ABSTRACT
OBJECTIVE: To analyze health care disparities in pediatric quality of care measures and determine the impact of data imputation. DATA SOURCES: Five HEDIS measures are calculated based on 2012 administrative data for 145,652 children in two public insurance programs in Florida. METHODS: The Bayesian Improved Surname and Geocoding (BISG) imputation method is used to impute missing race and ethnicity data for 42 percent of the sample (61,954 children). Models are estimated with and without the imputed race and ethnicity data. PRINCIPAL FINDINGS: Dropping individuals with missing race and ethnicity data biases quality of care measures for minorities downward relative to nonminority children for several measures. CONCLUSIONS: These results provide further support for the importance of appropriately accounting for missing race and ethnicity data through imputation methods.
Subject(s)
Ethnicity/statistics & numerical data , Healthcare Disparities/ethnology , Pediatrics/statistics & numerical data , Quality of Health Care/statistics & numerical data , Racial Groups/statistics & numerical data , Adolescent , Bayes Theorem , Benchmarking , Child , Child, Preschool , Florida , Geographic Mapping , Humans , Infant , Insurance Claim Review/statistics & numerical data , Quality Indicators, Health Care , United States , Young AdultABSTRACT
In 2006, Florida began a pilot program under a federal Medicaid waiver to reform its Medicaid program in Broward and Duval counties. The Children's Medical Services Network, a subcontracted health care delivery system for Florida's children with special health care needs (CSHCN) enrolled in public insurance programs, participated in Medicaid reform through an Integrated Care System (ICS) for its enrollees. The ICS constitutes a significant departure from the subcontracted fee-for-service system used to deliver care to CSHCN in the non-reform counties, and limited information exists about its impact. The purpose of this study was to assess the effects of the ICS on Medicaid utilization among CSHCN in Broward and Duval. Administrative data from 3,947 CSHCN in Broward and Duval, and two control counties, enrolled in Florida's Medicaid program between 2006 and 2008 were used for analyses. Fixed effects negative binomial models were used to estimate the impact of the ICS on inpatient, outpatient, and emergency department utilization. Results show the number of outpatient visits decreased by 9 % in Broward and 16 % in Duval. The number of inpatient stays decreased in Duval by 35 %. Emergency room utilization increased slightly in Broward, although the estimate was not significant. Results suggest that managed care under the ICS has impacted utilization, most significantly for inpatient care. The ICS presents a viable model of managed care for CSHCN that could result in cost savings. Results should be interpreted with care because the full effects of the ICS implementation may take more time to materialize.