analyses showed that patients with AWVs completed a greater percentage of their total recommended preventive health services than those without an AWV. CONCLUSION: Virtual implementation of an intervention that combined EHR-based tools with practice redesign approaches increased AWV and preventive services utilization in Medicare patients. Given the success of this intervention during the COVID-19 pandemic (when practices had many competing demands), greater consideration should be given to delivering future interventions virtually.

The Role of Primary Care in Improving Population Health.

Policy Points Systems based on primary care have better population health, health equity, and health care quality, and lower health care expenditure. Primary care can be a boundary-spanning force to integrate and personalize the many factors from which population health emerges. Equitably advancing population health requires understanding and supporting the complexly interacting mechanisms by which primary care influences health, equity, and health costs.

Patterns of Diagnostic Evaluation and Determinants of Treatment in Older Patients With Non-transfusion Dependent Myelodysplastic Syndromes.

BACKGROUND: Older patients with myelodysplastic syndromes (MDS), particularly those with no or one cytopenia and no transfusion dependence, typically have an indolent course. Approximately, half of these receive the recommended diagnostic evaluation (DE) for MDS. We explored factors determining DE in these patients and its impact on subsequent treatment and outcomes. PATIENTS AND METHODS: We used 2011-2014 Medicare data to identify patients ≥66 years of age diagnosed with MDS. We used Classification and Regression Tree (CART) analysis to identify combinations of factors associated with DE and its impact on subsequent treatment. Variables examined included demographics, comorbidities, nursing home status, and investigative procedures performed. We conducted a logistic regression analysis to identify correlates associated with receipt of DE and treatment. RESULTS: Of 16 851 patients with MDS, 51% underwent DE. patients with MDS with no cytopenia (n = 3908) had the lowest uptake of DE (34.7%). Compared to patients with no cytopenia, those with any cytopenia had nearly 3 times higher odds of receiving DE [adjusted odds ratio (AOR), 2.81: 95% CI, 2.60-3.04] and the odds were higher for men than for women [AOR, 1.39: 95%CI, 1.30-1.48] and for Non-Hispanic Whites [vs. everyone else (AOR, 1.17: 95% CI, 1.06-1.29)]. The CART showed DE as the principal discriminating node, followed by the presence of any cytopenia for receiving MDS treatment. The lowest percentage of treatment was observed in patients without DE, at 14.6%. CONCLUSION: In this select older patients with MDS, we identified disparities in accurate diagnosis by demographic and clinical factors. Receipt of DE influenced subsequent treatment but not survival.

Racial and Ethnic Differences in Antiseizure Medications Among People With Epilepsy on Medicaid: A Case of Potential Inequities.

Background and Objectives: Being on a newer, second-, and third-generation antiseizure medication (ASM) may represent an important marker of quality of care for people with epilepsy. We sought to examine whether there were racial/ethnic differences in their use. Methods: Using Medicaid claims data, we identified the type and number of ASMs, as well as the adherence, for people with epilepsy over a 5-year period (2010-2014). We used multilevel logistic regression models to examine the association between newer-generation ASMs and adherence. We then examined whether there were racial/ethnic differences in ASM use in models adjusted for demographics, utilization, year, and comorbidities. Results: Among 78,534 adults with epilepsy, 17,729 were Black, and 9,376 were Hispanic. Overall, 25.6% were on older ASMs, and being solely on second-generation ASMs during the study period was associated with better adherence (adjusted odds ratio: 1.17, 95% confidence interval [CI]: 1.11-1.23). Those who saw a neurologist (3.26, 95% CI: 3.13-3.41) or who were newly diagnosed (1.29, 95% CI: 1.16-1.42) had higher odds of being on newer ASMs. Importantly, Black (0.71, 95% CI: 0.68-0.75), Hispanic (0.93, 95% CI: 0.88-0.99), and Native Hawaiian and Other Pacific Island individuals (0.77, 95% CI: 0.67-0.88) had lower odds of being on newer ASMs when compared with White individuals. Discussion: Generally, racial and ethnic minoritized people with epilepsy have lower odds of being on newer-generation ASMs. Greater adherence by people who were only on newer ASMs, their greater use among people seeing a neurologist, and the opportunity of a new diagnosis point to actionable leverage points for reducing inequities in epilepsy care.

