Medicare and Medicaid Services
- kaggle.com
zipUpdated Apr 22, 2020+ more versions
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EmailClick to copy linkLink copiedCiteGoogle BigQuery (2020). Medicare and Medicaid Services [Dataset]. https://www.kaggle.com/datasets/bigquery/sdoh-hrsa-shortage-areaszip(0 bytes)Available download formatsDataset updatedApr 22, 2020AuthorsGoogle BigQueryDescriptionContext
This public dataset was created by the Centers for Medicare & Medicaid Services. The data summarize counts of enrollees who are dually-eligible for both Medicare and Medicaid program, including those in Medicare Savings Programs. “Duals” represent 20 percent of all Medicare beneficiaries, yet they account for 34 percent of all spending by the program, according to the Commonwealth Fund . As a representation of this high-needs, high-cost population, these data offer a view of regions ripe for more intensive care coordination that can address complex social and clinical needs. In addition to the high cost savings opportunity to deliver upstream clinical interventions, this population represents the county-by-county volume of patients who are eligible for both state level (Medicaid) and federal level (Medicare) reimbursements and potential funding streams to address unmet social needs across various programs, waivers, and other projects. The dataset includes eligibility type and enrollment by quarter, at both the state and county level. These data represent monthly snapshots submitted by states to the CMS, which are inherently lower than ever-enrolled counts (which include persons enrolled at any time during a calendar year.) For more information on dually eligible beneficiaries
Querying BigQuery tables
You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.sdoh_cms_dual_eligible_enrollment.
Sample Query
In what counties in Michigan has the number of dual-eligible individuals increased the most from 2015 to 2018? Find the counties in Michigan which have experienced the largest increase of dual enrollment households
duals_Jan_2015 AS ( SELECT Public_Total AS duals_2015, County_Name, FIPS FROM
bigquery-public-data.sdoh_cms_dual_eligible_enrollment.dual_eligible_enrollment_by_county_and_programWHERE State_Abbr = "MI" AND Date = '2015-12-01' ),duals_increase AS ( SELECT d18.FIPS, d18.County_Name, d15.duals_2015, d18.duals_2018, (d18.duals_2018 - d15.duals_2015) AS total_duals_diff FROM duals_Jan_2018 d18 JOIN duals_Jan_2015 d15 ON d18.FIPS = d15.FIPS )
SELECT * FROM duals_increase WHERE total_duals_diff IS NOT NULL ORDER BY total_duals_diff DESC
Medicaid Enrollment - New Adult Group
- catalog.data.gov
- data.virginia.gov
- +2more
Updated Feb 3, 2025+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteCenters for Medicare & Medicaid Services (2025). Medicaid Enrollment - New Adult Group [Dataset]. https://catalog.data.gov/dataset/medicaid-enrollment-new-adult-group-cb7e1Dataset updatedFeb 3, 2025Dataset provided byCenters for Medicare & Medicaid ServicesDescriptionTotal Medicaid Enrollees - VIII Group Break Out Report Reported on the CMS-64 The enrollment information is a state-reported count of unduplicated individuals enrolled in the state’s Medicaid program at any time during each month in the quarterly reporting period. The enrollment data identifies the total number of Medicaid enrollees and, for states that have expanded Medicaid, provides specific counts for the number of individuals enrolled in the new adult eligibility group, also referred to as the “VIII Group”. The VIII Group is only applicable for states that have expanded their Medicaid programs by adopting the VIII Group. This data includes state-by-state data for this population as well as a count of individuals whom the state has determined are newly eligible for Medicaid. All 50 states, the District of Columbia and the US territories are represented in these data. Notes: 1. “VIII GROUP” is also known as the “New Adult Group.” 2. The VIII Group is only applicable for states that have expanded their Medicaid programs by adopting the VIII Group. VIII Group enrollment information for the states that have not expanded their Medicaid program is noted as “N/A.”
Medi-Cal Enrollment by Eligibility Group
- data.chhs.ca.gov
- data.ca.gov
- +2more
csv, pdf, zipUpdated Jul 1, 2025+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteDepartment of Health Care Services (2025). Medi-Cal Enrollment by Eligibility Group [Dataset]. https://data.chhs.ca.gov/dataset/medi-cal-enrollment-by-eligibility-grouppdf, zip, csv(22656)Available download formatsDataset updatedJul 1, 2025AuthorsDepartment of Health Care ServicesDescriptionThis dataset includes the total number of individuals enrolled in Medi-Cal by eligibility group: Modified Adjusted Gross Income (MAGI), non-MAGI, and Children’s Health Insurance Program (CHIP). The groups are defined by the Centers for Medicare and Medicaid Services (CMS) Performance Indicators (CMSPI) reporting requirements. The Department of Health Care Services (DHCS) submits eligibility and enrollment data regarding Medicaid and CHIP monthly to CMS. The enrollment data represents enrollment totals as of 60 days after the eligibility month (indicated as “Reporting Period” in the dataset). CMS publishes the state total enrollments on the CMSPI website. The total enrollment comprises of individuals who are eligible for full scope Medi-Cal by MAGI – Child, MAGI – Adult, Non-MAGI Child, Non-MAGI Adult, and CHIP eligibility groups. DHCS does not report to CMS the total enrollment in limited scope Medi-Cal or state-only funded programs (indicated as the “Non-CMSPI” in the dataset).
