NCHS 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.

This dataset tracks the updates made on the dataset "Centers for Medicaid and Medicare Services (CMS) Research, Statistics, Data & Systems" as a repository for previous versions of the data and metadata.

Variety of Research, Statistics, Data & Systems information from CMS

NCHS has linked various surveys with the Medicaid Analytic eXtract (MAX) files collected from the Centers for Medicare & Medicaid Services (CMS). Linkage of the NCHS survey participants with the CMS Medicaid MAX data provides the opportunity to study changes in health status, health care utilization and expenditures in low-income families with children and the elderly U.S. populations.

Contains full API download of all available datasets on data.medicaid.gov. Program overview Data.Medicaid.gov is a public platform offering open access to a diverse range of datasets related to Medicaid and the Children’s Health Insurance Program (CHIP). It is tailored to support policymakers, researchers, and the general public by providing critical data for research, reporting, and analysis. The platform covers various topics, including state Medicaid and CHIP programs, enrollment statistics, spending trends, and quality metrics. With data presented in multiple formats, it promotes transparency, allowing users to track program performance and make informed decisions based on reliable insights.

According to findings reported in, The Medicaid Medically Improved Group, Losing Disability Status and Growing Earnings, published in Volume 4, Issue 1 of the Medicare and Medicaid Research Review, participants in the medically improved group option of Medicaid Buy-in programs for working adults with disabilities moved off Social Security cash assistance rolls, or were diverted from them, and increased their earnings nearly 200 dollars per month. The Ticket to Work and Work Incentives Improvement Act gives states the choice to extend Medicaid Buy-In coverage to a medically improved group, but evidence of participants employment results has been lacking. This study shows that enrollment has been limited, with 233 participants in 2009. However, participation has doubled annually, on average, with a low drop out or churn rate. Participants earnings grew significantly, with mean earnings in 2009 at 52 percent above the federal poverty level.

This 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

As of March 2021, there have been a large number of studies that look into the effect of the Affordable Care Act Medicaid Expansion on various outcomes. Most of these findings generally show positive effects of Medicaid expansion compared to states that have not expanded Medicaid (as of January 2021, there were 12 non-expansion states). The largest number of studies focused on the effect of Medicaid expansion on access and utilization of care with 70 percent of studies reporting positive effects. Most notably, all 25 studies on state economy found that Medicaid expansion actually had a positive economic impact on expansion states. This statistic shows the number of studies on the positive, mixed, and negative effects of ACA Medicaid expansion in the U.S. published between January 2014 and March 2021, sorted by outcome.

Supplementary methods to accompany the manuscript titled "Patients With Medicaid Are More Likely to Utilize Primary Care for Common Skin Conditions: A Cross-Sectional Study of United States Practice Data. " (Journal of the American Academy of Dermatology)

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. Our source data were the 50-state surveys of Medicaid and CHIP eligibility, enrollment, and cost-sharing policies 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, with each coded by state-quarter—1) eligibility (28 measures), 2) enrollment and renewal processes (39), 3) premiums (16), 4) cost-sharing (26), and 5) managed care (13).

More than one in four hospitalizations for those with both Medicare and full Medicaid coverage was potentially avoidable, according to findings reported in Medicare-Medicaid Eligible Beneficiaries and Potentially Avoidable Hospitalizations, published in Volume 4, Issue 1 of the Medicare and Medicaid Research Review. Using data from 2007 to 2009, the study examined potentially avoidable hospitalizations rates by setting, state, and medical condition, and the average cost of these events. Beneficiaries in institutions were much more likely to have these events - 16 percent of beneficiaries in the study population were in an institution, yet comprised 45 percent of all potentially avoidable hospitalizations. The range in rates per 1,000 person years across the states was considerable from a low of 59 (Utah) to a high of 197 (Mississippi), a more than a threefold difference. Five conditions were responsible for nearly 80 percent of potentially avoidable hospitalizations. From 2007 to 2009, the national and state rates were fairly consistent.

The Agency for Healthcare Research and Quality (AHRQ) created SyH-DR from eligibility and claims files for Medicare, Medicaid, and commercial insurance plans in calendar year 2016. SyH-DR contains data from a nationally representative sample of insured individuals for the 2016 calendar year. SyH-DR uses synthetic data elements at the claim level to resemble the marginal distribution of the original data elements. SyH-DR person-level data elements are not synthetic, but identifying information is aggregated or masked.

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According to findings reported in Readiness for Meaningful Use of Health Information Technology and Patient Centered Medical Home Recognition Survey Results, published in Volume 3, Issue 4, of the Medicare and Medicaid Research Review, nearly 70 percent of community health centers (CHCs) had full or partial Electronic Health Record (EHR) adoption at the time of the survey. Of CHCs with EHR systems, 30 percent had been in operation for less than one year, 31 percent for one to two years, and 39 percent for three or more years. Survey results were combined with 2009 Uniform Data System data to determine which factors impact use of Health IT and Meaningful Use readiness. Significant differences, by length of EHR operation were found for Medicaid patients, full or partial EHR adoption, and Patient Centered Medical Home recognition. Results for Stage 1 Core and Menu compliance and CHCs Technical Assistance or training interests are also presented.

