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.

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.

List of Top Authors of Medicare & Medicaid Research Review sorted by citations.

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.

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.

Medicaid and the Children's Health Insurance Program (CHIP) provide health insurance coverage to approximately 85 million Americans as of late 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 originally 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). 1 (June 28, 2023) – original version 2 (March 14, 2024) – re-reviewed, corrected (where necessary), and extended five income eligibility measures (inc_inf, inc_child_1_5, inc_child_6_18, inc_parents, and inc_preg) through January 2023

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

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.

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.

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

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.

MAX data is a set of person-level data files on Medicaid eligibility, service utilization, and payments in the United States of America. The MAX data are extracted from the Medicaid Statistical Information System (MSIS) and are created to support research and policy analysis. The MAX development process combines MSIS initial claims, interim claims, voids, and adjustments for a given service into final action events. MAX datasets include inpatient data, long-term care files, other services, prescription drug files, and person summary files.

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.

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 survey responses to ten questions on social determinants of health at the time of applying to Medicaid. 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. Archived as of 7/10/2025: The datasets will no longer receive updates but the historical data will continue to be available for download

The home of Medicaid and CHIP open data provided by the Federal Government. Conduct research and design data visualizations using open data from Medicaid and the Children's' Health Insurance Program (CHIP) Data available on the following categories: • Drug Pricing and Payment • Enrollment • Quality • Eligibility • State Drug Utilization • Uncategorized

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.

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.

Performance rates on publicly reported health care quality measures in the CMS Medicaid/CHIP Child and Adult Core Sets, for 2024 reporting. Sources: Mathematica analysis of (1) Quality Measure Reporting (QMR) system reports, (2) Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) data; and (3) National Core Indicators (NCI) data submitted by states to the National Association of State Directors of Developmental Disabilities Services (NASDDDS) and the Human Services Research Institute (HSRI) (The NCI National Team) through the Online Data Entry System (ODESA). Agency for Healthcare Research and Quality (AHRQ) and Centers for Medicare & Medicaid Services (CMS) analysis of the AHRQ CAHPS Database. Dataset revised September 2025. For more information, see the Children's Health Care Quality Measures and Adult Health Care Quality Measures webpages.

Digital Navigator Platforms for Medicaid Patients Market Outlook

As per our latest research, the Digital Navigator Platforms for Medicaid Patients market size reached USD 1.47 billion globally in 2024, demonstrating robust momentum driven by technological advancements and policy initiatives aimed at improving healthcare access. The market is expected to grow at a CAGR of 13.2% from 2025 to 2033, reaching an estimated USD 4.24 billion by the end of the forecast period. This growth is primarily fueled by increased Medicaid enrollment, rising digital transformation efforts across healthcare systems, and a growing emphasis on patient-centric care delivery models.

One of the primary growth factors for the Digital Navigator Platforms for Medicaid Patients market is the expanding Medicaid population, particularly in the United States, where policy reforms and Medicaid expansion initiatives have significantly increased the number of beneficiaries. As Medicaid covers a substantial portion of low-income individuals, there is a critical need for digital tools that can bridge gaps in health literacy, care coordination, and benefits navigation. Digital navigator platforms are uniquely positioned to address these challenges by offering tailored solutions that guide patients through complex healthcare systems, streamline access to benefits, and enhance overall patient engagement. Additionally, the integration of artificial intelligence and machine learning within these platforms is enabling more personalized patient experiences, which is further driving adoption among healthcare providers and payers.

Another significant driver is the rapid digitalization of healthcare services, accelerated by the COVID-19 pandemic. The increased reliance on telehealth, remote patient monitoring, and digital communication channels has underscored the importance of platforms that can facilitate seamless navigation for Medicaid patients. Digital navigator platforms are increasingly being adopted by hospitals, community health centers, and government agencies to improve care coordination, reduce administrative burdens, and ensure continuity of care. Furthermore, these platforms are instrumental in addressing social determinants of health by connecting patients to community resources, transportation, and other support services, thereby improving health outcomes and reducing disparities among vulnerable populations.

Social Determinants of Health play a crucial role in shaping the health outcomes of Medicaid patients. These determinants include factors such as socioeconomic status, education, neighborhood and physical environment, employment, and social support networks, as well as access to healthcare. Digital navigator platforms are increasingly being leveraged to address these determinants by connecting patients to essential community resources. By integrating social determinants of health into their frameworks, these platforms can provide a more holistic approach to patient care, ensuring that non-medical factors contributing to health disparities are effectively managed. This comprehensive approach not only improves individual patient outcomes but also enhances the overall efficiency of healthcare systems by reducing the need for emergency interventions and hospital readmissions.

The evolving regulatory landscape is also playing a pivotal role in shaping the growth trajectory of the Digital Navigator Platforms for Medicaid Patients market. Governments and healthcare organizations are prioritizing value-based care models, which emphasize outcomes, patient satisfaction, and cost efficiency. Digital navigator platforms support these objectives by enabling proactive outreach, closing care gaps, and facilitating communication between patients, providers, and payers. The ongoing focus on interoperability and data exchange standards is further enhancing the capabilities of these platforms, allowing for more comprehensive patient records and better-informed clinical decision-making. As a result, the market is witnessing increased investments from both public and private sectors, fostering innovation and expanding the reach of digital navigator solutions.

From a regional perspective, North America continues to dominate the Digital Navigator Platforms for Medicaid Patients market, accounting for the largest share

The All CMS Data Feeds dataset is an expansive resource offering access to 118 unique report feeds, providing in-depth insights into various aspects of the U.S. healthcare system. 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 tools and platforms. This ensures that users can easily integrate the data into their existing wo...