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 2022, 36 percent of the uninsured population eligible for Medicaid were Hispanic. Among those who were eligible for Medicaid or CHIP but were uninsured, around six in ten were people of color. This statistic shows the distribution of uninsured nonelderly population by eligible for Medicaid or CHIP in the United States in 2022.

This dataset includes the number of people enrolled in DSS services by town and by ethnicity 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.

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.

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.

In 2023, approximately ******** percent of the Hispanic population in the United States did not have health insurance, a historical low since 2010. In 2023, the national average was *** percent. White Americans had a below-average rate of just *** percent, whereas *** percent of Black Americans had no health insurance.Impact of the Affordable Care ActThe Affordable Care Act (ACA), also known as Obamacare, was enacted in March 2010, which expanded the Medicaid program, made affordable health insurance available to more people and aimed to lower health care costs by supporting innovative medical care delivery methods. Though it was enacted in 2010, the full effects of it weren’t seen until 2013, when government-run insurance marketplaces such as HealthCare.gov were opened. The number of Americans without health insurance fell significantly between 2010 and 2015, but began to rise again after 2016. What caused the change?The Tax Cuts and Jobs Act of 2017 has played a role in decreasing the number of Americans with health insurance, because the individual mandate was repealed. The aim of the individual mandate (part of the ACA) was to ensure that all Americans had health coverage and thus spread the costs over the young, old, sick and healthy by imposing a large tax fine on those without coverage.

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.

In 2022, just under 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.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees who received mental health (MH) or substance use disorder (SUD) services, overall and by six subpopulation topics: age group, sex or gender identity, race and ethnicity, urban or rural residence, eligibility category, and primary language. 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, ages 12 to 64 at the end of the calendar year, who were not dually eligible for Medicare and were continuously enrolled with comprehensive benefits for 12 months, with no more than one gap in enrollment exceeding 45 days. Enrollees who received services for both an MH condition and SUD in the year are counted toward both condition categories. Enrollees in Guam, American Samoa, the Northern Mariana Islands, and select states with TAF data quality issues are not included. Results shown for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown for the primary language subpopulation topic exclude select states with data quality issues with the primary language variable in TAF. 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: "Medicaid and CHIP enrollees who received mental health or SUD services in 2020." Enrollees are assigned to an age group subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to a sex or gender identity subpopulation using their latest reported sex in the calendar year. 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 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. Enrollees are assigned to a primary language subpopulation based on their reported ISO language code in TAF (English/missing, Spanish, and all other language codes) (Primary Language). 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 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.

In 2023, ten percent - or around 5.85 million - of all Medicare beneficiaries in the United States were Hispanic. This statistic depicts the distribution of Medicare beneficiaries in 2023, by ethnicity.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees who received a well-child visit paid for by Medicaid or CHIP, overall and by five subpopulation topics: age group, race and ethnicity, urban or rural residence, program type, and primary language. 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, except where otherwise noted. Enrollees in Guam, American Samoa, and the Northern Mariana Islands are not included. Results include enrollees with comprehensive Medicaid or CHIP benefits for all 12 months of the year and who were younger than age 19 at the end of the calendar year. Results shown for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown for the primary language subpopulation topic exclude select states with data quality issues with the primary language variable in TAF. 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: "Medicaid and CHIP enrollees who received a well-child visit in 2020." Enrollees are identified as receiving a well-child visit in the year according to the Line 6 criteria in the Form CMS-416 reporting instructions. Enrollees are assigned to an age group subpopulation using age as of December 31st of the calendar year. 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 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 a program type subpopulation based on the CHIP code and eligibility group code that applies to the majority of their enrolled-months during the year (Medicaid-Only Enrollment; M-CHIP and S-CHIP Enrollment). Enrollees are assigned to a primary language subpopulation based on their reported ISO language code in TAF (English/missing, Spanish, and all other language codes) (Primary Language). 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.

This data set includes annual counts and percentages of Medicaid enrollees who are eligible for benefits based on disability, overall; by reason for qualification of disability benefits; and by four subpopulation topics: age group, dual eligibility status, race and ethnicity, 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 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. The Children’s Health Insurance Program (CHIP) does not confer eligibility based on disability, so Medicaid expansion CHIP (M-CHIP) and separate CHIP (S-CHIP) enrollees are not included. Results shown for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown for the dual eligibility, race and ethnicity, and managed care participation subpopulation topics are restricted to working-age adults (ages 19 to 64) with comprehensive Medicaid benefits. 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: "Medicaid enrollees who qualify for benefits based on disability in 2020." Enrollees are assigned to a disability category based on their latest reported eligibility group code and age in the calendar year. Enrollees are assigned to an age group subpopulation using age as of December 31st of the calendar year. Enrollees are assigned to a dual eligibility status subpopulation based on the dual eligibility code that applies to the majority of their enrolled-months during the year (Dual Eligibility Code). 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 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.

