Samples Hillary, Lloyd Kristen, Ryali Radha, Martins Silvia S, Cerdá Magdalena, Hasin Deborah, Crystal Stephen, Olfson Mark
Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, New Jersey, USA.
Department of Health Behavior, Society and Policy, Rutgers School of Public Health, Piscataway, New Jersey, USA.
Health Serv Res. 2025 Jun;60(3):e14429. doi: 10.1111/1475-6773.14429. Epub 2025 Jan 2.
To evaluate the completeness and quality of Medicaid comprehensive managed care (CMC) data in national MAX/TAF research files.
This observational study compared CMC with fee-for-service (FFS) enrollee data in 2001-2019 Medicaid MAX/TAF inpatient, outpatient, and pharmacy files. Completeness was assessed as the proportion of enrollees with any claim and mean claims per enrollee with any claim. Quality was assessed as the proportion of inpatient and outpatient claims with primary diagnosis and procedure codes and the proportion of prescription drug claims with fill dates, National Drug Codes (NDC), days supplied, and quantity dispensed. Acceptable ranges for each study measure were defined as the national FFS mean ± 2 standard deviations.
We analyzed secondary data on 45 states from 2001 to 2013 (MAX) and 50 states and DC from 2014 to 2019 (TAF). The sample included adults aged 18-64 with continuous calendar-year enrollment who were eligible for full Medicaid benefits and ineligible for Medicare. We determined CMC enrollment rates and assessed data completeness and quality among state-years with ≥10% CMC penetration, comparing CMC with FFS enrollees.
Across 891 state-years, 194,364,647 enrollees met inclusion criteria. Of 540 state-years (60.6%) with ≥10% CMC enrollment, CMC data were largely comparable to national FFS distributions for all inpatient (n = 430; 79.6%), outpatient (n = 467, 86.5%), and prescription (n = 459, 85.0%) completeness criteria and for all inpatient (n = 449, 83.1%), outpatient (n = 511, 94.6%), and prescription (n = 528, 97.8%) quality criteria. Overall completeness (92.3%) and quality (84.6%) improved substantially by 2019.
Completeness and quality of CMC data were largely comparable to FFS data, with increasing state-years meeting criteria over time. Further research on national Medicaid populations should assess and address differences in data completeness and quality by plan type across states, over time, and in relation to specific study samples and measures of interest.
评估国家MAX/TAF研究文件中医疗补助综合管理式护理（CMC）数据的完整性和质量。
这项观察性研究比较了2001 - 2019年医疗补助MAX/TAF住院、门诊和药房文件中CMC与按服务收费（FFS）参保者的数据。完整性通过有任何索赔记录的参保者比例以及有任何索赔记录的参保者人均索赔次数来评估。质量通过有主要诊断和手术编码的住院和门诊索赔比例以及有配药日期、国家药品编码（NDC）、供应天数和配药量的处方药索赔比例来评估。每项研究指标的可接受范围定义为全国FFS均值±2个标准差。
我们分析了2001年至2013年45个州（MAX）以及2014年至2019年50个州和华盛顿特区（TAF）的二手数据。样本包括年龄在18 - 64岁、连续全年参保、有资格享受全额医疗补助福利且无资格享受医疗保险的成年人。我们确定了CMC参保率，并在CMC渗透率≥10%的州年中评估数据的完整性和质量，将CMC与FFS参保者进行比较。
在891个州年中，194,364,647名参保者符合纳入标准。在540个（60.6%）CMC参保率≥10%的州年中，CMC数据在所有住院（n = 430；79.6%）、门诊（n = 467，86.5%）和处方（n = 459，85.0%）完整性标准以及所有住院（n = 449，83.1%）、门诊（n = 511，94.6%）和处方（n = 528，97.8%）质量标准方面，与全国FFS分布情况基本相当。到2019年，总体完整性（92.3%）和质量（84.6%）有了显著提高。
CMC数据的完整性和质量与FFS数据基本相当，随着时间推移，符合标准的州年数量不断增加。关于全国医疗补助人群的进一步研究应评估并解决不同州在不同时间、针对特定研究样本和感兴趣的指标，按计划类型划分的数据完整性和质量差异。
