Skip to main content

Medicaid policy data for evaluating eligibility and programmatic changes

Abstract

Objectives

Medicaid and the Children’s Health Insurance Program (CHIP) provide health insurance coverage to more than 90 million Americans as of early 2023. There is substantial variation in eligibility criteria, application procedures, premiums, and other programmatic characteristics across states and over time. Analyzing changes in Medicaid policies is important for state and federal agencies and other stakeholders, but such analysis requires data on historical programmatic characteristics that are often not available in a form ready for quantitative analysis. Our objective is to fill this gap by synthesizing existing qualitative policy data to create a new data resource that facilitates Medicaid policy research.

Data description

Our source data were the 50-state surveys of Medicaid and CHIP eligibility, enrollment, and cost-sharing policies, and budgets conducted near annually by KFF since 2000, which we coded through 2020. These reports are a rich source of point-in-time information but not operationalized for quantitative analysis. Through a review of the measures captured in the KFF surveys, we developed five Medicaid policy domains with 122 measures in total, each coded by state-quarter—1) eligibility (28 measures), 2) enrollment and renewal processes (39 measures), 3) premiums (16 measures), 4) cost-sharing (26 measures), and 5) managed care (13 measures).

Peer Review reports

Objective

Medicaid and the Children’s Health Insurance Program (CHIP) provide health insurance coverage to more than 90 million Americans as of early 2023 [1]. There is substantial variation in eligibility criteria, application procedures, premiums, and other programmatic characteristics across states and over time. States use waiver authority provided in the Social Security Act to propose wide-ranging demonstration projects to reshape their programs [2]. Programmatic differences between state Medicaid programs may influence Medicaid enrollment, access to health care, and downstream health outcomes. Indeed, considerable cross-state variation in eligibility and administrative burdens to get and remain enrolled have often yielded inequities in participation and outcomes within the program [3,4,5]. Yet, the Government Accountability Office has noted the lack of rigorous evaluation required by Centers for Medicare and Medicaid Services (CMS) or conducted by states [6].

As such, analysis of Medicaid policy changes is important for state and federal agencies and other stakeholders, and is therefore critical and highly fundable work. However, this requires an understanding of historical eligibility criteria and programmatic characteristics that are not readily available in a form easily used for quantitative analysis. An example of this, published in 2015, used sensitivity to historical Medicaid eligibility changes to predict effects of the 2014 Medicaid expansion on use of care in the Veterans Health Administration, in which the authors noted that it was “based on historical data available only through 2008” [7].

Our objective is to fill this gap by synthesizing existing qualitative policy data to create a new data resource that facilitates Medicaid policy research. These data can be easily combined with health insurance claims, surveys, or other forms of quantitative data. As novel Medicaid claims data have become available from CMS [8], freely accessible Medicaid policy data will be useful for researchers.

Data description

Our historical source data consists of 50-state surveys by KFF on Medicaid and CHIP eligibility, enrollment, and cost-sharing policies, and Medicaid budgets. These surveys have been conducted annually by KFF since 2000 and were coded by our team through 2020 [9, 10]. These reports are a rich source of point-in-time information, which KFF uses to support its descriptive reports and interactive data visualizations on their website. Our coding entailed parsing text, maps, and tables from these annual reports into quantitative data (e.g., federal poverty level eligibility thresholds by category of Medicaid eligibility – continuous variable; availability of online application – binary variable). These data can supplement gaps in existing Medicaid policy data sets that are more narrowly focused and/or capture different timeframes [11,12,13].

Our research team developed five policy domains from a thorough review of the KFF surveys, resulting in a total of 122 measures—1) eligibility (28 measures), 2) enrollment and renewal processes (39 measures), 3) premiums (16 measures), 4) cost-sharing (26 measures), and 5) managed care (13 measures). To manage and house the Medicaid policy data, we used MonQcle (https://monqcle.com), a legal epidemiology tool available through the Center for Public Health Law Research at Temple University. Our team used double data entry of each measure with consensus meetings to address any inconsistencies in coding when beginning the project (approximately 4% of records), with the remainder being entered by a single coder and reviewed for accuracy by another. We coded each measure by state-quarter, capturing the timing of policy changes, and created domain-specific Excel, Stata, and SAS longitudinal data sets that researchers can merge on to other data sets (Table 1) [14].

Table 1 Overview of data files/data sets

Limitations

Our measures are not exhaustive of all policies represented in the historical source data or of all Medicaid policies that may warrant evaluation. Our measure set and coded data were limited by what was captured in the historical source data available. Due to coding by year and quarter based on the KFF surveys, specific timing of policy passage and/or implementation may differ slightly from how they are captured in our data. Our measures were either double entered, or coded from the source data and reviewed by another coder for concordance; however, there still may be errors. The accuracy and consistency of our data also depend on the reliability of the information provided in the source data. Not all measures were available, or applicable, for all states and/or years.

