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TwitterThis statistic depicts the monthly change in Medicare enrollments from ************** to ********* in the United States. During this period, there was a decline in enrollment levels from September to May, followed by an acceleration of growth from May through to July.
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TwitterMedicaid 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.
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TwitterThe table Master Beneficiary Summary File - Chronic Conditions (CC27) is part of the dataset Medicare 20% [2019-2020] Enrollment/Summary, available at https://stanford.redivis.com/datasets/2ewt-f9320gt59. It contains 13205788 rows across 84 variables.
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TwitterThis statistic depicts the projected average annual growth in Medicare enrollment in the United States from 2010 to 2050. For the period 2010-2020, the average annual growth is expected to be three percent.
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TwitterThe Medicare COVID-19 Hospitalization Trends dataset contains aggregate information from Medicare Fee-for-Service claims, Medicare Advantage encounter, and Medicare enrollment data. It provides insight around the groups of beneficiaries that were hospitalized at different points during the pandemic. CMS publicly released the first Preliminary Medicare COVID-19 Snapshot in June 2020 during the early stages of the Public Health Emergency for COVID-19. That report focused on COVID-19 cases and hospitalizations data for Medicare beneficiaries with a COVID-19 diagnosis. Throughout 2020 and 2021, that report was subsequently updated with refreshed data 13 times. Beginning in October 2021, CMS shifted its public COVID-19 reporting away from cumulative case and hospitalization rates to hospitalization trends over time with the release of this report, the Medicare COVID-19 Hospitalization Trends Report. All prior releases of both the Preliminary Medicare COVID-19 Snapshot and the Medicare COVID-19 Hospitalization Trends Report are available for download in the Medicare COVID-19 Data - Prior Releases file.
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TwitterThe table Master Beneficiary Summary File (MBSF) - Base (A/B/C/D) is part of the dataset Medicare 20% [2019-2020] Enrollment/Summary, available at https://stanford.redivis.com/datasets/2ewt-f9320gt59. It contains 26718736 rows across 185 variables.
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TwitterThe Public Provider Enrollment data for Medicare fee-for-service includes providers who are actively approved to bill Medicare. This dataset contains an enrollment ID crosswalk between those individual providers reassigning their benefits and those providers receiving the reassignment of benefits.
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TwitterThis 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.
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BackgroundThe objective of this study was to examine differences in availability and use of telehealth services among Medicare enrollees according to Alzheimer’s disease and related dementias (ADRD) status and enrollment in Medicare Advantage (MA) versus Traditional Medicare (TM) during the period surrounding the COVID-19 pandemic.MethodsThis was a retrospective cross-sectional analysis of data from community-dwelling MA and TM enrollees with and without ADRD from the Medicare Current Beneficiary Survey (MCBS) Fall 2020 and Winter 2021 COVID-19 Supplement Public Use Files. We examined self-reported availability of telehealth service before and during the COVID-19 pandemic and use of telehealth services during COVID-19. We analyzed marginal effects under multivariable logistic regression.ResultsThere were 13,700 beneficiaries with full-year enrollment in MA (6,046) or TM (7,724), 518 with ADRD and 13,252 without ADRD. Telehealth availability during COVID-19 was positively associated with having a higher income (2.81 pp. [percentage points]; 95% CI: 0.57, 5.06), having internet access (7.81 pp.; 95% CI: 4.96, 10.66), and owning telehealth-related technology (3.86; 95% CI: 1.36, 6.37); it was negatively associated with being of Black Non-Hispanic ethnicity (−8.51 pp.; 95% CI: −12.31, −4.71) and living in a non-metro area (−8.94 pp.; 95% CI: −13.29, −4.59). Telehealth availability before COVID-19 was positively associated with being of Black Non-Hispanic ethnicity (9.34 pp.; 95% CI: 3.74, 14.94) and with enrollment in MA (4.72 pp.; 95% CI: 1.63, 7.82); it was negatively associated having dual-eligibility (−5.59 pp.; 95% CI: −9.91, −1.26). Telehealth use was positively associated with being of Black Non-Hispanic ethnicity (6.47 pp.; 95% CI: 2.92, 10.01); it was negatively associated with falling into the age group of 75+ years (−4.98 pp.; 95% CI: −7.27, −2.69) and with being female (−4.98 pp.; 95% CI: −7.27, −2.69).ConclusionTelehealth services were available to and used by Medicare enrollees with ADRD to a similar extent compared to their non-ADRD counterparts. Telehealth services were available to MA enrollees to a greater extent before COVID-19 but not during COVID-19, and this group did not use telehealth services more than TM enrollees during COVID-19.
