Diversity of the US Public Health Workforce Pipeline (2016-2020): Role of Academic Institutions.

Objectives. To develop a diversity index (DI) comparing the diversity of graduates across public health schools and programs in the United States and to examine characteristics associated with institutions' graduate diversity. Methods. We analyzed longitudinal data from the Association of Schools and Programs of Public Health (ASPPH) across 5 academic years (2016-2017 to 2020-2021) for 109 ASPPH members. The outcome was the percentage of underrepresented minority (URM) students among those with bachelor's and graduate degrees in public health. The DI was constructed by dividing the percentage of URM graduates by the percentage of URM residents 20 to 35 years of age in the state where the ASPPH member was located. Results. The mean DI score increased from 0.7 in 2016 to 0.8 in 2020, but URM students remain underrepresented. A 1-percentage-point increase in the proportion of URM faculty members was associated with a 0.7-percentage-point increase in the proportion of URM graduates (P < .001). Conclusions. Although the diversity of the public health educational pipeline shows an upward trend, racial/ethnic minority students remain underrepresented in public health. We found that institutional characteristics such as faculty diversity, program degree level, and area of study were associated with student diversity. (Am J Public Health. 2023;113(9):1000-1008. https://doi.org/10.2105/AJPH.2023.307352).

Health care provider movement increased through COVID-19.

COVID-19 placed unprecedented strain on the health workforce, raising concerns of increasing worker turnover and attrition. This study explores the use of 2 publicly available Medicare datasets-Provider Enrollment, Chain, and Ownership System (PECOS) and Doctors and Clinicians-to track provider movement across states and organizations from 2017 to 2023. We found an increase in state-to-state movement of providers post-COVID-19, with an initial spike in physician movement in the first year (April 2020 to March 2021). Movement varied across specialties and professions. Between organizations, we saw an initial increase in movement for family physicians but not internal medicine physicians. Overall, provider movement was generally to larger organizations. Our study finds increasing movement of providers in the post-COVID-19 period through the novel use of 2 publicly available Medicare datasets. Tracking health care workforce movement closer to real time is important to understand a changing workforce-with differences across communities-and to guide policies to ensure sufficient workforce and prevent worsening disparities over time.

Telehealth Use and Access to Care for Underserved Populations Before and During the COVID-19 Pandemic.

While several studies have documented the rapid growth in telehealth visits during the pandemic, none have examined its relationship with greater overall access to care among vulnerable populations. We use Association of American Medical Colleges' Consumer Survey data to examine the relationship between access to care and telehealth use before and during the pandemic. The proportion of survey respondents who were always able to get medical care when needed was slightly lower in 2020 compared with prior years while telehealth use rose dramatically. Disparities in telehealth use for Medicaid beneficiaries and rural respondents disappeared during the pandemic, but remained for lower-income populations. Before the pandemic, telehealth use was associated with greater access, but not during the pandemic-when it appears to have become a substitute for in-person. After the pandemic, telehealth could once again be an opportunity to supplement access to care, if telehealth policies enacted during the pandemic are made permanent.

The Use of Interpreters in Health Centers: A Mixed-Methods Analysis.

Health centers serve millions of patients with limited English proficiency (LEP) through highly variable language services programs that reflect patient language preferences, the availability of bilingual staff, and very limited sources of third-party funding for interpreters. We conducted a mixed-methods study to understand interpreter services delivery in federally qualified health centers during 2009-2019. Using the Uniform Data System database, we conducted a quantitative analysis to determine characteristics of centers with and without interpreters, defined as staff whose time is devoted to translation and/or interpreter services. We also analyzed Medicaid-relevant policies' association with health centers' interpreter use. The qualitative component used a sample of 28 health centers to identify interpreter services models. We found that the use of interpreters, as measured by the ratio of interpreter full-time equivalents per patients with LEP, decreased between 2009 and 2019. We did not find statistically significant relationships between interpreter staffing and number of patients with LEP served, or in our examination of Medicaid-relevant policies. Our qualitative analysis uncovered homegrown models with varying program characteristics. Key themes included the critical role of bilingual staff, inconsistent interpreter training, and the reasonably smooth transition to virtual interpretation during COVID-19.

Association between state payment parity policies and telehealth usage at community health centers during COVID-19.