Separate CHIP Enrollment by Month and State – Historic CAA/Unwinding Period
- catalog.data.gov
- healthdata.gov
- +1more
Updated Feb 3, 2025ShareFacebookTwitterEmailClick to copy linkLink copiedCiteCenters for Medicare & Medicaid Services (2025). Separate CHIP Enrollment by Month and State – Historic CAA/Unwinding Period [Dataset]. https://catalog.data.gov/dataset/separate-chip-enrollment-by-month-and-stateDataset updatedFeb 3, 2025Dataset provided byCenters for Medicare & Medicaid ServicesDescriptionThis historic dataset with total enrollment in separate CHIP programs by month and state was created to fulfill reporting requirements under section 1902(tt)(1) of the Social Security Act, which was added by section 5131(b) of subtitle D of title V of division FF of the Consolidated Appropriations Act, 2023 (P.L. 117-328) (CAA, 2023). For each month from April 1, 2023, through June 30, 2024, states were required to submit to CMS (on a timely basis), and CMS was required to make public, certain monthly data, including the total number of beneficiaries who were enrolled in a separate CHIP program. Accordingly, this historic dataset contains separate CHIP enrollment by month and state between April 2023 and June 2024. CMS will continue to publicly report separate CHIP enrollment by month and state (beyond the historic CAA/Unwinding period) in a new dataset, which is available at [link]. Please note that the methods used to count separate CHIP enrollees differ slightly between the two datasets; as a result, data users should exercise caution if comparing separate CHIP enrollment across the two datasets. Sources: T-MSIS Analytic Files (TAF) and state-submitted enrollment totals. The data notes indicate when a state’s monthly total was a state-submitted value, rather than from T-MSIS.TAF data were pulled as follows:April 2023 enrollment - TAF as of August 2023May 2023 enrollment - TAF as of August 2023June 2023 enrollment - TAF as of September 2023July 2023 enrollment - TAF as of October 2023August 2023 enrollment - TAF as of November 2023September 2023 enrollment - TAF as of December 2023October 2023 enrollment - TAF as of January 2024November 2023 enrollment - TAF as of February 2024December 2023 enrollment - TAF as of March 2024January 2024 enrollment - TAF as of April 2024February 2024 enrollment - TAF as of May 2024March 2024 enrollment - TAF as of June 2024April 2024 enrollment – TAF as of July 2024May 2024 enrollment – TAF as of August 2024June 2024 enrollment – TAF as of September 2024 TAF are produced one month after the T-MSIS submission month. For example, TAF as of August 2023 is based on July T-MSIS submissions. Notes: The separate CHIP enrollment in this report is not inclusive of enrollees covered by Medicaid expansion CHIP. Enrollment includes individuals enrolled in separate CHIP at any point during the month but excludes those enrolled in both Medicaid and separate CHIP during the month. See the Data Sources and Metrics Definitions Overview document for a full description of the data sources, metric definitions, and general data limitations.Alaska, District of Columbia, Hawaii, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, South Carolina, Vermont, and Wyoming do not have separate CHIP Programs. Maryland has a separate CHIP program that began in July 2023; April 2023 - June 2023 data for Maryland represents retroactive coverage. This document includes separate CHIP data submitted to CMS by states via T-MSIS or a separate collection form. These data include reporting metrics consistent with section 1902(tt)(1) of the Social Security Act.CHIP: Children's Health Insurance Program Data notes: (a) State-submitted value; data not from T-MSIS(b1) May 2023 enrollment pulled from TAF as of September 2023(b2) Data was restated using TAF as of October 2023(b3) Data was restated using TAF as of April 2024(b4) Data was restated using TAF as of July 2024(b5) Data was restated using TAF as of August 2024(c) Enrollment counts include postpartum women with coverage funded via a Health Services Initiative
Separate CHIP Enrollment by Month and State
- catalog.data.gov
- data.virginia.gov
- +1more
Updated May 2, 2025ShareFacebookTwitterEmailClick to copy linkLink copiedCiteCenters for Medicare & Medicaid Services (2025). Separate CHIP Enrollment by Month and State [Dataset]. https://catalog.data.gov/dataset/separate-chip-enrollment-by-month-and-state-a70c9Dataset updatedMay 2, 2025Dataset provided byCenters for Medicare & Medicaid ServicesDescriptionThis dataset includes total enrollment in separate CHIP (S-CHIP) programs by month and state from April 2023 forward. Sources: T-MSIS Analytic Files (TAF) and state-submitted enrollment totals. The data notes indicate when a state’s monthly total was a state-submitted value, rather than from T-MSIS. Methods: Enrollment includes individuals enrolled in S-CHIP at any point during the coverage month, excluding those enrolled in dental-only coverage. The S-CHIP enrollment in this report also excludes enrollees covered by Medicaid expansion CHIP, a program in which a state receives federal funding to expand Medicaid eligibility to optional targeted low-income children that meets the requirements of section 2103 of the Social Security Act. If an individual is enrolled in both Medicaid or Medicaid-expansion CHIP and S-CHIP in a given month, TAF picks the program in which they were last enrolled. Unless S-CHIP enrollment counts are replaced with a state-submitted value, each state's monthly S-CHIP enrollment is equal to the number of unique people in TAF with a CHIP_CODE = 3 (S-CHIP) and ELGBLTY_GRP_CD not equal to ‘66’ (Children Eligible for Dental Only Supplemental Coverage). More information about TAF is available at https://www.medicaid.gov/medicaid/data-systems/macbis/medicaid-chip-research-files/transformed-medicaid-statistical-information-system-t-msis-analytic-files-taf/index.html. Note: A historic dataset with S-CHIP enrollment by month and state from April 2023 to June 2024 is also available at: https://data.medicaid.gov/dataset/d30cfc7c-4b32-4df1-b2bf-e0a850befd77. This historic dataset was created to fulfill reporting requirements under section 1902(tt)(1) of the Social Security Act, which was added by section 5131(b) of subtitle D of title V of division FF of the Consolidated Appropriations Act, 2023 (P.L. 117-328) (CAA, 2023). Please note that the methods used to count S-CHIP enrollees differ slightly between the two datasets; as a result, data users should exercise caution if comparing S-CHIP enrollment across the two datasets. State notes: Alaska, District of Columbia, Hawaii, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, South Carolina, Vermont, and Wyoming do not have S-CHIP programs. Maryland has an S-CHIP program for the from conception to end of pregnancy group that began in July 2023; April 2023 - June 2023 data for Maryland represents retroactive coverage. Oregon moved all its S-CHIP enrollees, other than those in the from conception to the end of pregnancy group, to a Medicaid-expansion CHIP program effective January 1, 2024. CHIP: Children's Health Insurance Program
