14 datasets found
  1. Medicaid and CHIP enrollees who received a well-child visit

    • data.virginia.gov
    • healthdata.gov
    • +2more
    csv
    Updated Jan 18, 2025
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    Centers for Medicare & Medicaid Services (2025). Medicaid and CHIP enrollees who received a well-child visit [Dataset]. https://data.virginia.gov/dataset/medicaid-and-chip-enrollees-who-received-a-well-child-visit
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    csvAvailable download formats
    Dataset updated
    Jan 18, 2025
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    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.

  2. Medicaid and CHIP enrollees who received mental health or SUD services

    • healthdata.gov
    • data.virginia.gov
    • +2more
    application/rdfxml +5
    Updated Feb 22, 2025
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    data.medicaid.gov (2025). Medicaid and CHIP enrollees who received mental health or SUD services [Dataset]. https://healthdata.gov/d/83hw-8hkc
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    xml, csv, application/rdfxml, json, tsv, application/rssxmlAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset provided by
    data.medicaid.gov
    Description

    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.

  3. Rural Medicaid and CHIP enrollees

    • catalog.data.gov
    • data.virginia.gov
    • +1more
    Updated Jul 11, 2025
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    Centers for Medicare & Medicaid Services (2025). Rural Medicaid and CHIP enrollees [Dataset]. https://catalog.data.gov/dataset/rural-medicaid-and-chip-enrollees
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    Dataset updated
    Jul 11, 2025
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    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.

  4. Primary language spoken by the Medicaid and CHIP population

    • s.cnmilf.com
    • healthdata.gov
    • +2more
    Updated Feb 3, 2025
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    Centers for Medicare & Medicaid Services (2025). Primary language spoken by the Medicaid and CHIP population [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/primary-language-spoken-by-the-medicaid-and-chip-population
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    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    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.

  5. Section 1915(c) waiver program participants

    • catalog.data.gov
    • healthdata.gov
    • +2more
    Updated Jul 11, 2025
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    Centers for Medicare & Medicaid Services (2025). Section 1915(c) waiver program participants [Dataset]. https://catalog.data.gov/dataset/section-1915c-waiver-program-participants
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    Dataset updated
    Jul 11, 2025
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    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.

  6. Race and ethnicity of the national Medicaid and CHIP population

    • catalog.data.gov
    • data.virginia.gov
    • +1more
    Updated Feb 3, 2025
    + more versions
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    Centers for Medicare & Medicaid Services (2025). Race and ethnicity of the national Medicaid and CHIP population [Dataset]. https://catalog.data.gov/dataset/race-and-ethnicity-of-the-national-medicaid-and-chip-population
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    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    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.

  7. SHIP Children Receiving Dental Care In The Last Year 2009-2021

    • healthdata.gov
    • opendata.maryland.gov
    • +2more
    application/rdfxml +5
    Updated Apr 8, 2025
    + more versions
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    opendata.maryland.gov (2025). SHIP Children Receiving Dental Care In The Last Year 2009-2021 [Dataset]. https://healthdata.gov/State/SHIP-Children-Receiving-Dental-Care-In-The-Last-Ye/rba8-mkr2
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    xml, application/rssxml, json, application/rdfxml, csv, tsvAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    opendata.maryland.gov
    Description

    This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated on 8/14/2024

    Children Receiving Dental Care In The Last Year - This indicator reflects the percentage of children (aged 0-20 years) enrolled in Medicaid (320+ days) who received at least one dental visit during the past year. Poor oral health can lead to problems with nutrition, growth, school and workplace readiness, and speech. Adoption and use of recommended oral hygiene measures are critical to maintaining overall health. https://health.maryland.gov/pophealth/Documents/SHIP/SHIP%20Lite%20Data%20Details/Children%20receiving%20Dental%20Care%20in%20the%20Last%20Year.pdf" > Link to Data Details

  8. Potentially Avoidable Antibiotic Prescribing Rates for Acute Respiratory...

    • healthdata.gov
    • health.data.ny.gov
    application/rdfxml +5
    Updated Apr 8, 2025
    + more versions
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    health.data.ny.gov (2025). Potentially Avoidable Antibiotic Prescribing Rates for Acute Respiratory Infection by Provider County, Children Age 3 Months-17 Years, NYS Medicaid: Beginning 2010 [Dataset]. https://healthdata.gov/State/Potentially-Avoidable-Antibiotic-Prescribing-Rates/w88u-4vqe
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    xml, application/rdfxml, json, csv, tsv, application/rssxmlAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    health.data.ny.gov
    Area covered
    New York
    Description

    This dataset contains Potentially Avoidable Antibiotic Prescribing observed and risk-adjusted rates for child Medicaid enrollees by provider county beginning in 2010.