This data set includes annual counts and percentages of Medicaid and Children’s Health Insurance Program (CHIP) enrollees who received a well-child visit paid for by Medicaid or CHIP, overall and by five subpopulation topics: age group, race and ethnicity, urban or rural residence, program type, and primary language. 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, except where otherwise noted. Enrollees in Guam, American Samoa, and the Northern Mariana Islands are not included. Results include enrollees with comprehensive Medicaid or CHIP benefits for all 12 months of the year and who were younger than age 19 at the end of the calendar year. Results shown for the race and ethnicity subpopulation topic exclude enrollees in the U.S. Virgin Islands. Results shown for the primary language subpopulation topic exclude select states with data quality issues with the primary language variable in TAF. 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: "Medicaid and CHIP enrollees who received a well-child visit in 2020." Enrollees are identified as receiving a well-child visit in the year according to the Line 6 criteria in the Form CMS-416 reporting instructions. Enrollees are assigned to an age group subpopulation using age as of December 31st of the calendar year. 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 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 a program type subpopulation based on the CHIP code and eligibility group code that applies to the majority of their enrolled-months during the year (Medicaid-Only Enrollment; M-CHIP and S-CHIP Enrollment). Enrollees are assigned to a primary language subpopulation based on their reported ISO language code in TAF (English/missing, Spanish, and all other language codes) (Primary Language). 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.

The percentage of Americans covered by the Medicaid public health insurance plan increased from **** percent in 2020 to around **** percent in 2023. However, the percentage of those insured through Medicaid remains lower than the peak of **** percent in 2015. The expansion of Medicaid The Affordable Care Act (ACA) provided the option for states to expand Medicaid eligibility to people whose income was below a particular threshold. The ACA’s major coverage expansion came into force in 2014, and the number of individuals estimated to be enrolled in Medicaid has since surpassed ** million. More than ** million children were enrolled in the program in 2018, representing ** percent of overall Medicaid enrollment. State Medicaid coverage Initially, the ACA mandated that all state Medicaid programs would have to be extended to provide medical coverage to nearly all low-income groups. However, the Supreme Court rejected that part of the act in 2012, leaving the door open for states to make their own decision on whether they expand their plans. As of September 2021, ** states plus the District of Columbia have adopted the Medicaid expansion.

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. 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 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.

This data collection supplies standard monthly labor force data as well as supplemental data on work experience, income, noncash benefits, and migration. Comprehensive information is given on the employment status, occupation, and industry of persons 15 years old and older. Additional data are available concerning weeks worked and hours per week worked, reason not working full-time, total income and income components, and residence on March 1, 1992. This file also contains data covering nine noncash income sources: food stamps, school lunch programs, employer-provided group health insurance plans, employer-provided pension plans, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance. Information on demographic characteristics, such as age, sex, race, household relationship, and Hispanic origin, are available for each person in the household enumerated. (Source: ICPSR, retrieved 06/23/2011)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR06244.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

IntroductionTelehealth can potentially improve the quality of healthcare through increased access to primary care. While telehealth use increased during the COVID-19 pandemic, racial/ethnic disparities in the use of telemedicine persisted during this period. Little is known about the relationship between health coverage and patient race/ethnicity after the onset of the COVID-19 pandemic.ObjectiveThis study examines how differences in patient race/ethnicity and health coverage are associated with the number of in-person vs. telehealth visits among patients with chronic conditions before and after California's stay-at-home order (SAHO) was issued on 19 March 2020.MethodsWe used weekly patient visit data (in-person (N = 63, 491) and telehealth visits (N = 55, 472)) from seven primary care sites of an integrated, multi-specialty medical group in Los Angeles County that served a diverse patient population between January 2020 and December 2020 to examine differences in telehealth visits reported for Latino and non-Latino Asian, Black, and white patients with chronic conditions (type 2 diabetes, pre-diabetes, and hypertension). After adjusting for age and sex, we estimate differences by race/ethnicity and the type of insurance using an interrupted time series with a multivariate logistic regression model to study telehealth use by race/ethnicity and type of health coverage before and after the SAHO. A limitation of our research is the analysis of aggregated patient data, which limited the number of individual-level confounders in the regression analyses.ResultsOur descriptive analysis shows that telehealth visits increased immediately after the SAHO for all race/ethnicity groups. Our adjusted analysis shows that the likelihood of having a telehealth visit was lower among uninsured patients and those with Medicaid or Medicare coverage compared to patients with private insurance. Latino and Asian patients had a lower probability of telehealth use compared with white patients.DiscussionTo address access to chronic care management through telehealth, we suggest targeting efforts on uninsured adults and those with Medicare or Medicaid coverage, who may benefit from increased telehealth use to manage their chronic care.