- i
Medicaid Claims by Recipient Race and Gender
- hub.mph.in.gov
Updated Sep 14, 2017ShareFacebookTwitterEmailClick to copy linkLink copiedCite(2017). Medicaid Claims by Recipient Race and Gender [Dataset]. https://hub.mph.in.gov/dataset/medicaid-claims-by-recipient-race-and-gendeDataset updatedSep 14, 2017DescriptionArchived as of 6/26/2025: The datasets will no longer receive updates but the historical data will continue to be available for download. This dataset provides information related to the claims of recipients enrolled in Medicaid. It contains information about the total number of patients, total number of claims, and total dollar amount, grouped by recipient race and gender. Restricted to claims with service date between 01/2012 to 12/2017. Restricted to patients with a Medicaid claim during this period. This data is for research purposes and is not intended to be used for reporting. Due to differences in geographic aggregation, time period considerations, and units of analysis, these numbers may differ from those reported by FSSA.
- O
Department of Social Services - People Served by Town and Program, 2015-2024...
- data.ct.gov
application/rdfxml +5Updated Mar 14, 2025+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteDepartment of Social Services (2025). Department of Social Services - People Served by Town and Program, 2015-2024 [Dataset]. https://data.ct.gov/Health-and-Human-Services/Department-of-Social-Services-People-Served-by-Tow/vvvu-dkxncsv, xml, json, application/rdfxml, application/rssxml, tsvAvailable download formatsDataset updatedMar 14, 2025Dataset authored and provided byDepartment of Social ServicesLicenseU.S. Government Workshttps://www.usa.gov/government-works
License information was derived automaticallyDescriptionThis dataset includes the number of people enrolled in DSS services by town and by program from CY 2015-2024. To view the full dataset and filter the data, click the "View Data" button at the top right of the screen. More data on people served by DSS can be found here.
About this data
- For privacy considerations, a count of zero is used for counts less than five.
- A recipient is counted in all towns where that recipient resided in that year.
- Due to eligibility policies and operational processes, enrollment can vary slightly after publication. Please be aware of the point-in-time nature of the published data when comparing to other data published or shared by the Department of Social Services, as this data may vary slightly.
Notes by year 2021 In March 2020, Connecticut opted to add a new Medicaid coverage group: the COVID-19 Testing Coverage for the Uninsured. Enrollment data on this limited-benefit Medicaid coverage group is being incorporated into Medicaid data effective January 1, 2021.
Enrollment data for this coverage group prior to January 1, 2021, was listed under State Funded Medical. An historical accounting of enrollment of the specific coverage group starting in calendar year 2020 will also be published separately.
2018 On April 22, 2019 the methodology for determining HUSKY A Newborn recipients changed, which caused an increase of recipients for that benefit starting in October 2016. We now count recipients recorded in the ImpaCT system as well as in the HIX system for that assistance type, instead using HIX exclusively.
Also, the methodology for determining the address of the recipients changed: 1. The address of a recipient in the ImpaCT system is now correctly determined specific to that month instead of using the address of the most recent month. This resulted in some shuffling of the recipients among townships starting in October 2016.
- If, in a given month, a recipient has benefit records in both the HIX system and in the ImpaCT system, the address of the recipient is now calculated as follows to resolve conflicts: Use the residential address in ImpaCT if it exists, else use the mailing address in ImpaCT if it exists, else use the address in HIX. This resulted in a reduction in counts for most townships starting in March 2017 because a single address is now used instead of two when the systems do not agree.
On February 14, 2019 the enrollment counts for 2012-2015 across all programs were updated to account for an error in the data integration process. As a result, the count of the number of people served increased by 13% for 2012, 10% for 2013, 8% for 2014 and 4% for 2015. Counts for 2016, 2017 and 2018 remain unchanged.
On January 16, 2019 these counts were revised to count a recipient in all locations that recipient resided in that year.
On January 1, 2019 the counts were revised to count a recipient in only one town per year even when the recipient moved within the year. The most recent address is used.
NPPES Plan and Provider Enumeration System
- kaggle.com
zipUpdated Mar 20, 2019ShareFacebookTwitterEmailClick to copy linkLink copiedCiteCenters for Medicare & Medicaid Services (2019). NPPES Plan and Provider Enumeration System [Dataset]. https://www.kaggle.com/cms/nppeszip(0 bytes)Available download formatsDataset updatedMar 20, 2019Dataset authored and provided byCenters for Medicare & Medicaid ServicesLicensehttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
DescriptionContext
The CMS National Plan and Provider Enumeration System (NPPES) was developed as part of the Administrative Simplification provisions in the original HIPAA act. The primary purpose of NPPES was to develop a unique identifier for each physician that billed medicare and medicaid. This identifier is now known as the National Provider Identifier Standard (NPI) which is a required 10 digit number that is unique to an individual provider at the national level.