Child Opportunity Index and Hospital Utilization in Children With Traumatic Brain Injury Admitted to the PICU.

The need to understand how Community-based disparities impact morbidity and mortality in pediatric critical illness, such as traumatic brain injury. Test the hypothesis that ZIP code-based disparities in hospital utilization, including length of stay (LOS) and hospital costs, exist in a cohort of children with traumatic brain injury (TBI) admitted to a PICU using the Child Opportunity Index (COI). DESIGN: Multicenter retrospective cohort study. SETTING: Pediatric Health Information System (PHIS) database. PATIENTS: Children 0-18 years old admitted to a PHIS hospital with a diagnosis of TBI from January 2016 to December 2020 requiring PICU care. To identify the most severely injured children, a study-specific definition of "Complicated TBI" was created based on radiology, pharmacy, and procedure codes. INTERVENTIONS: None. Main Outcomes and Measures: Using nationally normed ZIP code-level COI data, patients were categorized into COI quintiles. A low COI ZIP code has low childhood opportunity based on weighted indicators within educational, health and environmental, and social and economic domains. Population-averaged generalized estimating equation (GEE) models, adjusted for patient and clinical characteristics examined the association between COI and study outcomes, including hospital LOS and accrued hospital costs. The median age of this cohort of 8,055 children was 58 months (interquartile range [IQR], 8-145 mo). There were differences in patient demographics and rates of Complicated TBI between COI levels. The median hospital LOS was 3.0 days (IQR, 2.0-6.0 d) and in population-averaged GEE models, children living in very low COI ZIP codes were expected to have a hospital LOS 10.2% (95% CI, 4.1-16.8%; p = 0.0142) longer than children living in very high COI ZIP codes. For the 11% of children with a Complicated TBI, the relationship between COI and LOS was lost in multivariable models. COI level was not predictive of accrued hospital costs in this study. CONCLUSIONS: Children with TBI requiring PICU care living in low-opportunity ZIP codes have higher injury severity and longer hospital LOS compared with children living in higher-opportunity ZIP codes. Additional studies are needed to understand why these differences exist.

A framework for health equity in people living with epilepsy.

Epilepsy is a disease where disparities and inequities in risk and outcomes are complex and multifactorial. While most epilepsy research to date has identified several key areas of disparities, we set out to provide a multilevel life course model of epilepsy development, diagnosis, treatment, and outcomes to highlight how these disparities represent true inequities. Our piece also presents three hypothetical cases that highlight how the solutions to address inequities may vary across the lifespan. We then identify four key domains (structural, socio-cultural, health care, and physiological) that contribute to the persistence of inequities in epilepsy risk and outcomes in the United States. Each of these domains, and their core components in the context of epilepsy, are reviewed and discussed. Further, we highlight the connection between domains and key areas of intervention to strive towards health equity. The goal of this work is to highlight these domains while also providing epilepsy researchers and clinicians with broader context of how their work fits into health equity.

Primary Care: A Critical Stopgap of Mental Health Services During the COVID-19 Pandemic.

BACKGROUND: The COVID-19 pandemic resulted in a worsening mental health crisis, while also dramatically reducing access to in-person primary care services. Primary care, an essential provider of mental health services, rapidly adopted telemedicine to address behavioral health needs. Here we examine the provision of mental health services by primary care during the pandemic, including the essential use of telemedicine. METHODS: Data were collected via a series of national, cross-sectional surveys of primary care clinicians in November 2020 by the Larry A. Green Center. The survey was distributed through a network of partner organizations and subscribers. Descriptive and chi squared analysis were utilized. RESULTS: Among 1,472 respondents, 88% reported increased mental health needs and 37% reported higher rates of substance use among patients. Most (65%) clinicians became more involved in providing mental health support, and 64% reported using telemedicine to provide behavioral health services. Phone-based care was more common for care delivery among patients who were uninsured (60% vs 42%, P < .01), Medicare beneficiaries (45% vs 36%, P < .05), non-English speaking (67% vs 40%, P < .001), and racial and ethnic minorities (58% vs 34%, P < .001). CONCLUSIONS: Primary care is a leading provider of mental health services and has played a critical role during the pandemic. Primary care clinicians have strong relationships with their patients as well as outreach within communities that may otherwise struggle to access mental health services. The use of telemedicine in primary care, and specifically phone-based services, has been an essential tool to providing equitable access to mental health services.

