In 2023, just four in ten Medicaid/CHIP enrollees were White, non-Hispanic. In comparison, roughly three-quarters of Medicare beneficiaries were White. The Affordable Care Act (ACA) Medicaid expansion in 2014, has helped reduce racial disparities in access to healthcare in the United States. Medicaid eligibility Medicaid provides health coverage to certain low-income individuals, families, children, pregnant women, the elderly, and persons with disabilities. Each state has its own Medicaid eligibility criteria in accordance with federal guidelines. As a result, Medicaid eligibility and benefits differ widely from state to state. Medicaid expansion provision under the Affordable Care Act (ACA) allows states to provide coverage for low-income adults by expanding eligibility for Medicaid to 138 percent of the federal poverty line (FPL). Medicaid coverage gap Uninsured individuals who live in states that have chosen not to expand Medicaid under the Affordable Care Act (ACA) are referred to as being in the Medicaid coverage gap. As of January 2021, 12 states have not adopted the Medicaid expansion provision under the Affordable Care Act (ACA). More than two million uninsured adults fall into this coverage gap, and among them, more than 60 percent are people of color.

In 2023, some 47.6 percent of Medicaid and CHIP enrollees were aged between 18 and 64 years, while adults aged 65 years accounted for only eight percent of enrollees. Medicaid program is funded jointly by the federal and the state governments, it provided coverage to nearly 19.5 percent of the U.S. population in 2022. Medicaid vs CHIPMedicaid and the Children’s Health Insurance Program (CHIP) both provide health insurance coverage for children from low-income families. Children who are not eligible for Medicaid but who would otherwise be unable to obtain insurance through a family plan are covered by CHIP. More than five million children were enrolled in CHIP in the U.S. in 2023. Medicaid and CHIP funding rateThe Federal Medical Assistance Percentages (FMAPs) are used to calculate the amount of federal matching funds for State Medicare and CHIP programs. To encourage states to expand coverage for uninsured children the federal matching rates for CHIP are generally 15 points higher than the Medicaid rate. However, unlike permanent federal funding for Medicaid, CHIP federal funding is capped and due to expire in FY 2027.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees by race and ethnicity overall and by three subpopulation topics: scope of Medicaid and CHIP benefits, age group, and eligibility category. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, and Puerto Rico who were enrolled for at least one day in the calendar year. Enrollees in Guam, American Samoa, the Northern Mariana Islands, and the U.S. Virgin Islands are not included. Results shown for the age group and eligibility category subpopulation topics only include enrollees with comprehensive Medicaid and CHIP benefits in the year. Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on information shown in the brief: "Race and ethnicity of the national Medicaid and CHIP population in 2020." Enrollees are assigned to six race and ethnicity categories using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG). Enrollees are assigned to a child (ages 0-18) or adult (ages 19 and older) subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to the comprehensive benefits or limited benefits subpopulation according to the criteria in the "Identifying Beneficiaries with Full-Scope, Comprehensive, and Limited Benefits in the TAF" DQ Atlas brief. Enrollees are assigned to an eligibility category subpopulation using their latest reported eligibility group code, CHIP code, and age in the calendar year. Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.

Over ** million Americans were estimated to be enrolled in the Medicaid program as of 2023. That is a significant increase from around ** million ten years earlier. Medicaid is basically a joint federal and state health program that provides medical coverage to low-income individuals and families. Currently, Medicaid is responsible for ** percent of the nation’s health care bill, making it the third-largest payer behind private insurances and Medicare. From the beginning to ObamacareMedicaid was implemented in 1965 and since then has become the largest source of medical services for Americans with low income and limited resources. The program has become particularly prominent since the introduction of President Obama’s health reform – the Patient Protection and Affordable Care Act - in 2010. Medicaid was largely impacted by this reform, for states now had the opportunity to expand Medicaid eligibility to larger parts of the uninsured population. Thus, the percentage of uninsured in the United States decreased from over ** percent in 2010 to *** percent in 2022. Who is enrolled in Medicaid?Medicaid enrollment is divided mainly into four groups of beneficiaries: children, adults under 65 years of age, seniors aged 65 years or older, and disabled people. Children are the largest group, with a share of approximately ** percent of enrollees. However, their share of Medicaid expenditures is relatively small, with around ** percent. Compared to that, disabled people, accounting for **** percent of total enrollment, were responsible for **** percent of total expenditures. Around half of total Medicaid spending goes to managed care and health plans.