Once an NPI record is assigned to a healthcare provider, parts of the NPI record that have public relevance, including the provider’s name, speciality, and practice address are published in a searchable website as well as downloadable file of zipped data containing all of the FOIA disclosable health care provider data in NPPES and a separate PDF file of code values which documents and lists the descriptions for all of the codes found in the data file.
Content
The dataset contains the latest NPI downloadable file in an easy to query BigQuery table, npi_raw. In addition, there is a second table, npi_optimized which harnesses the power of Big Query’s next-generation columnar storage format to provide an analytical view of the NPI data containing description fields for the codes based on the mappings in Data Dissemination Public File - Code Values documentation as well as external lookups to the healthcare provider taxonomy codes . While this generates hundreds of columns, BigQuery makes it possible to process all this data effectively and have a convenient single lookup table for all provider information.
Fork this kernel to get started.
Acknowledgements
https://console.cloud.google.com/marketplace/details/hhs/nppes?filter=category:science-research
Dataset Source: Center for Medicare and Medicaid Services. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.
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Inspiration
What are the top ten most common types of physicians in Mountain View?
What are the names and phone numbers of dentists in California who studied public health?
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Dataplex: All CMS Data Feeds | Access 1519 Reports & 26B+ Rows of Contact...
- datarade.ai
.csvUpdated Aug 29, 2024+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteDataplex (2024). Dataplex: All CMS Data Feeds | Access 1519 Reports & 26B+ Rows of Contact Data | Perfect for Historical Analysis & Easy Ingestion [Dataset]. https://datarade.ai/data-products/dataplex-all-cms-data-feeds-access-1519-reports-26b-row-dataplex-3b76.csvAvailable download formatsDataset updatedAug 29, 2024Dataset authored and provided byDataplexArea coveredUnited States of AmericaDescriptionThe All CMS Data Feeds dataset is an expansive resource offering access to 119 unique report feeds, providing in-depth insights into various aspects of the U.S. healthcare system including nursing facility owners and accountable care organization participants contact data. With over 25.8 billion rows of data meticulously collected since 2007, this dataset is invaluable for healthcare professionals, analysts, researchers, and businesses seeking to understand and analyze healthcare trends, performance metrics, and demographic shifts over time. The dataset is updated monthly, ensuring that users always have access to the most current and relevant data available.
Dataset Overview:
118 Report Feeds: - The dataset includes a wide array of report feeds, each providing unique insights into different dimensions of healthcare. These topics range from Medicare and Medicaid service metrics, patient demographics, provider information, financial data, and much more. The breadth of information ensures that users can find relevant data for nearly any healthcare-related analysis. - As CMS releases new report feeds, they are automatically added to this dataset, keeping it current and expanding its utility for users.
25.8 Billion Rows of Data:
- With over 25.8 billion rows of data, this dataset provides a comprehensive view of the U.S. healthcare system. This extensive volume of data allows for granular analysis, enabling users to uncover insights that might be missed in smaller datasets. The data is also meticulously cleaned and aligned, ensuring accuracy and ease of use.
Historical Data Since 2007: - The dataset spans from 2007 to the present, offering a rich historical perspective that is essential for tracking long-term trends and changes in healthcare delivery, policy impacts, and patient outcomes. This historical data is particularly valuable for conducting longitudinal studies and evaluating the effects of various healthcare interventions over time.
Monthly Updates:
- To ensure that users have access to the most current information, the dataset is updated monthly. These updates include new reports as well as revisions to existing data, making the dataset a continuously evolving resource that stays relevant and accurate.
Data Sourced from CMS:
- The data in this dataset is sourced directly from the Centers for Medicare & Medicaid Services (CMS). After collection, the data is meticulously cleaned and its attributes are aligned, ensuring consistency, accuracy, and ease of use for any application. Furthermore, any new updates or releases from CMS are automatically integrated into the dataset, keeping it comprehensive and current.
Use Cases:
Market Analysis:
- The dataset is ideal for market analysts who need to understand the dynamics of the healthcare industry. The extensive historical data allows for detailed segmentation and analysis, helping users identify trends, market shifts, and growth opportunities. The comprehensive nature of the data enables users to perform in-depth analyses of specific market segments, making it a valuable tool for strategic decision-making.
Healthcare Research:
- Researchers will find the All CMS Data Feeds dataset to be a robust foundation for academic and commercial research. The historical data, combined with the breadth of coverage across various healthcare metrics, supports rigorous, in-depth analysis. Researchers can explore the effects of healthcare policies, study patient outcomes, analyze provider performance, and more, all within a single, comprehensive dataset.
Performance Tracking:
- Healthcare providers and organizations can use the dataset to track performance metrics over time. By comparing data across different periods, organizations can identify areas for improvement, monitor the effectiveness of initiatives, and ensure compliance with regulatory standards. The dataset provides the detailed, reliable data needed to track and analyze key performance indicators.
Compliance and Regulatory Reporting:
- The dataset is also an essential tool for compliance officers and those involved in regulatory reporting. With detailed data on provider performance, patient outcomes, and healthcare utilization, the dataset helps organizations meet regulatory requirements, prepare for audits, and ensure adherence to best practices. The accuracy and comprehensiveness of the data make it a trusted resource for regulatory compliance.
Data Quality and Reliability:
The All CMS Data Feeds dataset is designed with a strong emphasis on data quality and reliability. Each row of data is meticulously cleaned and aligned, ensuring that it is both accurate and consistent. This attention to detail makes the dataset a trusted resource for high-stakes applications, where data quality is critical.
