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Completeness and Quality of Data for Children in Medicaid Comprehensive Managed Care Compared to Fee-for-Service,
Kristen Lloyd1, Sanika Rege1, Stephen Crystal1
1Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, New Jersey, USA.
Insights
Medicaid managed care data for children shows improved completeness and quality over time. This allows for larger studies on publicly insured children's health services and epidemiology.
Area of Science:
- Health Services Research
- Public Health
- Health Informatics
Background:
- Medicaid managed care enrollment for children has grown significantly.
- Understanding the quality of Medicaid research files is crucial for accurate analysis.
- Fee-for-service (FFS) data has traditionally been the benchmark for Medicaid research.
Purpose of the Study:
- To compare data completeness and quality between comprehensive managed care (CMC) and fee-for-service (FFS) Medicaid programs for children.
- To assess the suitability of CMC data for research purposes.
- To identify trends in data quality over time.
Main Methods:
- Utilized national Medicaid inpatient, other services, and pharmacy files from 2001-2019.
- Compared CMC-enrolled children in states with ≥10% CMC enrollment to FFS data.
- Assessed data completeness (proportion with claims, mean claims) and quality (coding, dispensing information).
Main Results:
- Over 70% of state-years met completeness and quality criteria for CMC data, increasing to 83.8% by 2019.
- High comparability between CMC and FFS data was observed: 92.7% for inpatient completeness and 96.9% for prescription quality.
- Significant improvements in CMC data completeness and quality were noted over the study period.
Conclusions:
- Comprehensive managed care data for children in Medicaid is increasingly robust and comparable to FFS data.
- Improved data quality in CMC programs enhances opportunities for large-scale research on publicly insured children.
- Future research can leverage the growing volume and quality of CMC data to expand understanding of children's health services.
Objective:
To compare the data in national Medicaid research files for children enrolled in comprehensive managed care (CMC) vs. fee-for-service (FFS).
Study Setting And Design:
This observational study utilized inpatient, other services, and pharmacy files in national Medicaid data from 2001 to 2019. CMC-enrolled children in state-years with ≥ 10% CMC enrollment were compared on several measures to yearly FFS data across all available states. Completeness measures were the proportion with any claim and mean claims per enrollee. Quality measures were the proportion of inpatient and other services claims with primary diagnosis and procedure codes and the proportion of prescription claims with fill dates, National Drug Codes, days supplied, and quantity dispensed. The range of acceptable values for each measure was defined as overall FFS mean ± 2 standard deviations.
Data Sources And Analytic Sample:
We analyzed secondary MAX/TAF data on 45 states from 2001 to 2013 and 50 states and DC from 2014 to 2019. The sample included children ages 0-17 with continuous calendar-year enrollment in Medicaid and/or Medicaid-expansion CHIP with full Medicaid benefits and not dually enrolled in Medicare.
Principal Findings:
The sample included 368.7 million person-years across 888 state-years. Three hundred thirty-eight state-years (38.1%) had < 10% CMC enrollment. Of 550 remaining state-years, 70%, representing ~59% of all enrolled children, met criteria for both completeness and quality in all three files, increasing from 35.7% of states in 2001 to 83.8% of states in 2019. The percentages of state-years with comparable CMC/FFS data for completeness measures were 92.7% inpatient, 86.0% other services, and 87.3% prescription. For quality measures, these proportions were 88.5% inpatient, 95.6% other services, and 96.9% prescription.
Conclusions:
Growth in Medicaid-managed care over the last two decades, coupled with observed improvements in CMC data quality, presents opportunities to increase the sample size and scope of epidemiologic and health services research on publicly insured children.
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