Evidence map›Paper›PMID 39748217›Full record

Observational studyHealth services research2025

Completeness and quality of comprehensive managed care data compared with fee-for-service data in national Medicaid claims from 2001 to 2019.

Hillary Samples, Kristen Lloyd, Radha Ryali, Silvia S Martins, Magdalena Cerdá, Deborah Hasin, Stephen Crystal, Mark Olfson

Abstract readObservational StudyComparative Study
In one paragraph

Observational study in Health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Geographic and racial/ethnic patterns of polysomnography use among children enrolled in Medicaid, 2017-2019.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2026
    Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hillary SamplesInstitute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, New Jersey, USA.ORCID https://orcid.org/0000-0001-5773-3705
Kristen LloydInstitute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, New Jersey, USA.ORCID https://orcid.org/0000-0001-8057-1003
Radha RyaliInstitute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, New Jersey, USA.
Silvia S MartinsDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA.
Magdalena CerdáDepartment of Population Health, NYU Grossman School of Medicine, New York, New York, USA.
Deborah HasinDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA.
Stephen CrystalInstitute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, New Jersey, USA.
Mark OlfsonDepartment of Psychiatry, New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, New York, USA.

Funding

Opioid Overdoses among Medicaid Beneficiaries: Predictors, Outcomes, and State Policy EffectsR01DA047347 · NIDA · RUTGERS, THE STATE UNIV OF N.J. · PI CRYSTAL, STEPHEN · 2019 to 2022
$3.1M
Multi-level associations between opioid use and overdose: Individual, clinical, and population-based risk factors for fatalityK01DA049950 · NIDA · RUTGERS BIOMEDICAL/HEALTH SCIENCES-RBHS · PI SAMPLES, HILLARY · 2020 to 2024
$981k
NIDA NIH HHS K01 DA049950NIDA NIH HHS K01DA049950NIDA NIH HHS R01 DA047347NIDA NIH HHS R01DA047347
6 · The paper itself

Abstract

objectiveTo evaluate the completeness and quality of Medicaid comprehensive managed care (CMC) data in national MAX/TAF research files. STUDY SETTING AND

designThis 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. DATA SOURCES AND ANALYTIC SAMPLE: 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. PRINCIPAL

findingsAcross 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.

conclusionsCompleteness 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.

Indexed as

Fee-for-Service PlansInsurance Claim ReviewManaged Care ProgramsMedicaidAdolescentAdultFemaleHumansMaleMiddle AgedUnited StatesYoung Adultdata accuracydata qualityfee‐for‐service plansmanaged care programsMedicaid

Identifiers

PMID39748217
PMCPMC12120513

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.