Integration and Usability:
Ease of Integration:
- The dataset is provided in a CSV format, which is widely compatible with most data analysis too...
Medicaid and CHIP Updated Renewal Outcomes
- healthdata.gov
- data.virginia.gov
- +2more
application/rdfxml +5Updated May 4, 2024+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCitedata.medicaid.gov (2024). Medicaid and CHIP Updated Renewal Outcomes [Dataset]. https://healthdata.gov/dataset/Medicaid-and-CHIP-Updated-Renewal-Outcomes/5cf3-8irwapplication/rssxml, csv, xml, application/rdfxml, json, tsvAvailable download formatsDataset updatedMay 4, 2024Dataset provided bydata.medicaid.govDescriptionState-reported data on Medicaid and CHIP eligibility renewals that reflect the outcomes of previously pending renewals three months after the renewal was due and also any corrections to the original renewal data submitted to CMS. See here for original renewal data.
CMS renewal data specifications require states to update and submit to CMS their monthly renewal outcome metrics - metric 5 data and its submetrics (monthly metrics 5a, 5a(1), 5a(2), 5b, 5c, and 5d) - after the original monthly report submission. The “updated” renewal data reflect the outcomes of renewals previously reported as pending (monthly metric 5d of the original monthly report) as of three months after the renewal was due. For more information about this data set and considerations for users when reviewing, please see the Medicaid and CHIP Unwinding: Data Sources and Metrics Definitions Overview found here.
Sources:
(1) March 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in March 2023 as of June 2023. April 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in April 2023 as of July 2023. May 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in May 2023 as of August 2023. June 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in June 2023 as of September 2023. July 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in July 2023 as of October 2023. August 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in August 2023 as of November 2023. September 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on April 02, 2024, representing the updated disposition of renewals due in September 2023 as of December 2023. October 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on April 02, 2024, representing the updated disposition of renewals due in October 2023 as of January 2024. November 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on May 07, 2024, representing the updated disposition of renewals due in November 2023 as of February 2024. December 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on June 11, 2024, representing the updated disposition of renewals due in December 2023 as of March 2024. New Hampshire’s December 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on April 09, 2024, representing the updated disposition of renewals due in December 2023 as of March 2024. New York’s December 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on April 22, 2024, representing the updated disposition of renewals due in December 2023 as of March 2024. January 2024 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on July 02, 2024, representing the updated disposition of renewals due in January 2024 as of April 2024. February 2024 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on August 06, 2024, representing the updated disposition of renewals due in February 2024 as of May 2024. March 2024 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on September 09, 2024, representing the updated disposition of renewals due in March 2024 as of June 2024.
Notes: States report updated renewal outcomes for a cohort as of three months after the month renewals are scheduled for completion, unless otherwise noted. In the March 2023 – October 2023 reporting periods, Oklahoma included outcomes for some individuals who returned their renewal form during the reconsideration period. See the Data Sources and Definitions Overview document for a full description of the metric definitions and how they relate to each other.
April 2023: Ohio reported updated renewal outcomes for the cohort as of 10/31/2023. Arkansas and Pennsylvania reported the eligibility status of the cohort, and data may include outcomes of eligibility actions that occurred after the renewal.
May 2023: The following states reported updated renewal outcomes for the cohort as of a different date: Ohio (outcomes as of 10/31/2023), Rhode Island (outcomes as of 11/1/2023), South Carolina (outcomes as of 12/20/2023), and Texas (outcomes as of 9/8/2023). Pennsylvania, Rhode Island, and South Carolina updated the eligibility status of the cohort, and data may include eligibility actions that occurred after the renewal.
June 2023: The following states reported updated renewal outcomes for the cohort as of a different date: Kansas (outcomes as of 8/31/23), Minnesota (outcomes as of 12/2023), Ohio (outcomes as of 10/31/2023), North Carolina (outcomes as of 12/1/2023), Rhode Island (outcomes as of 11/1/2023), and South Carolina (outcomes as of 12/20/2023). Pennsylvania, Rhode Island, and South Carolina updated the eligibility status of the cohort, and data may include eligibility actions that occurred after the renewal.
July 2023: The following states reported updated renewal outcomes for the cohort as of a different date: Minnesota (outcomes as of 12/2023), North Carolina (outcomes as of 12/1/2023), Rhode Island (outcomes as of 11/1/2023), and Texas (outcomes as of 11/9/2023). California, Pennsylvania, and Rhode Island updated the eligibility status of the cohort, and data may include eligibility actions that occurred after the renewal.
August 2023: The following states reported updated renewal outcomes for the cohort as of a different date: Minnesota (outcomes as of 12/2023), North Carolina (outcomes as of 12/1/2023), Rhode Island (outcomes as of 12/4/2023), and South Carolina (outcomes as of 12/20/2023). California, Pennsylvania, Rhode Island, and South Carolina updated the eligibility status of the cohort, and data may include eligibility actions that occurred after the renewal.
September 2023: The following states reported updated renewal outcomes for the cohort as of a different date: Minnesota (outcomes as of 1/8/2024), North Carolina (1/2/2024), Rhode Island (1/1/2024), and South Carolina (outcomes as of 1/8/2024). California, Pennsylvania, Rhode Island, and South Carolina updated the eligibility status of the cohort, and data may include eligibility actions that occurred after the renewal. Vermont excluded renewal outcomes for some individuals who requested voluntary terminations or who were deceased.