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TwitterMedicare outlays in the United States amounted to 1.01 trillion U.S. dollars in 2023. The forecast predicts an increase in Medicare outlays up to one trillion U.S. dollars in 2034.
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TwitterThe 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.
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TwitterThe table MBSF: Other Chronic/Potentially Disabling Conditions is part of the dataset Medicare 20% [2019-2020] Enrollment/Summary, available at https://stanford.redivis.com/datasets/2ewt-f9320gt59. It contains 26718736 rows across 83 variables.
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TwitterThis 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.
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TwitterOver ** 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.
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TwitterWeekly Cumulative Influenza Vaccination Coverage, by Flu Season and Race/Ethnicity, Medicare Fee-For-Service Beneficiaries aged ≥65 years, United States
• Influenza vaccination coverage among Medicare fee-for-service beneficiaries aged ≥65 years is assessed using data files from the Medicare Fee-For-Service (FFS) administrative claims data managed by the Centers for Medicare & Medicaid Services (CMS).
• Weekly influenza vaccination coverage estimates were calculated using Kaplan-Meier survival analysis, based on beneficiaries enrolled as of August 1, 2019 and followed through May 31, 2020 for 2019-20 flu season; and enrolled as of August 1, 2020 and followed through May 31, 2021 for 2020-21 flu season; and enrolled as of Aug 1, 2021 and followed through May 28, 2022 for the 2021-22 flu season.
• Additional information about data source is available https://www2.ccwdata.org/web/guest/home/.
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TwitterThis 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.
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TwitterBy 2025, around ** percent of all Medicare Advantage beneficiaries were enrolled in special needs plans (SNPs). SNPs penetration rate has significantly increased in the provided time interval. This statistic shows the SNPs penetration into the total Medicare Advantage (MA) market in the United States from 2020 to 2025.
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TwitterThe dataset contains information on the non-PACE (Programs of All-Inclusive Care for the Elderly) risk scores 2016-2020. Risk scores used in the ratebooks are calculated using the model to be used in the payment year. The beneficiaries included in the state-level risk scores in this dataset are those enrolled in fee-for-service (FFS) population.
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TwitterThis table presents the number of pregnant and postpartum Medicaid and CHIP beneficiaries, 2017-2021. It includes (1) the number and percentage of beneficiaries ever pregnant in the year; (2) the number and percentage of live births in the year; (3) the number and percentage of miscarriages, stillbirths, or terminations in the year; and (4) the number and percentage of births with an unknown delivery outcome in the year. 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 identifying this population. Data for a state are considered unusable based on DQ Atlas thresholds for the following topics: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Claims Volume - IP, Diagnosis Code - IP, Diagnosis Code - OT, Procedure Codes - OT Professional. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Data from Maryland, Tennessee, and Utah are omitted from the tables due to data quality concerns. Maryland was excluded in 2017 due to unusable diagnosis codes in the IP file and the OT file. Tennessee was excluded due to unusable diagnosis codes in the IP file in 2017 - 2019. Utah was excluded due to unusable procedure codes on OT professional claims in 2017 - 2020. In addition, states with a high data quality concern on one or more measures are noted in the table in the "Data Quality" column. 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.
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TwitterThis statistic depicts the monthly change in Medicare enrollments from ************** to ********* in the United States. During this period, there was a decline in enrollment levels from September to May, followed by an acceleration of growth from May through to July.