Data Availability

The data described in this Data note can be freely and openly accessed on Harvard Dataverse under https://doi.org/10.7910/DVN/KAYSAB. Please see Table 1 and reference [14] for details and links to the data.

Abbreviations

CHIP:

Children’s Health Insurance Program

CMS:

Centers for Medicare and Medicaid Services

References

  1. Center for Medicare and Medicaid Services. February 2023 Medicaid & CHIP Enrollment Data Highlights [Internet]. n.d. [cited 2023 Jun 22]. Available from: https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html.

  2. Center for Medicare and Medicaid Services. About Sect. 1115 Demonstrations [Internet]. n.d. [cited 2023 Jun 22]. Available from: https://www.medicaid.gov/medicaid/section-1115-demonstrations/about-section-1115-demonstrations/index.html.

  3. Michener J. Fragmented Democracy: Medicaid, Federalism, and Unequal Politics [Internet]. Cambridge University Pres; 2018 [cited 2020 Dec 17]. Available from: https://doi.org/10.1017/9781108224987.

  4. Herd P, Moynihan D. Administrative Burdens in Health Policy. J Health Hum Serv Adm. 2020;3–16.

  5. Sofer N. Work requirements won’t affect the debt ceiling — but they will stir up racist narratives. The Emancipator [Internet]. 2023 May 31 [cited 2023 Jun 8]; Available from: https://www.bostonglobe.com/2023/05/31/opinion/work-requirements-wont-affect-debt-ceiling-they-will-stir-up-racist-narratives/.

  6. Government Accountability Office. Evaluations Yielded Limited Results, Underscoring Need for Changes to Federal Policies and Procedure [Internet]. 2018 [cited 2023 Jun 22]. Available from: https://www.gao.gov/products/gao-18-220.

  7. Frakt AB, Hanchate A, Pizer SD. The effect of Medicaid expansions on demand for care from the Veterans Health Administration. Healthc Amst Neth. 2015;3(3):123–8.

    Article  Google Scholar 

  8. Center for Medicare and Medicaid Services. CMS Takes Historic Steps to Increase Public Access to Medicaid and CHIP Data [Internet]. 2019 [cited 2023 Jun 22]. Available from: https://www.cms.gov/newsroom/press-releases/cms-takes-historic-steps-increase-public-access-medicaid-and-chip-data.

  9. KFF. Annual Updates on Eligibility Rules, Enrollment and Renewal Procedures, and Cost-Sharing Practices in Medicaid and CHIP [Internet]. 2023 [cited 2023 Jun 22]. Available from: https://www.kff.org/medicaid/report/annual-updates-on-eligibility-rules-enrollment-and-renewal-procedures-and-cost-sharing-practices-in-medicaid-and-chip/.

  10. KFF. 50-State Medicaid Budget Survey Archives [Internet]. 2022 [cited 2023 Jun 27]. Available from: https://www.kff.org/medicaid/report/medicaid-budget-survey-archives/.

  11. Burns M, Dague L. Medicaid Waiver Dataset: Coverage for Childless Adults, 1996–2014 [Internet]. 2016 [cited 2023 Jun 22]. Available from: https://www.disc.wisc.edu/archive/Medicaid/index.html.

  12. Urban Institute. TRIM3 Documentation. 2012 [cited 2023 Jun 22]. Available from: https://boreas.urban.org/T3Technical.php.

  13. Fox A. State Safety-net Generosity Index [Internet]. n.d. [cited 2023 Jun 22]. Available from: https://safetynetgenerosity.com.

  14. Shafer P, Katchmar A, Callori S, Alam R, Patel R, Choi S, Auty S. Medicaid policy data for evaluating eligibility and programmatic changes. Harv Dataverse. 2023. https://doi.org/10.7910/DVN/KAYSAB.

    Article  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This work was supported by an Early Career Catalyst Award from the Boston University School of Public Health idea hub. The funder had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

PS conceived of the project, obtained funding, oversaw policy data collection, and wrote the first draft of the manuscript. AK, SC1, RA, RP, SC2, and SA contributed to measure development, coded data, and/or substantially revised the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Paul R. Shafer.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shafer, P.R., Katchmar, A., Callori, S. et al. Medicaid policy data for evaluating eligibility and programmatic changes. BMC Res Notes 16, 250 (2023). https://doi.org/10.1186/s13104-023-06525-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13104-023-06525-6

Keywords