October 2023: The following states reported updated renewal outcomes for the cohort as of a different date: Minnesota (outcomes as of 2/12/2024), North Carolina (outcomes as of 2/1/2024), Rhode Island (outcomes as of 2/15/2024), and South Carolina (outcomes as 2/1/2024). California, Pennsylvania, and South Carolina updated the eligibility status of the cohort, and data may include eligibility actions that occurred after the renewal. Rhode Island’s updated data includes some individuals reported as pending whose renewal was completed.
November 2023: The following states reported updated renewal outcomes for the cohort as of a different date: Minnesota (outcomes as of 3/4/2024), New York (outcomes as of 3/31/2024), North Carolina (outcomes as of 3/1/2024), Rhode Island (outcomes as of 4/1/2024), and South Carolina (outcomes as of 3/1/2024). Pennsylvania and South Carolina updated the eligibility status of the cohort, and data may include eligibility actions that occurred after the renewal. Rhode Island’s updated data includes some individuals reported as pending whose renewal was completed. California included outcomes for some individuals whose eligibility was redetermined based on a change in circumstances after the renewal was processed.
December 2023: The following states reported updated renewal outcomes for the cohort as of a different date: North Carolina (outcomes as of 4/1/2024) and Minnesota (outcomes as of 4/2/2024). Pennsylvania updated the eligibility status of the cohort, and data may include eligibility actions that occurred after the renewal. California included outcomes for some individuals whose eligibility was redetermined based on a change in circumstances after the renewal was processed.
January 2024: The following states reported updated renewal outcomes for the cohort as of a different date: North Carolina (outcomes as of 5/1/2024) and Minnesota (outcomes as of 5/6/2024). Pennsylvania updated the eligibility status of the cohort, and data may include eligibility actions that occurred after the renewal.
February 2024: The following states reported updated renewal outcomes for the cohort as of a different date: North Carolina (outcomes as of 6/3/2024) and Minnesota (outcomes as of 6/5/2024). Pennsylvania and Wyoming- i
Medicaid Claims by Subprogram Funding Source - Dataset - The Indiana Data...
- hub.mph.in.gov
Updated Sep 14, 2017ShareFacebookTwitterEmailClick to copy linkLink copiedCite(2017). Medicaid Claims by Subprogram Funding Source - Dataset - The Indiana Data Hub [Dataset]. https://hub.mph.in.gov/dataset/medicaid-claims-by-subprogram-funding-sourceDataset updatedSep 14, 2017DescriptionArchived as of 6/26/2025: The datasets will no longer receive updates but the historical data will continue to be available for download. This dataset provides information related to the claims of recipients enrolled in Medicaid. It contains information about the total number of patients, total number of claims, and total dollar amount, grouped by funding subprogram code. Restricted to claims with service date between 01/2012 to 12/2017. Restricted to patients with a Medicaid claim during this period. This data is for research purposes and is not intended to be used for reporting. Due to differences in geographic aggregation, time period considerations, and units of analysis, these numbers may differ from those reported by FSSA.
Share of Medicaid Enrollees in Managed Care
- catalog.data.gov
Updated Feb 3, 2025+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteCenters for Medicare & Medicaid Services (2025). Share of Medicaid Enrollees in Managed Care [Dataset]. https://catalog.data.gov/dataset/share-of-medicaid-enrollees-in-managed-care-712a3Dataset updatedFeb 3, 2025Dataset provided byCenters for Medicare & Medicaid ServicesDescriptionThe Share of Medicaid Enrollees in any Managed Care and in Comprehensive Managed CaAre profiles state-level enrollment statistics (numbers and percentages) of total Medicaid enrollees in any type of managed care as well as those enrolled specifically in comprehensive managed care programs. The report provides managed care enrollment by state with all 50 states, the District of Columbia and the US territories are represented in these data. Note: "n/a" indicates that a state or territory was not able to report data or does not have a managed care program. The “Total Medicaid Enrollees” column represents an unduplicated count of all beneficiaries in FFS and any type of managed care, including Medicaid-only and dually eligible individuals receiving full Medicaid benefits or Medicaid cost sharing. The “Total Medicaid Enrollment in Any Type of Managed Care” column represents an unduplicated count of beneficiaries enrolled in any Medicaid managed care program, including comprehensive MCOs, limited benefit MCOs, PCCMs, and PCCM entities. The “Medicaid Enrollment in Comprehensive Managed Care” column represents an unduplicated count of Medicaid beneficiaries enrolled in a managed care plan that provides comprehensive benefits (acute, primary care, specialty, and any other), as well as PACE programs. It excludes beneficiaries who are enrolled in a Financial Alignment Initiative Medicare-Medicaid Plan as their only form of managed care.
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Medicaid Claims by Recipient Zip Code
- hub.mph.in.gov
Updated Sep 14, 2017ShareFacebookTwitterEmailClick to copy linkLink copiedCite(2017). Medicaid Claims by Recipient Zip Code [Dataset]. https://hub.mph.in.gov/dataset/medicaid-claims-by-recipient-zip-codeDataset updatedSep 14, 2017DescriptionArchived as of 6/26/2025: The datasets will no longer receive updates but the historical data will continue to be available for download. This dataset provides information related to the services related to recipients enrolled in Medicaid. It contains information about the total number of recipients, total number of claims, and total dollar amount, by recipient zip code. Restricted to claims with service date between 01/2012 to 12/2017. Restricted to patients with a Medicaid claim during this period. This data is for research purposes and is not intended to be used for reporting. Due to differences in geographic aggregation, time period considerations, and units of analysis, these numbers may differ from those reported by FSSA.