The Medicaid Managed Care Enrollment Report profiles enrollment statistics on Medicaid managed care programs on a plan-specific level. The managed care enrollment statistics include enrollees receiving comprehensive benefits and limited benefits and are point-in-time counts. Because Medicaid beneficiaries may be enrolled concurrently in more than one type of managed care program (e.g., a Comprehensive MCO and a BHO), users should not sum enrollment across all program types, since the total would count individuals more than once and, in some states, exceed the actual number of Medicaid enrollees. Comprehensive MCOs cover acute, primary, and specialty medical care services; they may also cover behavioral health, long-term services and supports, and other benefits in some states. Limited benefit managed care programs, including PCCM, MLTSS only, BHO, Dental, Transportation, and Other cover a narrower set of services. 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. "--" indicates states that do not operate programs of a given type. 0 signifies that a state operated a program of this type in 2014, but it ended before July 1, 2014, or began after that date.

This report provides information at the state and town level of people served by the Connecticut Department of Social Services for the Calendar Years 2012-2024 by demographics (gender, age-groups, race, and ethnicity) at the state and town level by Medical Benefit Plan (Husky A-D, Husky limited benefit, MSP and Other Medical); Assistance Type (Cash, Food, Medical, Other); and Program (CADAP, CHCPE, CHIP, ConnTRANS, Medicaid, Medical, MSP, Refugee Cash, Repatriation, SAGA, SAGA Funeral, SNAP, Social Work Services, State Funded Medical, State Supplement, TFA). NOTE: On 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. Effective January 1, 2021, this coverage group have been separated: (1) the COVID-19 Testing Coverage for the Uninsured is now G06-I and is now listed as a limited benefit plan that rolls up into “Program Name” of Medicaid and “Medical Benefit Plan” of HUSKY Limited Benefit; (2) the emergency medical coverage has been separated into G06-II as a limited benefit plan that rolls up into “Program Name” of Emergency Medical and “Medical Benefit Plan” of Other Medical. NOTE: 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 has 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. 2. 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 change in methodology causes 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. NOTE: 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.

This data set includes monthly counts and rates (per 1,000 beneficiaries) of acute care services, including emergency department (ED) visits, inpatient stays, intensive care unit (ICU) stays, and ICU stays that include ventilator use, provided to Medicaid and CHIP beneficiaries, by state. Users can filter to acute care services for any reason, or acute care services for COVID-19. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating acute care services measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Diagnosis Code - IP, Diagnosis Code - OT, Procedure Codes - OT Professional. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

This data set includes monthly counts and rates (per 1,000 beneficiaries) of behavioral health services, including emergency department services, inpatient services, intensive outpatient/partial hospitalizations, outpatient services, or services delivered through telehealth, provided to Medicaid and CHIP beneficiaries, by state. Users can filter by either mental health disorder or substance use disorder. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating behavioral health services measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Diagnosis Code - IP, Diagnosis Code - OT. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

This dataset aggregates and displays the number of New York State Medicaid enrollees by eligibility year and month within each NYS Economic Region; health insurance plan information; and enrollee demographics. For more information, check out http://www.health.ny.gov/health_care/medicaid/, or go to the "About" tab.

There is a growing consensus among healthcare professionals and policymakers that the way healthcare has historically been provided within the United States is insufficient to meet the needs of the population. The incidence and prevalence of many chronic diseases, coupled with the challenges associated with accessing prenatal care, are notable across the country and globally. In response to this problem OSF HealthCare and four federally qualified health centers partnered together to reimagine how health care can be delivered to underserved populations. This case study provides a practical perspective on how care delivery is enhanced, delivered, and improved through use of digital technologies to expand access to care and chronic disease management in the Medicaid population. Through the formation of the Medicaid Innovation Collaborative, which is partially funded by the Illinois Department of Health and Family Services, digital health programs tailored to individual patient needs and supported by remote and in-person digital health navigators (DHNs), are provided with 24/7/365 access to care from a diverse team of healthcare professionals. In this article, we describe the essential program elements, design, and implementation of four novel programs. While developing digital care solutions for adult Medicaid recipients across the state has been challenging, our work illustrates the feasibility of such an endeavor. To date, we have outreached to over 418,037 patients, and enrolled 38,964 in our diverse programs that include, but are not limited to, helping patients managing chronic disease, increasing access to prenatal care, offering support for health literacy and wellness, and screening for the social determinants of health.