    Potentially Avoidable Antibiotic Prescriptions are antibiotic prescriptions filled for the treatment of acute respiratory infections for which antibiotics are not indicated, contributing to bacterial drug resistance. Index visits for acute respiratory infections and corresponding prescription fills were identified through the use of previously published methods.

    The rates were calculated using Medicaid outpatient claims and encounters, and prescription drug data.

    The observed and risk adjusted rates are presented by provider county (including a statewide total).

  9. C

    Childhood Asthma Healthcare Utilization

    • data.wprdc.org
    • data.amerigeoss.org
    csv
    Updated Jun 3, 2024
    + more versions
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    Allegheny County (2024). Childhood Asthma Healthcare Utilization [Dataset]. https://data.wprdc.org/dataset/childhood-asthma-healthcare-utilization
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    csv(10404)Available download formats
    Dataset updated
    Jun 3, 2024
    Dataset provided by
    Allegheny County
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This data shows healthcare utilization for asthma by Allegheny County residents 18 years of age and younger. It counts asthma-related visits to the Emergency Department (ED), hospitalizations, urgent care visits, and asthma controller medication dispensing events.

    The asthma data was compiled as part of the Allegheny County Health Department’s Asthma Task Force, which was established in 2018. The Task Force was formed to identify strategies to decrease asthma inpatient and emergency utilization among children (ages 0-18), with special focus on children receiving services funded by Medicaid. Data is being used to improve the understanding of asthma in Allegheny County, and inform the recommended actions of the task force. Data will also be used to evaluate progress toward the goal of reducing asthma-related hospitalization and ED visits.

    Regarding this data, asthma is defined using the International Classification of Diseases, Tenth Revision (IDC-10) classification system code J45.xxx. The ICD-10 system is used to classify diagnoses, symptoms, and procedures in the U.S. healthcare system.

    Children seeking care for an asthma-related claim in 2017 are represented in the data. Data is compiled by the Health Department from medical claims submitted to three health plans (UPMC, Gateway Health, and Highmark). Claims may also come from people enrolled in Medicaid plans managed by these insurers. The Health Department estimates that 74% of the County’s population aged 0-18 is represented in the data.

    Users should be cautious of using administrative claims data as a measure of disease prevalence and interpreting trends over time. Missing from the data are the uninsured, members in participating plans enrolled for less than 90 continuous days in 2017, children with an asthma-related condition that did not file a claim in 2017, and children participating in plans managed by insurers that did not share data with the Health Department.

    Data users should also be aware that diagnoses may also be subject to misclassification, and that children with an asthmatic condition may not be diagnosed. It is also possible that some children may be counted more than once in the data if they are enrolled in a plan by more than one participating insurer and file a claim on each policy in the same calendar year.

    Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

  10. A

    ‘SHIP Children Receiving Blood Lead Screening 2011-2017’ analyzed by...

    • analyst-2.ai
    Updated Mar 20, 2019
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2019). ‘SHIP Children Receiving Blood Lead Screening 2011-2017’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-ship-children-receiving-blood-lead-screening-2011-2017-7344/latest
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    Dataset updated
    Mar 20, 2019
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘SHIP Children Receiving Blood Lead Screening 2011-2017’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/89d18468-2bab-40ed-8cb6-c76660d950ad on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    Children Receiving Blood Lead Screening - This indicator reflects the percentage of children (aged 12-35 months) enrolled in Medicaid (90+ days) screened for lead in their blood. Each pediatric Medicaid enrollee should be screened for blood lead during their 12 and 24-month well child visit. Common sources of pediatric lead exposure include dust and paint chips from chipping or peeling lead paint, as well as lead contaminated: soil, toys, water, cosmetics, and folk medicines.

