Total Medicaid Enrollees - VIII Group Break Out Report Reported on the CMS-64

The enrollment information is a state-reported count of unduplicated individuals enrolled in the state’s Medicaid program at any time during each month in the quarterly reporting period. The enrollment data identifies the total number of Medicaid enrollees and, for states that have expanded Medicaid, provides specific counts for the number of individuals enrolled in the new adult eligibility group, also referred to as the “VIII Group”. The VIII Group is only applicable for states that have expanded their Medicaid programs by adopting the VIII Group. This data includes state-by-state data for this population as well as a count of individuals whom the state has determined are newly eligible for Medicaid. All 50 states, the District of Columbia and the US territories are represented in these data.

Notes: 1. “VIII GROUP” is also known as the “New Adult Group.” 2. The VIII Group is only applicable for states that have expanded their Medicaid programs by adopting the VIII Group. VIII Group enrollment information for the states that have not expanded their Medicaid program is noted as “N/A.”

Data on Medicaid coverage among persons under age 65 by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Health Interview Survey, health insurance supplements (1984, 1989, 1994-1996). Starting with 1997, data are from the family core and the sample adult questionnaires. Data for level of difficulty are from the 2010 Quality of Life, 2011-2017 Functioning and Disability, and 2018 Sample Adult questionnaires. For more information on the National Health Interview Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by major eligibility group (children, adult expansion group, adult, aged, persons with disabilities, or COVID newly-eligible). There are three metrics presented: (1) the number of beneficiaries ever enrolled in each major eligibility group over the year (duplicated count); (2) the number of beneficiaries enrolled in each major eligibility group as of an individual’s last month of enrollment (unduplicated count); and (3) average monthly enrollment in each major eligibility group.

These metrics are based on data in the T-MSIS Analytic Files (TAF). 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 topic Eligibility Group Code. 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.

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 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.

Medicaid CMS-64 New Adult Group Expenditures

  Description

This dataset reports summary level expenditure data associated with the new adult group established under the Affordable Care Act. These state expenditures are reported through the federal Medicaid Budget and Expenditure System (MBES). Notes:

“VIII GROUP” is also known as the “New Adult Group.” The VIII Group is only applicable for states that have expanded their Medicaid programs by adopting the VIII Group. VIII… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/medicaid-cms-64-new-adult-group-expenditures.

This layer shows the market potential for an adult to carry medical/hospital/accident insurance in the U.S. in 2016 in a multiscale map (by country, state, county, ZIP Code, tract, and block group). The pop-up is configured to include the following information for each geography level:Market Potential Index and count of adults expected to carry medical/hospital/accident insuranceMarket Potential Index and count of adults expected to carry different types of medical insurance (HMO, PPO, etc)Market Potential Index and count of adults expected to carry insurance from various sources (Medicare, place of work, etc)Esri's 2016 Market Potential (MPI) data measures the likely demand for a product or service in an area. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product or service. An MPI compares the demand for a specific product or service in an area with the national demand for that product or service. The MPI values at the US level are 100, representing average demand for the country. A value of more than 100 represents higher demand than the national average, and a value of less than 100 represents lower demand than the national average. For example, an index of 120 implies that demand in the area is 20 percent higher than the US average; an index of 80 implies that demand is 20 percent lower than the US average. See Market Potential database to view the methodology statement and complete variable list.Esri's Financial & Insurance Data Collection includes data that measures the likely demand for financial and insurance products and services, including health insurance. The database includes an expected number of consumers and a Market Potential Index (MPI) for each product, activity, or service. See the United States Data Browser to view complete variable lists for each Esri demographics collection.Additional Esri Resources:U.S. 2016/2021 Esri Updated DemographicsEssential demographic vocabularyEsri's arcgis.com demographic map layers

Objective: A one third reduction of premature deaths from non-communicable diseases by 2030 is a target of the United Nations Sustainable Development Goal for Health. Unlike in other developed nations, premature mortality in the United States (US) is increasing. The state of Oklahoma suffers some of the greatest rates in the US of both all-cause mortality and overdose deaths. Medicaid opioids are associated with overdose death at the patient level, but the impact of this exposure on population all-cause mortality is unknown. The objective of this study was to look for an association between Medicaid spending, as proxy measure for Medicaid opioid exposure, and all-cause mortality rates in the 45–54-year-old American Indian/Alaska Native (AI/AN45-54) and non-Hispanic white (NHW45-54) populations.Methods: All-cause mortality rates were collected from the US Centers for Disease Control & Prevention Wonder Detailed Mortality database. Annual per capita (APC) Medicaid spending, and APC Medicare opioid claims, smoking, obesity, and poverty data were also collected from existing databases. County-level multiple linear regression (MLR) analyses were performed. American Indian mortality misclassification at death is known to be common, and sparse populations are present in certain counties; therefore, the two populations were examined as a combined population (AI/NHW45-54), with results being compared to NHW45-54 alone.Results: State-level simple linear regressions of AI/NHW45-54 mortality and APC Medicaid spending show strong, linear correlations: females, coefficient 0.168, (R2 0.956; P < 0.0001; CI95 0.15, 0.19); and males, coefficient 0.139 (R2 0.746; P < 0.0001; CI95 0.10, 0.18). County-level regression models reveal that AI/NHW45-54 mortality is strongly associated with APC Medicaid spending, adjusting for Medicare opioid claims, smoking, obesity, and poverty. In females: [R2 0.545; (F)P < 0.0001; Medicaid spending coefficient 0.137; P < 0.004; 95% CI 0.05, 0.23]. In males: [R2 0.719; (F)P < 0.0001; Medicaid spending coefficient 0.330; P < 0.001; 95% CI 0.21, 0.45].Conclusions: In Oklahoma, per capita Medicaid spending is a very strong risk factor for all-cause mortality in the combined AI/NHW45-54 population, after controlling for Medicare opioid claims, smoking, obesity, and poverty.

2014 Child and Adult Health Care Quality Measures

  Description

Performance rates on frequently reported health care quality measures in the CMS Medicaid/CHIP Child and Adult Core Sets, for FFY 2014 reporting. Dataset contains both child and adult measures. Source: Mathematica analysis of FFY 2014 Child and Adult CARTS reports as of May 8, 2015, as published in the 2015 Secretary's Reports on the Quality of Care in Medicaid/CHIP.

  Dataset Details

Publisher:… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/2014-child-and-adult-health-care-quality-measures.

2022 Child and Adult Health Care Quality Measures Quality

  Description

Performance rates on frequently reported health care quality measures in the CMS Medicaid/CHIP Child and Adult Core Sets, for FFY 2022 reporting. Source: Mathematica analysis of MACPro and Form CMS-416 reports for the FFY 2022 reporting cycle. Dataset revised September 2023. For more information, see the Children's Health Care Quality Measures and Adult Health Care Quality Measures webpages.… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/2022-child-and-adult-health-care-quality-measures.