California has more Medicaid and CHIP enrollees than any other state in the United States. As of April 2023, approximately ** million Americans were enrolled in the Medicaid health insurance programs in California, which accounted for approximately ** percent of the total number of Medicaid enrollees nationwide (**** million). Blow to Medicaid expansion plans California is one of many states that has expanded its Medicaid program under the Affordable Care Act (ACA) to encourage more low-income adults to sign up for health coverage. One of the original aims of the ACA was to limit some of the variations in state Medicaid programs, but the Supreme Court ruled that the expansion should be optional. Governors of the states that did not expand said they were concerned about long-term costs. California is the leading state for Medicaid expenditure, spending approximately **** billion U.S. dollars in FY2020. Health coverage for children The Children’s Health Insurance Program (CHIP) was created as a complement to Medicaid, expanding the reach of government-funded health coverage to more children in low-income families. As of May 2021, over **** million children were enrolled in Medicaid/CHIP programs in California, more than any other state. As of January 2021, the median Medicaid/CHIP eligibility level for children was *** percent of the federal poverty level.

This data set includes monthly counts and rates (per 1,000 beneficiaries) of services provided via telehealth, including live audio video, remote patient monitoring, store and forward, and other telehealth, to Medicaid and CHIP beneficiaries, by state. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating telehealth services measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Claims Volume - OT, Procedure Codes - OT Professional. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

Medicaid is an important public health insurance for individuals with a low income, those that are pregnant, disabled or are children. It was projected that by 2020 there would be approximately **** million Medicaid enrollees. By 2027 that number is expected to increase to ** million individuals covered.

Medicaid in the focus

Medicaid has recently been in the news for several reasons. A proposed Medicaid expansion was announced with the implementation of the Affordable Care Act in 2010. According to the expansion, all states were given the option to expand Medicaid programs to help provide insurance coverage to millions of U.S. Americans. As of 2019, ** states have accepted federal funding to expand their Medicaid programs. Medicaid, after Medicare and private insurance, provides a significant proportion of the total health expenditures in the United States. In general, Medicaid expenditure, like the number of enrollees, has been growing over time.

Medicaid demographics

A significant proportion of Medicaid enrollees in the U.S. are children and low-income adults. Despite children accounting for most of the enrollees in the Medicaid program, the largest percentage of expenditures for Medicaid is dedicated to those enrolled as a disabled individual. Expenditures for the program also vary regionally. The states with the highest Medicaid expenditures include California, New York and Texas, to name a few.

This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by managed care participation (comprehensive managed care, primary care case management, MLTSS, including PACE, behavioral health organizations, nonmedical prepaid health plans, medical-only prepaid health plans, and other). There are three metrics presented: (1) the number of beneficiaries ever enrolled in each managed care plan type over the year (duplicated count); (2) the number of beneficiaries enrolled in each managed care plan type as of an individual’s last month of enrollment (duplicated count); and (3) average monthly enrollment in each managed care plan type. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some cells have a value of “DS”. Some states have serious data quality issues, making the data unusable for calculating these measures. To assess data quality, analysts used measures featured in the DQ Atlas. Data for a state and year are considered unusable or of high concern based on DQ Atlas thresholds for the topics Enrollment in CMC, Enrollment in PCCM Programs, and Enrollment in BHO Plans. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

The number of older individuals – those aged 65 and older – enrolled in the Medicaid health insurance program was projected to be *** million in 2020. Enrollment is expected to increase year-on-year and is forecast to reach ***** million by 2027.

