AndreaBozzo/ceres-open-data-index huggingface dataset:
2021 Final Assisted Reproductive Technology (ART) Success Rates

Data were updated on September 11, 2024.

ART data are made available as part of the National ART Surveillance System (NASS) that collects success rates, services, profiles and annual summary data from fertility clinics across the U.S. There are four datasets available: ART Services and Profiles, ART Patient and Cycle Characteristics, ART Success Rates, and ART Summary. All four datasets may be linked by “ClinicID.” ClinicID is a unique identifier for each clinic that reported cycles. The Success Rates dataset contains success rates for ART cycles started during the year indicated. Since ART success depends on whether patients are using their own eggs or donor eggs, success rates are included separately for these two groups. Success rates for patients using their own eggs are shown per intended retrieval, per actual retrieval, and per transfer. These success rates are reported as cumulative success rates, which take into account transfers that occur within 1 year after an egg retrieval. Since ART success depends on whether patients are using ART for the first time or had prior ART cycles, users can examine success rates for all “Patients using their own eggs” or for “Patients with no prior ART using their own eggs.” For new patients using ART for the first time, the success rates are also shown after 1, 2, or all intended egg retrievals during the reporting year. In addition, the average number of transfers per intended retrieval and the average number of intended retrievals per live-birth delivery are shown. Success rates for ART cycles that involve the transfer of embryos created from donor eggs or donated embryos are shown and are not cumulative. They are based on donor cycles started in the year indicated that had embryo transfers, regardless of when the donor eggs were retrieved. Success rates in this section are not presented by patient age group because previous data show that an intended parent’s age does not substantially affect success when using donor eggs or donated embryos. The success rates are presented by types of embryos and eggs used in the transfer. This dataset excludes cycles that were considered research—that is, cycles performed to evaluate new procedures.

Tags: art, assisted-reproductive-technology, clinic, fertility, infertility, services, success-rates
Organization: U.S. Department of Health & Human Services
2021 Final Assisted Reproductive Technology (ART) Patient and Cycle Characteristics

ART data are made available as part of the National ART Surveillance System (NASS) that collects success rates, services, profiles and annual summary data from fertility clinics across the U.S. There are four datasets available: ART Services and Profiles, ART Patient and Cycle Characteristics, ART Success Rates, and ART Summary. All four datasets may be linked by “ClinicID.” ClinicID is a unique identifier for each clinic that reported cycles. The Patient and Cycle Characteristics dataset summarizes the types of ART services performed and the kinds of patients who received ART procedures in a specific clinic. Please note patient characteristics are presented per cycle rather than per patient. As a result, patients who had more than one ART cycle within the reporting year are represented more than once.

Tags: art, assisted-reproductive-technology, clinic, fertility, infertility, services, success-rates
Organization: U.S. Department of Health & Human Services
2021 Child and Adult Health Care Quality Measures Quality

Performance rates on frequently reported health care quality measures in the CMS Medicaid/CHIP Child and Adult Core Sets, for FFY 2021 reporting.

Source: Mathematica analysis of MACPro and Form CMS-416 reports for the FFY 2021 reporting cycle. Dataset revised September 2023. For more information, see the Children's Health Care Quality Measures and Adult Health Care Quality Measures webpages.

Tags: core-sets, performance-rates, quality-measures
Organization: U.S. Department of Health & Human Services
Program Information for Medicaid and CHIP Beneficiaries by Year

This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by program type (Medicaid or CHIP). There are three metrics presented: (1) the number of beneficiaries ever enrolled in each program type over the year (duplicated count); (2) the number of beneficiaries enrolled in each program type as of an individual’s last month of enrollment (unduplicated count); and (3) average monthly enrollment in each program type. 

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 topics Medicaid-only enrollment and M-CHIP and S-CHIP Enrollment. 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.

Tags: chip, dq-atlas, medicaid, program-enrollment, t-msis-analytic-files
Organization: U.S. Department of Health & Human Services
NOHSS Adult Indicators

2012-2020 (even years). Data from BRFSS for indicators of adult oral health for even years from 2012 through 2020. National estimates are represented by the median prevalence among 50 states and the District of Columbia data. Estimates are prepared from the BRFSS public use data sets. Estimates in this file are not age adjusted, and may differ slightly from estimates available from the BRFSS web site or Chronic Disease Indicators due to small differences in definition, age adjustment or rounding.  For more information, see: https://www.cdc.gov/oralhealthdata/overview/Adult-Indicators.html.