Evaluating Health Home Care Quality
- kaggle.com
Updated Jan 23, 2023ShareFacebookTwitterEmailClick to copy linkLink copiedCiteThe Devastator (2023). Evaluating Health Home Care Quality [Dataset]. https://www.kaggle.com/datasets/thedevastator/evaluating-health-home-care-qualityCroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Dataset updatedJan 23, 2023Dataset provided byKaggleAuthorsThe DevastatorDescriptionEvaluating Health Home Care Quality
CMS Core Set and Health Home SPA Measures
By Health Data New York [source]
About this dataset
This dataset provides comprehensive measures to evaluate the quality of medical services provided to Medicaid beneficiaries by Health Homes, including the Centers for Medicare & Medicaid Services (CMS) Core Set and Health Home State Plan Amendment (SPA). This allows us to gain insight into how well these health homes are performing in terms of delivering high-quality care. Our data sources include the Medicaid Data Mart, QARR Member Level Files, and New York State Delivery System Inform Incentive Program (DSRIP) Data Warehouse. With this data set you can explore essential indicators such as rates for indicators within scope of Core Set Measures, sub domains, domains and measure descriptions; age categories used; denominators of each measure; level of significance for each indicator; and more! By understanding more about Health Home Quality Measures from this resource you can help make informed decisions about evidence based health practices while also promoting better patient outcomes
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For more datasets, click here.
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How to use the dataset
This dataset contains measures that evaluate the quality of care delivered by Health Homes for the Centers for Medicare & Medicaid Services (CMS). With this dataset, you can get an overview of how a health home is performing in terms of quality. You can use this data to compare different health homes and their respective service offerings.
The data used to create this dataset was collected from Medicaid Data Mart, QARR Member Level Files, and New York State Delivery System Incentive Program (DSRIP) Data Warehouse sources.
In order to use this dataset effectively, you should start by looking at the columns provided. These include: Measurement Year; Health Home Name; Domain; Sub Domain; Measure Description; Age Category; Denominator; Rate; Level of Significance; Indicator. Each column provides valuable insight into how a particular health home is performing in various measurements of healthcare quality.
When examining this data, it is important to remember that many variables are included in any given measure and that changes may have occurred over time due to varying factors such as population or financial resources available for healthcare delivery. Furthermore, changes in policy may also affect performance over time so it is important to take these things into account when evaluating the performance of any given health home from one year to the next or when comparing different health homes on a specific measure or set of indicators over time
Research Ideas
- Using this dataset, state governments can evaluate the effectiveness of their health home programs by comparing the performance across different domains and subdomains.
- Healthcare providers and organizations can use this data to identify areas for improvement in quality of care provided by health homes and strategies to reduce disparities between individuals receiving care from health homes.
- Researchers can use this dataset to analyze how variations in cultural context, geography, demographics or other factors impact delivery of quality health home services across different locations
Acknowledgements
If you use this dataset in your research, please credit the original authors. Data Source
License
See the dataset description for more information.
Columns
File: health-home-quality-measures-beginning-2013-1.csv | Column name | Description | |:--------------------------|:----------------------------------------------------| | Measurement Year | The year in which the data was collected. (Integer) | | Health Home Name | The name of the health home. (String) | | Domain | The domain of the measure. (String) | | Sub Domain | The sub domain of the measure. (String) | | Measure Description | A description of the measure. (String) | | Age Category | The age category of the patient. (String) | | Denominator | The denominator of the measure. (Integer) | | Rate | The rate of the measure. (Float) | | Level of Significance | The level of significance of the measure. (String) | | Indicator | The indicator of the measure. (String) |
Acknowledgements
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Medicaid Claims of Returning Citizens
- hub.mph.in.gov
Updated Aug 19, 2022+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCite(2022). Medicaid Claims of Returning Citizens [Dataset]. https://hub.mph.in.gov/dataset/medicaid-claims-of-returning-citizensDataset updatedAug 19, 2022DescriptionArchived as of 5/30/2025: The datasets will no longer receive updates but the historical data will continue to be available for download. This dataset provides information related to returning citizens released from a Department of Corrections facility and enrolled in Medicaid during the time period 01/2019 to 03/2022. It contains total number of paid Medicaid claims, cost, and median cost by recipient county. This data is for research purposes and is not intended to be used for reporting. Due to differences in geographic aggregation, time period considerations, and units of analysis, these numbers may differ from those reported by FSSA.
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‘Share of Medicaid Enrollees in Managed Care’ analyzed by Analyst-2
- analyst-2.ai
Updated Sep 10, 2015ShareFacebookTwitterEmailClick to copy linkLink copiedCiteAnalyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2015). ‘Share of Medicaid Enrollees in Managed Care’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-share-of-medicaid-enrollees-in-managed-care-3808/latestDataset updatedSep 10, 2015Dataset authored and provided byAnalyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)LicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionAnalysis of ‘Share of Medicaid Enrollees in Managed Care’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/f28822ae-11ec-4f57-948a-0e848d76ded0 on 26 January 2022.
--- Dataset description provided by original source is as follows ---
The Share of Medicaid Enrollees in any Managed Care and in Comprehensive Managed CaAre profiles state-level enrollment statistics (numbers and percentages) of total Medicaid enrollees in any type of managed care as well as those enrolled specifically in comprehensive managed care programs. The report provides managed care enrollment by state with all 50 states, the District of Columbia and the US territories are represented in these data.
--- Original source retains full ownership of the source dataset ---
NCHS Survey Data Linked to Centers for Medicare & Medicaid Services (CMS)...
