Dataset Information

Community residential segregation and the local supply of federally qualified health centers.

ABSTRACT:

Objective

To examine associations between community residential segregation by income and race/ethnicity, and the supply of federally qualified health centers (FQHCs) in urban areas.

Data sources and study setting

Area Resource File (2000-2007) linked with 2000 U.S. Census on U.S. metropolitan counties (N = 1,786).

Study design

We used logistic and negative binomial regression models with state-level fixed effects to examine how county-level characteristics in 2000 are associated with the presence of FQHCs in 2000, and with the increase in FQHCs from 2000 to 2007. Income and racial/ethnic residential segregation were measured by poverty and the non-white dissimilarity indices, respectively. Covariates included measures of federal criteria for medically underserved areas/populations.

Principal findings

Counties with a high non-white dissimilarity index and a high percentage of minorities were more likely to have an FQHC in 2000. When we examined the addition of new FQHCs from 2000 to 2007, the effects of both poverty and non-white dissimilarity indices were positive and significant.

Conclusions

Residential segregation likely produces geographic segregation of health services, such that provider maldistribution may explain the association between residential segregation and FQHC supply. Metropolitan areas that fail to achieve greater integration of poor and minority communities may require FQHCs to compensate for provider shortages.

SUBMITTER: Ko M

PROVIDER: S-EPMC3589965 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:IntroductionFederally Qualified Health Centers serve 29.8 million low-income patients across the U.S., many of whom have unaddressed social risks. In 2019, for the first time, data on social risk screening capabilities were collected from every U.S. Federally Qualified Health Center. The objectives of this study were to describe the national rates of social risk screening capabilities across Federally Qualified Health Centers, identify organizational predictors of screening, and assess between-state heterogeneity.MethodsUsing a 100% sample of U.S. Federally Qualified Health Centers (N=1,384, representing 29.8 million patients) from the 2019 Uniform Data System, the primary outcome was whether a Federally Qualified Health Center collected data on patients' social risk factors (yes/no). Summary statistics on the rates of social risk screening capabilities were generated in aggregate and by state. Linear probability models were then used to estimate the relationship between the probability of social risk screening and 7 key Federally Qualified Health Center characteristics (e.g., Federally Qualified Health Center size, Medicaid MCO contract, Medicaid accountable care organization presence). Data were analyzed in 2020‒2021.ResultsMost (71%) Federally Qualified Health Centers collected social risk data, with a between-state variation. The most common screener was the Protocol for Responding to and Assessing Patients' Assets Risks and Experiences (43% of Federally Qualified Health Centers that screened), whereas 22% collected social risk data using a nonstandardized screener. After adjusting for other characteristics, Federally Qualified Health Centers with social risk screening capabilities served more total patients, were more likely to be located in a state with a Medicaid accountable care organization, and were less likely to have an MCO contract.ConclusionsThere has been widespread adoption of social risk screening tools across U.S. Federally Qualified Health Centers, but between-state disparities exist. Targeting social risk screening resources to smaller Federally Qualified Health Centers may increase the adoption of screening tools.