Which enrollment group is the largest? The percentage of people covered by Medicaid has notably increased since 2000, and enrollment has accelerated in recent years due to the program’s expansion under the Affordable Care Act. The elderly represent the smallest enrollment group, and this looks set to continue in the coming years. The number of disabled enrollees is projected to grow to nearly ****** million, while children are expected to remain the largest enrollment group.

Combining Medicaid and Medicare Aged individuals can qualify for Medicaid based on their low-income or via another eligibility pathway, such as receiving Supplemental Security Income. Some seniors may also qualify for both Medicaid and Medicare, and these dual-eligible beneficiaries receive a comprehensive range of medical support. Medicare is a health insurance program primarily aimed at individuals aged 65 and older – this group accounted for around ** percent of all Medicare enrollees in 2019.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees by primary language spoken (English, Spanish, and all other languages). Results are shown overall; by state; and by five subpopulation topics: race and ethnicity, age group, scope of Medicaid and CHIP benefits, urban or rural residence, and eligibility category. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands who were enrolled for at least one day in the calendar year, except where otherwise noted. Enrollees in Guam, American Samoa, the Northern Mariana Islands, and select states with data quality issues with the primary language variable in TAF are not included. Results shown for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown overall (where subpopulation topic is "Total enrollees") exclude enrollees younger than age 5 and enrollees in the U.S. Virgin Islands. Results for states with TAF data quality issues in the year have a value of "Unusable data." Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on the brief: "Primary language spoken by the Medicaid and CHIP population in 2020." Enrollees are assigned to a primary language category based on their reported ISO language code in TAF (English/missing, Spanish, and all other language codes) (Primary Language). Enrollees are assigned to a race and ethnicity subpopulation using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG) (Race and ethnicity of the national Medicaid and CHIP population in 2020). Enrollees are assigned to an age group subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to the comprehensive benefits or limited benefits subpopulation according to the criteria in the "Identifying Beneficiaries with Full-Scope, Comprehensive, and Limited Benefits in the TAF" DQ Atlas brief. Enrollees are assigned to an urban or rural subpopulation based on the 2010 Rural-Urban Commuting Area (RUCA) code associated with their home or mailing address ZIP code in TAF (Rural Medicaid and CHIP enrollees in 2020). Enrollees are assigned to an eligibility category subpopulation using their latest reported eligibility group code, CHIP code, and age in the calendar year. Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees by urban or rural residence. Results are shown overall; by state; and by four subpopulation topics: scope of Medicaid and CHIP benefits, race and ethnicity, disability-related eligibility category, and managed care participation. These results were generated using Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Release 1 data and the Race/Ethnicity Imputation Companion File. This data set includes Medicaid and CHIP enrollees in all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands who were enrolled for at least one day in the calendar year, except where otherwise noted. Enrollees in Guam, American Samoa, and the Northern Mariana Islands are not included. Results shown overall (where subpopulation topic is "Total enrollees") and for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown for the race and ethnicity, disability category, and managed care participation subpopulation topics only include Medicaid and CHIP enrollees with comprehensive benefits. Results shown for the disability category subpopulation topic only include working-age adults (ages 19 to 64). Results for states with TAF data quality issues in the year have a value of "Unusable data." Some rows in the data set have a value of "DS," which indicates that data were suppressed according to the Centers for Medicare & Medicaid Services’ Cell Suppression Policy for values between 1 and 10. This data set is based on the brief: "Rural Medicaid and CHIP enrollees in 2020." Enrollees are assigned to an urban or rural category based on the 2010 Rural-Urban Commuting Area (RUCA) code associated with their home or mailing address ZIP code in TAF. Enrollees are assigned to the comprehensive benefits or limited benefits subpopulation according to the criteria in the "Identifying Beneficiaries with Full-Scope, Comprehensive, and Limited Benefits in the TAF" DQ Atlas brief. Enrollees are assigned to a race and ethnicity subpopulation using the state-reported race and ethnicity information in TAF when it is available and of good quality; if it is missing or unreliable, race and ethnicity is indirectly estimated using an enhanced version of Bayesian Improved Surname Geocoding (BISG) (Race and ethnicity of the national Medicaid and CHIP population in 2020). Enrollees are assigned to a disability category subpopulation using their latest reported eligibility group code and age in the year (Medicaid enrollees who qualify for benefits based on disability in 2020). Enrollees are assigned to a managed care participation subpopulation based on the managed care plan type code that applies to the majority of their enrolled-months during the year (Enrollment in CMC Plans). Please refer to the full brief for additional context about the methodology and detailed findings. Future updates to this data set will include more recent data years as the TAF data become available.