Tags: access-to-care, adult, adults, brfss, dental-care, dental-cleaning, dental-visits, dentist, division-of-oral-health, nohss, oral-health, prevalence, surveillance, tooth-loss
Organization: U.S. Department of Health & Human Services
Dual Status Information for Medicaid and CHIP Beneficiaries by Year

This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by dual eligibility status for Medicaid and Medicare (full dual eligibility, partial dual eligibility, or not dually eligible). There are three metrics presented: (1) the number of beneficiaries ever dually eligible for Medicaid and Medicare over the year (duplicated count); (2) the number of beneficiaries dually eligible for Medicaid and Medicare as of an individual’s last month of enrollment (unduplicated count); and (3) average monthly eligibility for Medicaid and Medicare. 

These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating these measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable or of high concern based on DQ Atlas thresholds for the topic Dually Enrolled in Medicare. 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.

Tags: chip, dq-atlas, dual-enrollment, medicaid, t-msis-analytic-files
Organization: U.S. Department of Health & Human Services
PLACES: Local Data for Better Health, County Data 2023 release

This dataset contains model-based county estimates. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. This dataset includes estimates for 36 measures: 13 for health outcomes, 9 for preventive services use, 4 for chronic disease-related health risk behaviors, 7 for disabilities, and 3 for health status. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2021 or 2020 data, Census Bureau 2021 or 2020 county population estimate data, and American Community Survey 2017–2021, or 2016–2020 estimates. The 2023 release uses 2021 BRFSS data for 29 measures and 2020 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours) that the survey collects data on every other year. More information about the methodology can be found at  www.cdc.gov/places.

Tags: behaviors, brfss, county, disability, health, outcomes, places, prevalence, prevention, risk, status
Organization: U.S. Department of Health & Human Services
Behavioral Health Services Provided to the Medicaid and CHIP Population

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

Tags: behavioral-health, chip, dq-atlas, medicaid, mental-health-disorder, service-use, substance-use-disorder, t-msis-analytic-files
Organization: U.S. Department of Health & Human Services
Interagency Data Team Presentation March 7, 2018

<font size='3'>Presentation slides from the Interagency Data Team meeting. The Interagency Data Team is a community of data analysts, or agency liaisons, who convene regularly with representation from DC agencies of all persuasions. Participants engage in discussions regarding the team’s core mission and priorities for a better kind of data culture – collection, application, sharing, classification and governance to name a few. The team is coordinated by the Office of the Chief Technology Officer (OCTO), lead by the Chief Data Officer (CDO), and directly supports the District of Columbia's Data Policy.</font>

Tags: idt, idtpresentation
Organization: District of Columbia
Interagency Data Team Notes March 9, 2021

Meeting notes from Interagency Data Team meetings. These are best attempt to capture notable comments and questions from attendees. Notes are paraphrased. Please reference presentation or contact <a href='mailto:open.data@dc.gov' target='_blank' rel='nofollow ugc noopener noreferrer'>open.data@dc.gov</a> with questions. The Interagency Data Team is a community of data analysts, or agency liaisons, who convene regularly with representation from DC agencies of all persuasions. Participants engage in discussions regarding the team’s core mission and priorities for a better kind of data culture – collection, application, sharing, classification and governance to name a few. The team is coordinated by the Office of the Chief Technology Officer (OCTO), lead by the Chief Data Officer (CDO), and directly supports the District of Columbia's Data Policy.

Tags: idt, idtnotes
Organization: District of Columbia
Interagency Data Team Notes January 23, 2019

Meeting notes from Interagency Data Team meetings. These are best attempt to capture notable comments and questions from attendees. Notes are paraphrased. Please reference presentation or contact <a href='mailto:open.data@dc.gov' target='_blank' rel='nofollow ugc noopener noreferrer'>open.data@dc.gov</a> with questions. The Interagency Data Team is a community of data analysts, or agency liaisons, who convene regularly with representation from DC agencies of all persuasions. Participants engage in discussions regarding the team’s core mission and priorities for a better kind of data culture – collection, application, sharing, classification and governance to name a few. The team is coordinated by the Office of the Chief Technology Officer (OCTO), lead by the Chief Data Officer (CDO), and directly supports the District of Columbia's Data Policy.