Screening Families in Primary Care for Social and Economic Needs: Patients' Urgency and Activation for Social Care Navigation.

INTRODUCTION: Social determinants of health (SDoH) screening and intervention in primary care aim to alleviate adverse influences on health, but its efficacy may be diluted when offered supports are not well matched to families' desire for such services. The purpose of this prospective cohort study was to provide guidance to social care navigation teams regarding which families would be most likely to make use of services. METHODS: Analysis of registry data collected in April 1-September 30, 2021 from a social care navigation program embedded in a medical home was conducted. Multivariable regression models explored (1) whether family-reported urgency of needs, number of needs, and/or specific types of needs predicted completing program intake and (2) whether the degree of family activation regarding social needs predicted subsequent interactions with the navigation team. RESULTS: Of the 1,483 families reporting any social care needs (38% of all screens completed, mean of 2.5 needs per screen), 31% indicated that their needs were urgent. Accounting for program factors and the number and type of needs reported, families whose needs were urgent were more likely to complete intake (OR=1.34; 95% CI=1.01, 1.82; p=0.04) and remain engaged with the program over time (OR=2.25; 95% CI=1.62, 3.12; p<0.01). Those who were self-advocates were substantially less likely to desire follow-up or stay engaged (OR=0.40; 95% CI=0.17, 0.93; p<0.01). CONCLUSIONS: Family-reported urgency of needs and activation for social care assistance predicted engagement with the navigation team. SDoH interventions should prioritize outreach to those families expressing an interest in help with any of their identified needs.

Describing and assessing a new method of approximating categorical individual-level income using community-level income from the census (weighting by income probabilities).

OBJECTIVE: To assess a new approach (weighting by "income probabilities [IP]") that uses US Census data from the patients' communities to approximate individual-level income, an important but often missing variable in health services research. DATA SOURCES: Community (census tract level) income data came from the 2017 5-year American Community Survey (ACS). The patient data included those diagnosed with cancer in 2017 in Ohio (n = 65,759). The reference population was the 2017 5-year ACS Public Use Microdata Sample (n = 564,357 generalizing to 11,288,350 Ohioans). STUDY DESIGN/METHODS: We applied the traditional approach of income approximation using median census tract income along with two IP based approaches to estimate the proportions in the patient data with incomes of 0%-149%, 150%-299%, 300%-499%, and 500%+ of the federal poverty level (FPL) ("class-relevant income grouping") or 0%-138%, 139%-249%, 250%-399%, and 400%+ FPL ("policy-relevant income grouping"). These estimated income distributions were then compared with the known income distributions of the reference population. DATA COLLECTION/EXTRACTION METHODS: The patient data came from Ohio's cancer registry. The other data were publicly available. PRINCIPAL FINDINGS: Both IP based approaches consistently outperformed the traditional approach overall and in subgroup analyses, as measured by the weighted average absolute percentage point differences between the proportions of each of the income categories of the reference population and the estimated proportions generated by the income approximation approaches ("average percent difference," or APD). The smallest APD for an IP based method, 0.5%, was seen in non-Hispanic White females in the class-relevant income grouping (compared with 16.5% for the conventional method), while the largest APD, 7.1%, was seen in non-Hispanic Black females in the policy-relevant income grouping (compared with 18.0% for the conventional method). CONCLUSIONS: Weighting by IP substantially outperformed the conventional approach of estimating the distribution of incomes in patient data.

Inconsistent Medicaid Coverage is Associated with Negative Health Events for People with Epilepsy.

OBJECTIVE: Examine the association between gaps in Medicaid coverage and negative health events (NHEs) for people with epilepsy (PWE). METHODS: Using five years of Medicaid claims for PWE, we identified gaps in Medicaid coverage. We used logistic regression to evaluate the association between a gap in coverage and being in the top quartile of NHEs and factors associated with having a gap. These models adjusted for: demographics, residence, medication adherence, disease severity, and comorbidities. RESULTS: Of 186,616 PWE, 21.7% had a gap in coverage. The odds of being in the top quartile of NHEs per year were 66% higher among those with a gap (OR: 1.66; 95% CI: 1.61, 1.70). Being female, younger, and having psychiatric comorbidities increased the odds of having a gap. CONCLUSIONS: Gaps in Medicaid coverage are associated with being a high utilizer during covered periods. Specific groups could be targeted with interventions to reduce churning.

