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Medicaid policy data for evaluating eligibility and programmatic changes

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...

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Autores principales: Shafer, Paul R., Katchmar, Amanda, Callori, Steven, Alam, Raisa, Patel, Roshni, Choi, Sugy, Auty, Samantha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546693/
https://www.ncbi.nlm.nih.gov/pubmed/37789360
http://dx.doi.org/10.1186/s13104-023-06525-6
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author Shafer, Paul R.
Katchmar, Amanda
Callori, Steven
Alam, Raisa
Patel, Roshni
Choi, Sugy
Auty, Samantha
author_facet Shafer, Paul R.
Katchmar, Amanda
Callori, Steven
Alam, Raisa
Patel, Roshni
Choi, Sugy
Auty, Samantha
author_sort Shafer, Paul R.
collection PubMed
description 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).
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spelling pubmed-105466932023-10-04 Medicaid policy data for evaluating eligibility and programmatic changes Shafer, Paul R. Katchmar, Amanda Callori, Steven Alam, Raisa Patel, Roshni Choi, Sugy Auty, Samantha BMC Res Notes Data Note 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). BioMed Central 2023-10-03 /pmc/articles/PMC10546693/ /pubmed/37789360 http://dx.doi.org/10.1186/s13104-023-06525-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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.
spellingShingle Data Note
Shafer, Paul R.
Katchmar, Amanda
Callori, Steven
Alam, Raisa
Patel, Roshni
Choi, Sugy
Auty, Samantha
Medicaid policy data for evaluating eligibility and programmatic changes
title Medicaid policy data for evaluating eligibility and programmatic changes
title_full Medicaid policy data for evaluating eligibility and programmatic changes
title_fullStr Medicaid policy data for evaluating eligibility and programmatic changes
title_full_unstemmed Medicaid policy data for evaluating eligibility and programmatic changes
title_short Medicaid policy data for evaluating eligibility and programmatic changes
title_sort medicaid policy data for evaluating eligibility and programmatic changes
topic Data Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10546693/
https://www.ncbi.nlm.nih.gov/pubmed/37789360
http://dx.doi.org/10.1186/s13104-023-06525-6
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