Tags: idt, idtnotes
Organization: District of Columbia
Open Data Handbook Curation Diagram

Open Data Handbook Curation Detailed Diagram. DC’s data submission process involves four steps as depicted in this diagram. Overall, the data analysts guide the data owner and other analysts as needed to run the data through the submission process, with different groups leading each part (see all caps in diagram above).  Their application occurs in a unified database infrastructure consisting of a data warehouse and geospatial database.  While there are specific processes and guidelines for each database, they share an overall setting where consistency and standardization are promoted and supported for their individual data curation processes.

Tags: handbook, opendata-dc-gov
Organization: District of Columbia
HIV and AIDS Clinic

<div style='text-align:Left;'><div><div><p><span>HIV/AIDS Clinic locations. The dataset contains locations and attributes of HIV/AIDS clinics, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. A database provided by the DC Department of Health identified clinic locations.</span></p></div></div></div>

Tags: aids, clinic, d-c, dc, dc-gis, dcgis, district-of-columbia, health, hiv, hospital, open-data, washington, washington-dc
Organization: District of Columbia
500 Cities: Census Tract-level Data (GIS Friendly Format), 2016 release

2014, 2013. Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. 500 cities project census tract-level data in GIS-friendly format can be joined with census tract spatial data (https://chronicdata.cdc.gov/500-Cities/500-Cities-Census-Tract-Boundaries/x7zy-2xmx) in a geographic information system (GIS) to produce maps of 27 measures at the census tract level.

Tags: 500-cities, census-tracts, estimates, prevalence
Organization: U.S. Department of Health & Human Services
Intermediate Care Facilities

<DIV STYLE="text-align:Left;"><DIV><P><SPAN>Intermediate Care Facility. This dataset contains points representing Intermediate Care Facility locations, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Intermediate Care Facility locations were identified from Department of Health records, then geocoded to the MAR.</SPAN></P></DIV></DIV>

Tags: care-facility, district-of-columbia, health, hospital, intermediate-care, washington-dc
Organization: District of Columbia
Mosquito Trap Sites

<div style='text-align:Left;'><div><div><p><span>These data represent mosquito trap site results in the District of Columbia from 2016 to 2018. Trap locations are considered approximate address and/or the “nearest” street address or block to the stated coordinates in the data. Visit </span><a href='https://dcgis.maps.arcgis.com/apps/MapJournal/index.html?appid=30c7550c37f04be3803c36928e6cac7c' rel='nofollow ugc'><span>Fight the Bite: Protecting the District of Columbia from Mosquitoes</span></a><span>- a collection of the 2016-2018 Arbovirus Surveillance Program conducted annually by DC Health, Health Regulation &amp; Licensing Admin., Animal Services Div.</span></p><p><span>Mosquitoes have the potential to spread harmful diseases. During the annual mosquito season in Washington DC, usually from April – October, </span><a href='https://dchealth.dc.gov/' rel='nofollow ugc'><span>DC Health</span></a> <span>deploys surveillance and mitigation methods to control the mosquito population in the District. DC Health (also known as the D.C. Department of Health or formerly DOH) has been trapping and testing mosquitoes for West Nile virus (WNV) for well over a decade. Starting in 2016, and in response to the Zika outbreak in Latin America and the Caribbean, DC Health substantially increased mosquito monitoring activities across the city. There were a total of 28 sites and 36 traps across the 8 wards. Data was submitted to the Centers for Disease Control MoquitoNet Portal.</span></p><p><span>Note: the 2017 analysis does not include data for October. This is because October of 2017 would have skewed the results far too much based on a few variables that occurred. For example, the number of traps which had failed by the end of the season.</span></p><p><span>Mosquito species in Washington, D.C.:</span></p><p><span>Culex Pipiens, Salinarius and Culex Restuan: spread West Nile Virus</span></p><p><span>Aedes aegypti : according to the Centers for Disease Control (CDC), health experts have determined this species to be the most competent vector, capable of transmitting Zika to the human population. To date, none of the Aedes aegypti trapped in Washington, D.C. have been found to carry the Zika virus.</span></p><p><span>Aedes albopictus: capable of spreading Zika to people. However, health experts are still learning whether it is likely to do so as it appears at this time, it is not as competent a vector for transmitting Zika as is the Aedes aegypti. Just because a mosquito can carry the virus does not mean that it will cause disease. So far, none of the Aedes albopictus trapped in Washington, D.C. have been found to carry the Zika virus.</span></p><p><span>Aedes japonicus: normally found in South Florida, is present in D.C. in small numbers. Presently there is no indication that they are competent vectors for spreading Zika to the human population.</span></p></div></div></div>