Using Community-Based System Dynamics to Address Structural Racism in Community Health Improvement.

CONTEXT: Structural racism is a profound determinant of health resulting in pervasive health inequities for people of color. Despite the recognition of structural racism as a complex, dynamic system, we lack a shared vision of the system that would enable identification of solutions for equitable systems transformation. POLICY: Through a public health-led community health improvement planning process, a cross-sector consortium implemented community-based system dynamics to provide a systems science lens to guide efforts to eliminate structural racism. IMPLEMENTATION: In group model building sessions involving diverse stakeholders, community-based system dynamics was used to bring together cross-sector stakeholders to create causal loop diagrams of the system of structural racism. Participants identified potential leverage points for actionable focus to eliminate structural racism. EVALUATION: Causal loop diagrams of structural racism generated through group model building demonstrate complex dynamics in the areas of criminal justice, education and economic opportunity, health and health care, quality of life, racial trauma and healing, and a promising system transformative solution through perspective transformation. DISCUSSION: Community-based system dynamics, employed in the context of local community health improvement planning, engages stakeholders in systems thinking through sharing lived experience to create system maps of structural racism and identify leverage points and transportable solutions that foster health equity. These informal maps serve as the foundation for formal computer simulation models that will guide systemic action on high-yield, community-driven solutions to eliminate structural racism.

ICD-10 Z-Code Health-Related Social Needs and Increased Healthcare Utilization.

INTRODUCTION: Health-related social needs are known drivers of health and health outcomes, yet work to date to examine health-related social needs using ICD-10 Z-codes remains limited. This study seeks to evaluate the differences in the prevalence of conditions as well as utilization and cost between patients with and without health-related social needs. METHODS: Using the 2017 Florida State Emergency Department and State Inpatient Databases, this study identified patients with documented health-related social needs using ICD-10 Z-codes. The prevalence ratio was calculated for 14 conditions that are the leading causes of mortality and economic costs. In addition, ratios for the median total number of negative health events and total annual costs between patients with health-related social needs and those without health-related social needs across these conditions were calculated. Data analysis was conducted in 2021. RESULTS: Of 4,477,772 patients, 46,081 (1.0%) had documented health-related social needs and had 4 times the negative health events and 9.3 times the total annual costs. Trends of increased negative health events and costs were seen across all examined conditions; patients with health-related social needs had 2.5-3.5 times the negative health events and 2-18 times greater total costs. The biggest difference in negative health events was seen in patients with unintentional injuries and depression and psychoses (3.5 times for patients with health-related social needs), whereas the biggest difference in total costs was for unintentional injuries (18.4 times for patients with health-related social needs). CONCLUSIONS: This study shows the increased prevalence of numerous high-priority conditions as well as increased utilization and costs among patients with documented health-related social needs.

Burden of Chronic and Acute Conditions and Symptoms in People With Epilepsy.

BACKGROUND AND OBJECTIVES: People with epilepsy, one-third of whom in the United States are on Medicaid, experience a wide range of chronic and physical comorbidities that influence their care and outcomes. In this study, we examine the burden and racial/ethnic disparities of chronic and acute conditions, injuries, and symptoms in a large and diverse group of people with epilepsy on Medicaid. METHODS: Using 5 years of Medicaid claims data, we identified adults with epilepsy and used all available claims and diagnoses to identify each person's Clinical Classification Codes groups diagnosed during the study period. Using association rule mining, we identified the top combinations of conditions and stratified these by race/ethnicity to identify potential prevalence disparities. We examined the top combinations of conditions in high utilizers; that is, individuals in the top quartile of hospitalizations and emergency department visits. RESULTS: Among 81,963 patients, the most common conditions were anxiety and mood disorders (46.5%), hypertension (36.9%), back problems (35.2%), developmental disorders (31.6%), and headache (29.5%). When examining combinations of conditions, anxiety and mood disorders continued to have an outsized prevalence, appearing in nearly every combination. There were notable disparities in disease burden, with American Indians and Alaskan Natives having a substantially higher prevalence of developmental disorders, while Black individuals had a higher prevalence of hypertension. These disparities persisted to the higher-order combinations that included these conditions. High utilizers had a much higher disease burden, with 75.8% having an anxiety or mood disorder, as well as a higher burden of injuries. DISCUSSION: This study shows a high prevalence of psychiatric and physical conditions and identifies racial and ethnic disparities affecting people with epilepsy. Targeting interventions to consider the comorbidities, race, and ethnicity has potential to improve clinical care and reduce disparities.

