Disaggregating Health Official Statistics by Integrating Data From Multiple Sources

Andreea Erciulescu Co-Author
Westat
 
Oksana Balabay Speaker
Westat
 
Thursday, Aug 7: 8:35 AM - 9:05 AM
Invited Paper Session 
Music City Center 

Description

Disaggregated statistics help improve the description of the society. However, survey estimates are subject to larger uncertainty at finer levels than at higher levels, and often not even available at fine levels. The Behavioral Risk Factor Surveillance System (BRFSS) is considered the nation's premier system collecting health data from individuals in the US using telephone surveys. Among the BRFSS official statistics, state-level estimates are available for two related health prevalence quantities: the prevalence of having a personal doctor and the prevalence of having health insurance coverage. No county-level BRFSS estimates are released for these quantities. In addition, county-level estimates for the prevalence of having health insurance coverage are also available from the US. Small Area Health Insurance Estimates (SAHIE) program. This article addresses the disaggregation of the state-level prevalence of having a personal doctor to the county level, by using the state-level relationship between the two BRFSS prevalence variables and the county-level bridge between the BRFSS and the SAHIE prevalence of having health insurance coverage. Using 2018 public-use data, county-level model estimates are produced for both prevalence variables and on both BRFSS and SAHIE scales, improving the usability of the BRFSS public-use data.

Keywords

Hierarchical Bayes

prevalence of having a personal doctor

prevalence of having health insurance coverage

small area estimation

multilevel models