Metrics from individual Marketplaces during the current reporting period. The report includes data for the states using HealthCare.gov. Sources: HealthCare.gov application and policy data through October 6, 2024, HealthCare.gov inbound account transfer data through November 7, 2024, and T-MSIS Analytic Files (TAF) through July 2024 (TAF version 7.1). The table includes states that use HealthCare.gov. Notes: This table includes Marketplace consumers who submitted a HealthCare.gov application from March 6, 2023 - October 6, 2024 or who had an inbound account transfer from April 3, 2023 - November 7, 2024, who can be linked to an enrollment record in TAF that shows a last day of Medicaid or CHIP enrollment from March 31, 2023 - July 31, 2024. Beneficiaries with a leaving event may have continuous coverage through another coverage source, including Medicaid or CHIP coverage in another state. However, a beneficiary that lost Medicaid or CHIP coverage and regained coverage in the same state must have a gap of at least 31 days or a full calendar month. This table includes Medicaid or CHIP beneficiaries with full benefits in the month they left Medicaid or CHIP coverage. ‘Account Transfer Consumers Whose Medicaid or CHIP Coverage was Terminated’ are consumers 1) whose full benefit Medicaid or CHIP coverage was terminated and 2) were sent by a state Medicaid or CHIP agency via secure electronic file to the HealthCare.gov Marketplace in a process referred to as an inbound account transfer either 2 months before or 4 months after they left Medicaid or CHIP. 'Marketplace Consumers Not on Account Transfer Whose Medicaid or CHIP Coverage was Terminated' are consumers 1) who applied at the HealthCare.gov Marketplace and 2) were not sent by a state Medicaid or CHIP agency via an inbound account transfer either 2 months before or 4 months after they left Medicaid or CHIP. Marketplace consumers counts are based on the month Medicaid or CHIP coverage was terminated for a beneficiary. Counts include all recent Marketplace activity. HealthCare.gov data are organized by week. Reporting months start on the first Monday of the month and end on the first Sunday of the next month when the last day of the reporting month is not a Sunday. HealthCare.gov data are through Sunday, October 6. Data are preliminary and will be restated over time to reflect consumers most recent HealthCare.gov status. Data may change as states resubmit T-MSIS data or data quality issues are identified. See the data and methodology documentation for a full description of the data sources, measure definitions, and general data limitations. Data notes: The percentages for the 'Marketplace Consumers Not on Account Transfer whose Medicaid or CHIP Coverage was Terminated' data record group are marked as not available (NA) because the full population of consumers without an account transfer was not available for this report. Virginia operated a Federally Facilitated Exchange (FFE) on the HealthCare.gov platform during 2023. In 2024, the state started operating a State Based Marketplace (SBM) platform. This table only includes data about 2023 applications and policies obtained through the HealthCare.gov Marketplace. Due to limited Marketplace activity on the HealthCare.gov platform in November 2023, data from November 2023 onward are excluded. The cumulative count and percentage for Virginia and the HealthCare.gov total reflect Virginia data from April 2023 through October 2023. APTC: Advance Premium Tax Credit; CHIP: Children's Health Insurance Program; QHP: Qualified Health Plan; NA: Not Available

This data set includes monthly counts and percentages of Medicaid and CHIP beneficiaries, by state, who received at least one service for each of the following conditions: acute bronchitis, acute respiratory distress, bronchitis not other specified (NOS), COVID-19 (based on the presence of diagnosis code U07.1), influenza, lower or acute respiratory infection, pneumonia, respiratory infection NOS, and suspected COVID-19 (based on the presence of diagnosis code B97.29).

These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating COVID-related conditions measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Claims Volume - IP, Diagnosis Code - IP, Diagnosis Code - OT, Procedure Codes - OT Professional. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data.

Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

Context

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