    --- Original source retains full ownership of the source dataset ---

  11. W

    SHIP Children Receiving Dental Care In The Last Year 2009-2017

    • cloud.csiss.gmu.edu
    csv, json, rdf, xml
    Updated Mar 10, 2020
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    United States (2020). SHIP Children Receiving Dental Care In The Last Year 2009-2017 [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/ship-children-receiving-dental-care-in-the-last-year-2009-2017
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    json, xml, csv, rdfAvailable download formats
    Dataset updated
    Mar 10, 2020
    Dataset provided by
    United States
    Description

    Children Receiving Dental Care In The Last Year - This indicator reflects the percentage of children (aged 0-20 years) enrolled in Medicaid (320+ days) who received at least one dental visit during the past year. Poor oral health can lead to problems with nutrition, growth, school and workplace readiness, and speech. Adoption and use of recommended oral hygiene measures are critical to maintaining overall health.

  12. Relative rates of imaging (95% confidence intervals) comparing children with...

    • figshare.com
    • plos.figshare.com
    xls
    Updated Sep 6, 2023
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    Emily C. Marlow; Jonathan M. Ducore; Marilyn L. Kwan; Erin J. A. Bowles; Robert T. Greenlee; Jason D. Pole; Alanna K. Rahm; Natasha K. Stout; Sheila Weinmann; Rebecca Smith-Bindman; Diana L. Miglioretti (2023). Relative rates of imaging (95% confidence intervals) comparing children with vs. without Down syndrome for each modality by age, calendar year, sex, and Medicaid status, adjusted for the other variables listed as well as race, ethnicity, and healthcare system. [Dataset]. http://doi.org/10.1371/journal.pone.0289957.t003
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    xlsAvailable download formats
    Dataset updated
    Sep 6, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Emily C. Marlow; Jonathan M. Ducore; Marilyn L. Kwan; Erin J. A. Bowles; Robert T. Greenlee; Jason D. Pole; Alanna K. Rahm; Natasha K. Stout; Sheila Weinmann; Rebecca Smith-Bindman; Diana L. Miglioretti
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Relative rates of imaging (95% confidence intervals) comparing children with vs. without Down syndrome for each modality by age, calendar year, sex, and Medicaid status, adjusted for the other variables listed as well as race, ethnicity, and healthcare system.

  13. Potentially Avoidable Antibiotic Prescribing Rates for Acute Respiratory...

    • healthdata.gov
    application/rdfxml +5
    Updated Apr 8, 2025
    + more versions
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    (2025). Potentially Avoidable Antibiotic Prescribing Rates for Acute Respiratory Infection by Provider County, Children Age 3 Months-17 Years, NYS Medicaid: Beginning 2010 - w88u-4vqe - Archive Repository [Dataset]. https://healthdata.gov/dataset/Potentially-Avoidable-Antibiotic-Prescribing-Rates/7xqa-s2tg
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    csv, json, application/rdfxml, tsv, application/rssxml, xmlAvailable download formats
    Dataset updated
    Apr 8, 2025
    Description

    This dataset tracks the updates made on the dataset "Potentially Avoidable Antibiotic Prescribing Rates for Acute Respiratory Infection by Provider County, Children Age 3 Months-17 Years, NYS Medicaid: Beginning 2010" as a repository for previous versions of the data and metadata.

  14. d

    SHIP Children Receiving Blood Lead Screening 2011-2021

    • catalog.data.gov
    • opendata.maryland.gov
    • +1more
    Updated Aug 16, 2024
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    opendata.maryland.gov (2024). SHIP Children Receiving Blood Lead Screening 2011-2021 [Dataset]. https://catalog.data.gov/dataset/ship-children-receiving-blood-lead-screening-2011-2017
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    Dataset updated
    Aug 16, 2024
    Dataset provided by
    opendata.maryland.gov
    Description

    This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated on 8/14/2024 Children Receiving Blood Lead Screening - This indicator reflects the percentage of children (aged 12-35 months) enrolled in Medicaid (90+ days) screened for lead in their blood. Each pediatric Medicaid enrollee should be screened for blood lead during their 12 and 24-month well child visit. Common sources of pediatric lead exposure include dust and paint chips from chipping or peeling lead paint, as well as lead contaminated: soil, toys, water, cosmetics, and folk medicines. Link to Data Details

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Centers for Medicare & Medicaid Services (2025). Medicaid and CHIP enrollees who received a well-child visit [Dataset]. https://data.virginia.gov/dataset/medicaid-and-chip-enrollees-who-received-a-well-child-visit
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Medicaid and CHIP enrollees who received a well-child visit

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Dataset updated
Jan 18, 2025
Dataset provided by
Centers for Medicare & Medicaid Services
Description

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.

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