According to findings reported in Readiness for Meaningful Use of Health Information Technology and Patient Centered Medical Home Recognition Survey Results, published in Volume 3, Issue 4, of the Medicare and Medicaid Research Review, nearly 70 percent of community health centers (CHCs) had full or partial Electronic Health Record (EHR) adoption at the time of the survey. Of CHCs with EHR systems, 30 percent had been in operation for less than one year, 31 percent for one to two years, and 39 percent for three or more years. Survey results were combined with 2009 Uniform Data System data to determine which factors impact use of Health IT and Meaningful Use readiness. Significant differences, by length of EHR operation were found for Medicaid patients, full or partial EHR adoption, and Patient Centered Medical Home recognition. Results for Stage 1 Core and Menu compliance and CHCs Technical Assistance or training interests are also presented.

Archived 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.

NCHS has linked various surveys with Medicaid enrollment and claims records collected from the Centers for Medicare & Medicaid Services (CMS) Transformed Medicaid Statistical Information System (T-MSIS). Linkage of the NCHS survey participants with the CMS T-MSIS data creates a new data resource that can support research studies focused on a wide range of patient health outcomes and the association of means-tested government insurance programs on health and health outcomes.

Through its data linkage program, NCHS has been able to expand the analytic utility of the data collected from the National Hospital Care Survey (NHCS) by augmenting it with Medicaid and Children’s Health Insurance Program (CHIP) claims data collected by the Centers for Medicare & Medicaid Services (CMS) Transformed Medicaid Statistical Information System (T-MSIS). Linkage of NHCS patient data with T-MSIS enrollment and claims data creates a new data resource that can support research studies focused on a wide range of patient health outcomes and the association of means-tested government insurance programs with health and health outcomes.

Contains full records from the CMS Open Payments Data API. About openpaymentsdata.cms.gov: The mission of the program is to provide the public with a more transparent health care system. Open Payments collects and publishes information about financial relationships between drug and medical device companies (referred to as "reporting entities") and certain health care providers (referred to as "covered recipients"). These relationships may involve payments to providers for things including but not limited to research, meals, travel, gifts or speaking fees. All information available on the Open Payments database is open to personal interpretation and if there are questions about the data, patients and their advocates should speak directly to the health care provider for a better understanding.

Archived 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 information about the total number of recipients by county of residence at the time of the Medicaid application, gender, ethnicity, and race. 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.

The 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...

Big “p” policy changes at the state and federal level are certainly important to health equity, such as eligibility for and generosity of Medicaid benefits. Medicaid expansion has significantly expanded the number of people who are eligible for Medicaid and the creation of the health insurance exchanges (Marketplace) under the Affordable Care Act created a very visible avenue through which people can learn that they are eligible. Although many applications are now submitted online, physical access to state, county, and tribal government Medicaid offices still plays a critical role in understanding eligibility, getting help in applying, and navigating required documentation for both initial enrollment and redetermination of eligibility. However, as more government functions have moved online, in-person office locations and/or staff may have been cut to reduce costs, and gentrification has shifted where minoritized, marginalized, and/or low-income populations live, it is unclear if this key local connection point between residents and Medicaid has been maintained. Our objective was to identify and geocode all Medicaid offices in the United States for pairing with other spatial data (e.g., demographics, Medicaid participation, health care use, health outcomes) to investigate policy-relevant research questions. Three coders identified Medicaid office addresses in all 50 states and the District of Columbia by searching state government websites (e.g., Department of Health and Human Services or analogous state agency) during late 2021 and early 2022 for the appropriate Medicaid agency and its office locations, which were then reviewed for accuracy by a fourth coder. Our corpus of Medicaid office addresses was then geocoded using the Census Geocoder from the US Census Bureau (https://geocoding.geo.census.gov/geocoder/) with unresolved addresses investigated and/or manually geocoded using Google Maps. The corpus was updated in August through December 2023 following the end of the COVID-19 public health emergency by a fifth coder as several states closed and/or combined offices during the pandemic. After deduplication (e.g., where multiple counties share a single office) and removal of mailing addresses (e.g., PO Boxes), our dataset includes 3,027 Medicaid office locations. 1 (December 19, 2023) – original version 2 (January 25, 2024) – added related publication (Data in Brief), corrected two records that were missing negative signs in longitude 3 (February 6, 2024) – corrected latitude and longitude for one office (1340 State Route 9, Lake George, NY 12845) 4 (March 4, 2024) – added one office for Vermont after contacting relevant state agency (280 State Road, Waterbury, VT 05671)