Tags: animal-regulation, arbovirus, cdc, disease, doh, health, mosquito, trap, washington-dc, west-nile-virus, zika
Organization: District of Columbia
Opioid Dependence Treatment Facilities

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The dataset contains locations and attributes of Opioid Dependency Treatment Centers and Needle Exchange Programs.</SPAN></P></DIV></DIV></DIV>

Tags: clinic, district-of-columbia, doh, health, open-data, opioid, washington-dc
Organization: District of Columbia
Baist Index (1959)

The Baist Index provides a mapping index that mirrors the hardcopy index in the original Baist Map Volumes. The Index was hand digitized from the original Baist map volumes. Spatial data was attributed to enable selection of Map Volume as well as individual map sheets. This dataset was originally created in shapefile format, later imported into ArcGis (Version 8.3)

Tags: baist, district-of-columbia, historic, open-data, property, society, washington-dc
Organization: District of Columbia
DCGIS Data Archive August 2006

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The District of Columbia’s Data program is pleased to offer the enterprise GIS geodatabase archive. This product offers a historic snapshot of the DC GIS data. The data consists of the GIS mapping layers and are exported as shapefiles. The date format in the named is "Archive_YYYYMMDD."</SPAN></P></DIV></DIV></DIV>

Tags: archive, data-archive, district-of-columbia, gisdvdarchive, historic, washington-dc
Organization: District of Columbia
DCGIS Data Archive April 2015

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The District of Columbia’s Data program is pleased to offer the enterprise GIS geodatabase archive. This product offers a historic snapshot of the DC GIS data. The data consists of the GIS mapping layers and are exported as shapefiles. The date format in the named is "Archive_YYYYMMDD."</SPAN></P></DIV></DIV></DIV>

Tags: archive, data-archive, district-of-columbia, gisdvdarchive, historic, washington-dc
Organization: District of Columbia
DCGIS Data Archive August 2007

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The District of Columbia’s Data program is pleased to offer the enterprise GIS geodatabase archive. This product offers a historic snapshot of the DC GIS data. The data consists of the GIS mapping layers and are exported as shapefiles. The date format in the named is "Archive_YYYYMMDD."</SPAN></P></DIV></DIV></DIV>

Tags: archive, data-archive, district-of-columbia, gisdvdarchive, historic, washington-dc
Organization: District of Columbia
DCGIS Data Archive December 2019

<div style='font-family: &quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size: 16px;'><div style='margin-bottom: 3rem;'><div><div style='overflow: auto; overflow-wrap: break-word; max-width: 100%; display: inherit;'><div style='font-family: inherit;'><div style='font-family: inherit;'><div style='font-family: inherit;'><p style='margin-top: 0px; margin-bottom: 1.5rem;'><span style='font-family: inherit;'>The District of Columbia’s Data program is pleased to offer the enterprise GIS geodatabase archive. This product offers a historic snapshot of the DC GIS data. The data consists of the GIS mapping layers and are exported as shapefiles. The date format in the named is &quot;Archive_YYYYMMDD.</span></p></div></div></div></div></div></div></div><div style='font-family: &quot;Avenir Next W01&quot;, &quot;Avenir Next W00&quot;, &quot;Avenir Next&quot;, Avenir, &quot;Helvetica Neue&quot;, sans-serif; font-size: 16px;'><div style='margin-bottom: 3rem;'></div></div>

Tags: archive, data-archive, district-of-columbia, gisdvdarchive, historic, washington-dc
Organization: District of Columbia
Development Enterprise Zones

<div style='text-align:Left;'><div><div><p><span>The Development Enterprise Zones are used for the purposes of the Certified Business Enterprise program, for active businesses and businesses seeking certification from the Department of Small and Local Business Development (DSLBD).</span></p></div></div></div>

Tags: business, dc, district-of-columbia, dslbd, economic, enterprise-zone, incentive, washington-dc
Organization: District of Columbia
DCGIS Data Archive February 2007

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The District of Columbia’s Data program is pleased to offer the enterprise GIS geodatabase archive. This product offers a historic snapshot of the DC GIS data. The data consists of the GIS mapping layers and are exported as shapefiles. The date format in the named is "Archive_YYYYMMDD."</SPAN></P></DIV></DIV></DIV>

Tags: archive, data-archive, district-of-columbia, gisdvdarchive, historic, washington-dc
Organization: District of Columbia