Simple Rules That Guide Generalist and Specialist Care.

The sometimes-paradoxical emergent behavior of complex systems may be explained by the interaction of simple rules. The paradox of primary care-that systems based on primary care have healthier populations, fewer health inequities, lower health care expenditures, and better system-level evidence-based disease care, despite less evidence-based care for individual diseases-may be explained by the iterative interaction among three simple rules that describe the generalist approach: (1) Recognize a broad range of problems/opportunities; (2) Prioritize attention and action with the intent of promoting health, healing, and connection; and (3) Personalize care based on the particulars of the individual or family in their local context. These are complemented by three simple rules for specialist care that represent current approaches to quality and health care system improvement: (1) Identify and classify disease for management; (2) Interpret through specialized knowledge; (3) Generate and carry out a management plan. Health care systems that support the enactment of the simple rules of the generalist approach are likely to have more effective primary and specialty care, and greater population health, equity, quality, and sustainable cost.

Shared Language for Shared Work in Population Health.

People working on behalf of population health, community health, or public health often experience confusion or ambiguity in the meaning of these and other common terms-the similarities and differences and how they bear on the tasks and division of labor for care delivery and public health. Shared language must be clear enough to help, not hinder people working together as they ultimately come to mutual understanding of roles, responsibilities, and actions in their joint work. Based on an iterative lexicon development process, the authors developed and propose a definitional framework as an aid to navigating among related population and community health terms. These terms are defined, similarities and differences clarified, and then organized into 3 categories that reflect goals, realities, and ways to get the job done. Goals include (a) health as well-being for persons, (b) population health as that goal expressed in measurable terms for groups, and (c) community health as population health for particular communities of interest, geography, or other defining characteristic-groups with shared identity and particular systemic influences on health. Realities are social determinants as influences, health disparities as effects, and health equity as both a goal and a design principle. Ways to get the job done include health care delivery systems for enrollees and public health in population-based civic activities-with a broad zone of collaboration where streams of effort converge in partnership with served communities. This map of terms can enable people to move forward together in a broad zone of collaboration for health with less confusion, ambiguity, and conflict.

Structural racism and risk of SARS-CoV-2 in pregnancy.

BACKGROUND: Structural racism leads to adverse health outcomes, as highlighted by inequities in COVID-19 infections. We characterized Black/White disparities among pregnant women with SARS-CoV-2 in Cuyahoga County which has some of the most extreme health disparities in the U.S., such as a rate of Black infant mortality that is three times that of White counterparts. METHODS: This was a retrospective cohort study using data collected as part of public health surveillance between March 16, 2020 until October 1, 2020. This study aimed to compare Black and Non-Black pregnant women infected with SARS-CoV-2 to understand how the distribution of risk factors may differ by race. Outcomes included age, gestational age at infection, medical co-morbidities, exposure history, socio-economic status, occupation, symptom severity and pregnancy complications. FINDINGS: One hundred and sixty-two women were included. 81 (50%) were Black, 67 (41%) White, 9 (0·05%) Hispanic, 2 (0·01%) Asian; and three did not self-identify with any particular race. More than half who supplied occupational information (n = 132) were essential workers as classified by the CDC definition (55%, n = 73). Black women were younger (p = 0·0062) and more likely to identify an occupational contact as exposing them to SARS-CoV-2 (p = 0·020). Non-Black women were more likely to work from home (p = 0·018) and indicate a personal or household contact as their exposure (p = 0·020). Occupation was a risk factor for severe symptoms (aOR 4·487, p = 0·037). Most Black women lived in areas with median income <$39,000 and Black women were more likely to have a preterm delivery (22·2% versus 0%, p = 0·026). INTERPRETATION: Many pregnant women infected by SARS-CoV-2 are essential workers. Black women are more likely than White counterparts to have occupational exposure as the presumed source for their infection. Limitations in occupational options and controlling risk in these positions could be related to lower socio-economic status, resulting from a long history of structural racism in Cuyahoga County as evidenced by redlining and other policies limiting opportunities for people of color. FUNDING: none.