- data.virginia.gov
- healthdata.gov
- +1more
htmlUpdated Apr 21, 2025+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteCenters for Disease Control and Prevention (2025). NCHS Survey Data Linked to Centers for Medicare & Medicaid Services (CMS) Medicare Data Files [Dataset]. https://data.virginia.gov/dataset/nchs-survey-data-linked-to-centers-for-medicare-medicaid-services-cms-medicare-data-fileshtmlAvailable download formatsDataset updatedApr 21, 2025DescriptionNCHS has linked data from various surveys with Medicare program enrollment and health care utilization and expenditure data from the Centers for Medicare & Medicaid Services (CMS). Linkage of the NCHS survey participants with the CMS Medicare data provides the opportunity to study changes in health status, health care utilization and costs, and prescription drug use among Medicare enrollees. Medicare is the federal health insurance program for people who are 65 or older, certain younger people with disabilities, and people with End-Stage Renal Disease.
dqs-medicaid-coverage-among-persons-under-age-65-b
- huggingface.co
Updated Apr 21, 2025+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteDepartment of Health and Human Services (2025). dqs-medicaid-coverage-among-persons-under-age-65-b [Dataset]. https://huggingface.co/datasets/HHS-Official/dqs-medicaid-coverage-among-persons-under-age-65-bDataset updatedApr 21, 2025AuthorsDepartment of Health and Human ServicesDescriptionDQS Medicaid coverage among persons under age 65, by selected characteristics: United States
DescriptionData on Medicaid coverage among people under age 65, in the United States, by selected population characteristics. Data from Health, United States. SOURCE: National Center for Health Statistics, National Health Interview Survey. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from:… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/dqs-medicaid-coverage-among-persons-under-age-65-b.
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Average Medicaid Enrollment by Plan by Fiscal Year
- data.delaware.gov
application/rdfxml +5Updated Jul 22, 2025+ more versionsShareFacebookTwitterEmailClick to copy linkLink copiedCiteDepartment of Health and Social Services, Division of Medicaid and Medical Assistance (2025). Average Medicaid Enrollment by Plan by Fiscal Year [Dataset]. https://data.delaware.gov/Health/Average-Medicaid-Enrollment-by-Plan-by-Fiscal-Year/v59b-a2wexml, csv, application/rssxml, application/rdfxml, json, tsvAvailable download formatsDataset updatedJul 22, 2025Dataset authored and provided byDepartment of Health and Social Services, Division of Medicaid and Medical AssistanceLicenseU.S. Government Workshttps://www.usa.gov/government-works
License information was derived automaticallyDescriptionThis dataset represents the number of Medicaid eligible individuals receiving the various Medicaid services over time.
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Medicaid buy in program income levels
- data.wu.ac.at
- datadiscoverystudio.org
- +1more
csv, json, rdf, xmlUpdated May 3, 2018ShareFacebookTwitterEmailClick to copy linkLink copiedCiteCity of New York (2018). Medicaid buy in program income levels [Dataset]. https://data.wu.ac.at/schema/data_gov/NzAwMjZkNGYtMTdkNy00NDEwLWI4Y2YtYTQ5ZjA3NWE2MDk2csv, rdf, json, xmlAvailable download formatsDataset updatedMay 3, 2018Dataset provided byCity of New YorkDescriptionThe Medicaid Buy-In Program for Working People with Disabilities offers people with disabilities who are working, and earning more than the allowable limits for regular Medicaid, the opportunity to keep their health care coverage through Medicaid. Eligibility requirements include certain criteria and income levels as listed here. This chart is only a guide. Individuals should see an enrollment counselor for eligibility screening. NOTE: Chart effective January 1, 2012; subject to annual income updates.
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This public dataset was created by the Centers for Medicare & Medicaid Services. The data summarize counts of enrollees who are dually-eligible for both Medicare and Medicaid program, including those in Medicare Savings Programs. “Duals” represent 20 percent of all Medicare beneficiaries, yet they account for 34 percent of all spending by the program, according to the Commonwealth Fund . As a representation of this high-needs, high-cost population, these data offer a view of regions ripe for more intensive care coordination that can address complex social and clinical needs. In addition to the high cost savings opportunity to deliver upstream clinical interventions, this population represents the county-by-county volume of patients who are eligible for both state level (Medicaid) and federal level (Medicare) reimbursements and potential funding streams to address unmet social needs across various programs, waivers, and other projects. The dataset includes eligibility type and enrollment by quarter, at both the state and county level. These data represent monthly snapshots submitted by states to the CMS, which are inherently lower than ever-enrolled counts (which include persons enrolled at any time during a calendar year.) For more information on dually eligible beneficiaries
Querying BigQuery tables
You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.sdoh_cms_dual_eligible_enrollment.
Sample Query
In what counties in Michigan has the number of dual-eligible individuals increased the most from 2015 to 2018? Find the counties in Michigan which have experienced the largest increase of dual enrollment households
duals_Jan_2015 AS (
SELECT Public_Total AS duals_2015, County_Name, FIPS
FROM bigquery-public-data.sdoh_cms_dual_eligible_enrollment.dual_eligible_enrollment_by_county_and_program
WHERE State_Abbr = "MI" AND Date = '2015-12-01'
),
duals_increase AS ( SELECT d18.FIPS, d18.County_Name, d15.duals_2015, d18.duals_2018, (d18.duals_2018 - d15.duals_2015) AS total_duals_diff FROM duals_Jan_2018 d18 JOIN duals_Jan_2015 d15 ON d18.FIPS = d15.FIPS )
SELECT * FROM duals_increase WHERE total_duals_diff IS NOT NULL ORDER BY total_duals_diff DESC