OBJECTIVE: We study the association between payment parity policies and telehealth utilization at community health centers (CHCs) before, during, and after the onset of the pandemic. MATERIALS AND METHODS: We use aggregated, de-identified data from FAIR Health for privately insured patients at CHC sites. Descriptive statistics and time trends are calculated. Logistic regression models were used to quantify the factors associated with telehealth utilization for each of our time periods: 1) pre-pandemic (March-June 2019), 2) immediate pandemic response (March-June 2020), and 3) sustained pandemic response (March-June 2021). RESULTS: Telehealth usage rates at CHC sites surged to approximately 61% in April 2020. By April 2021, only 29% of CHC sites in states without payment parity policies used telehealth versus 42% in states without. Controlling for other characteristics, we find that CHC sites in states with payment parity were more likely to utilize telehealth one year after the onset of the pandemic (OR:1.740, p<0.001) than states without, but did not find this association in 2019 or 2020. DISCUSSION: The public health emergency drove widespread use of telehealth, making the virtual care environment inherently different in 2021 than in 2019. Due to the unique fiscal constraints facing CHCs, the financial sustainability of telehealth may be highly relevant to the relationship between telehealth utilization and payment parity we find in this paper. CONCLUSION: Supportive payment policy and continued investments in broadband availability in rural and undeserved communities should enable CHCs to offer telehealth services to populations in these areas.

Quantification of Neighborhood-Level Social Determinants of Health in the Continental United States.

IMPORTANCE: An association between social and neighborhood characteristics and health outcomes has been reported but remains poorly understood owing to complex multidimensional factors that vary across geographic space. OBJECTIVES: To quantify social determinants of health (SDOH) as multiple dimensions across the continental United States (the 48 contiguous states and the District of Columbia) at a small-area resolution and to examine the association of SDOH with premature mortality within Chicago, Illinois. DESIGN, SETTING, AND PARTICIPANTS: In this cross-sectional study, census tracts from the US Census Bureau from 2014 were used to develop multidimensional SDOH indices and a regional typology of the continental United States at a small-area level (n = 71 901 census tracts with approximately 312 million persons) using dimension reduction and clustering machine learning techniques (unsupervised algorithms used to reduce dimensions of multivariate data). The SDOH indices were used to estimate age-adjusted mortality rates in Chicago (n = 789 census tracts with approximately 7.5 million persons) with a spatial regression for the same period, while controlling for violent crime. MAIN OUTCOMES AND MEASURES: Fifteen variables, measured as a 5-year mean, were selected to characterize SDOH as small-area variations for demographic characteristics of vulnerable groups, economic status, social and neighborhood characteristics, and housing and transportation availability at the census-tract level. This SDOH data matrix was reduced to 4 indices reflecting advantage, isolation, opportunity, and mixed immigrant cohesion and accessibility, which were then clustered into 7 distinct multidimensional neighborhood typologies. The association between SDOH indices and premature mortality (defined as death before age 75 years) in Chicago was measured by years of potential life lost and aggregated to a 5-year mean. Data analyses were conducted between July 1, 2018, and August 30, 2019. RESULTS: Among the 71 901 census tracts examined across the continental United States, a median (interquartile range) of 27.2% (47.1%) of residents had minority status, 12.1% (7.5%) had disabilities, 22.9% (7.6%) were 18 years and younger, and 13.6% (8.1%) were 65 years and older. Among the 789 census tracts examined in Chicago, a median (interquartile range) of 80.4% (56.3%) of residents had minority status, 10.2% (8.2%) had disabilities, 23.2% (10.9%) were 18 years and younger, and 9.5% (7.1%) were 65 years and older. Four SDOH indices accounted for 71% of the variance across all census tracts in the continental United States in 2014. The SDOH neighborhood typology of extreme poverty, which is of greatest concern to health care practitioners and policy advocates, comprised only 9.6% of all census tracts across the continental United States but characterized small areas of known public health crises. An association was observed between all SDOH indices and age-adjusted premature mortality rates in Chicago (R2 = 0.63; P < .001), even after accounting for violent crime and spatial structures. CONCLUSIONS AND RELEVANCE: The modeling of SDOH as multivariate indices rather than as a singular deprivation index may better capture the complexity and spatial heterogeneity underlying SDOH. During a time of increased attention to SDOH, this analysis may provide actionable information for key stakeholders with respect to the focus of interventions.