HHS responsibly shares “open by default” data with the public to democratize access to information, demystify the Department, and increase transparency through data sharing. HHS Open Data is non-sensitive data, meaning thousands of health and human services datasets are publicly available to fuel new business models, enable emerging technologies like AI, accelerate scientific discoveries, and inspire American innovation. This top-1000 HHS Open Data websites and resources page, dynamically generated from the Digital Analytics Program (DAP) provided by the U.S. General Services Administration (GSA), is driven by near-real-time user demand. GSA’s DAP helps federal agencies and the public see how visitors find, access, and use government websites, data, and services online. The below list filters DAP for only resources from HHS and includes all HHS Divisions. You may filter by individual HHS Divisions and columns.

The Health Insurance Marketplace Public Use Files contain data on health and dental plans offered to individuals and small businesses through the US Health Insurance Marketplace.

Exploration Ideas

To help get you started, here are some data exploration ideas:

• How do plan rates and benefits vary across states?
• How do plan benefits relate to plan rates?
• How do plan rates vary by age?
• How do plans vary across insurance network providers?

See this forum thread for more ideas, and post there if you want to add your own ideas or answer some of the open questions!

Data Description

This data was originally prepared and released by the Centers for Medicare & Medicaid Services (CMS). Please read the CMS Disclaimer-User Agreement before using this data.

Here, we've processed the data to facilitate analytics. This processed version has three components:

1. Original versions of the data

The original versions of the 2014, 2015, 2016 data are available in the "raw" directory of the download and "../input/raw" on Kaggle Scripts. Search for "dictionaries" on this page to find the data dictionaries describing the individual raw files.

2. Combined CSV files that contain

In the top level directory of the download ("../input" on Kaggle Scripts), there are six CSV files that contain the combined at across all years:

• BenefitsCostSharing.csv
• BusinessRules.csv
• Network.csv
• PlanAttributes.csv
• Rate.csv
• ServiceArea.csv

Additionally, there are two CSV files that facilitate joining data across years:

• Crosswalk2015.csv - joining 2014 and 2015 data
• Crosswalk2016.csv - joining 2015 and 2016 data

3. SQLite database

The "database.sqlite" file contains tables corresponding to each of the processed CSV files.

The code to create the processed version of this data is available on GitHub.

Analytics HealthData.gov is the home of HHS Open Data, providing researchers, policymakers, and the public with access to valuable information that drives innovation, transparency, and informed decision making. This dashboard provides at-a-glance insights into: How users are engaging with HHS data What categories of data and data resources are available How data engagement has evolved over time.

Analysis of ‘HHS IDs’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/4c2a81b2-1556-4d56-a7ce-27f1e6d4bd26 on 11 February 2022.

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

This file helps define the HHS_ID column that is published in both the

'COVID-19 Reported Patient Impact and Hospital Capacity by Facility' found here: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/anag-cw7u

COVID-19 Reported Patient Impact and 'Hospital Capacity by Facility -- RAW' found here: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/uqq2-txqb

As a part of an effort to improve the granularity of spatial data, unique identifiers (named “HHS IDs” in the datasets) have been assigned to each individual facility. These unique identifiers are provided so data users can reference each individual “brick and mortar” facility that is reporting data to HHS, even in cases when multiple facilities report under the same CMS Certification Number (CCN). Additional datasets and further details related to HHS IDs will be released at a later date.

With this file, you can associate the reporting facility with its physical location(s).

On October 8, 2021, this file will now include the HHS IDs for Psychiatric, Rehabilitation and Behavioral hospitals, as well as Ambulatory Surgical Centers and Free Standing Emergency departments wherever these institutions are reporting under https://www.hhs.gov/sites/default/files/covid-19-faqs-hospitals-hospital-laboratory-acute-care-facility-data-reporting.pdf

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

Analysis of ‘HHS Data Governance Board Membership’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/29b05748-bcc1-44ab-a6de-b9ff200ac96a on 26 January 2022.

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

The purpose of the U.S. Department of Health & Human Services (HHS) Data Governance Board (DGB) is to serve as the Department’s principal data governance forum and decision-making body for managing HHS’ data as a strategic asset and to support HHS in meeting its mission and agency priorities, including implementation of the Evidence Act.

The HHS DGB currently meets monthly to support these activities.

This dataset serves to communicate to the public the members of the HHS DGB, as required by the Federal Data Strategy.

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

Analysis of ‘HHS Unaccompanied Children Program’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/aafeae2a-82df-4019-a67d-2f083b7b17c3 on 11 February 2022.

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

This data represents unaccompanied children who are taken into custody by Customs and Border Protection brought to a facility and processed for transfer to the Department of Health and Human Services (HHS) as required by law. HHS holds the child for testing and quarantine, and shelters the child until the child is placed with a sponsor here in the United States.

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

Summary of pcHPSA counties, by HHS Region, 2017.

The Adoption and Foster Care Analysis and Reporting System (AFCARS) is a federally mandated data collection system intended to provide case specific information on all children covered by the protections of Title IV-B/E of the Social Security Act (Section 427). Under the Final 1993 AFCARS’ rule, states are required to collect and submit data on all children who are under the responsiblity of the title IV-B/IV-E agency for placement, care, or supervision. Units of Response: Children in Foster Care Type of Data: Administrative Tribal Data: Unavailable Periodicity: Semiannual Demographic Indicators: Disability;Geographic Areas;Sex SORN: https://www.federalregister.gov/documents/2016/12/14/2016-29366/adoption-and-foster-care-analysis-and-reporting-system Data Use Agreement: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf Data Use Agreement Location: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf Granularity: Individual Spatial: United States Geocoding: FIPS Code

Analysis of ‘HHS Nursing Homes’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/1c1af968-40f4-489e-9878-0fc7014881b2 on 26 January 2022.

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

Nursing Homes Located in Montgomery County

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

A list of Suppliers that indicates the supplies carried at that location and the supplier's Medicare participation status

Works of the U.S. government are in the public domain, and permission is not required to use them. An attribution to the Centers for Medicare & Medicaid Services (CMS) as the source is appreciated. However, publicly reported data, including star ratings, should not be construed as an endorsement by the U.S. Department of Health and Human Services (HHS) of any health care provider’s products or services. Conveying a false impression of government approval, endorsement or authorization of products or services is forbidden. See 42 U.S.C. 1320b-10.

The star ratings and all data on this site are provided as a service to the public and are not intended to grant rights or impose obligations. Star ratings are limited in scope to the data sources from which they are derived. A provider’s star rating on an individual measure or domain may not be reflective of that provider’s overall star rating..

Analysis of ‘COVID-19 Reported Patient Impact and Hospital Capacity by State’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/66a46309-d465-47bc-9997-210532ebbf63 on 11 February 2022.

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

The following dataset provides state-aggregated data for hospital utilization. These are derived from reports with facility-level granularity across two main sources: (1) HHS TeleTracking, and (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities.

The file will be updated daily and provides the latest values reported by each facility within the last four days. This allows for a more comprehensive picture of the hospital utilization within a state by ensuring a hospital is represented, even if they miss a single day of reporting.

No statistical analysis is applied to account for non-response and/or to account for missing data.

The below table displays one value for each field (i.e., column). Sometimes, reports for a given facility will be provided to both HHS TeleTracking and HHS Protect. When this occurs, to ensure that there are not duplicate reports, deduplication is applied: specifically, HHS selects the TeleTracking record provided directly by the facility over the state-provided data to HHS Protect.

On April 29, 2021, this data set has had the following fields added: previous_day_admission_adult_covid_confirmed_18-19 previous_day_admission_adult_covid_confirmed_18-19_coverage previous_day_admission_adult_covid_confirmed_20-29_coverage previous_day_admission_adult_covid_confirmed_30-39 previous_day_admission_adult_covid_confirmed_30-39_coverage previous_day_admission_adult_covid_confirmed_40-49 previous_day_admission_adult_covid_confirmed_40-49_coverage previous_day_admission_adult_covid_confirmed_40-49_coverage previous_day_admission_adult_covid_confirmed_50-59 previous_day_admission_adult_covid_confirmed_50-59_coverage previous_day_admission_adult_covid_confirmed_60-69 previous_day_admission_adult_covid_confirmed_60-69_coverage previous_day_admission_adult_covid_confirmed_70-79 previous_day_admission_adult_covid_confirmed_70-79_coverage previous_day_admission_adult_covid_confirmed_80+ previous_day_admission_adult_covid_confirmed_80+_coverage previous_day_admission_adult_covid_confirmed_unknown previous_day_admission_adult_covid_confirmed_unknown_coverage previous_day_admission_adult_covid_suspected_18-19 previous_day_admission_adult_covid_suspected_18-19_coverage previous_day_admission_adult_covid_suspected_20-29 previous_day_admission_adult_covid_suspected_20-29_coverage previous_day_admission_adult_covid_suspected_30-39 previous_day_admission_adult_covid_suspected_30-39_coverage previous_day_admission_adult_covid_suspected_40-49 previous_day_admission_adult_covid_suspected_40-49_coverage previous_day_admission_adult_covid_suspected_50-59 previous_day_admission_adult_covid_suspected_50-59_coverage previous_day_admission_adult_covid_suspected_60-69 previous_day_admission_adult_covid_suspected_60-69_coverage previous_day_admission_adult_covid_suspected_70-79 previous_day_admission_adult_covid_suspected_70-79_coverage previous_day_admission_adult_covid_suspected_80+ previous_day_admission_adult_covid_suspected_80+_coverage previous_day_admission_adult_covid_suspected_unknown previous_day_admission_adult_covid_suspected_unknown_coverage

On June 30, 2021, this data set has had the following fields added: deaths_covid deaths_covid_coverage

On September 13, 2021, this data set has had the following fields added: on_hand_supply_therapeutic_a_casirivimab_imdevimab_courses, on_hand_supply_therapeutic_b_bamlanivimab_courses, on_hand_supply_therapeutic_c_bamlanivimab_etesevimab_courses, previous_week_therapeutic_a_casirivimab_imdevimab_courses_used, previous_week_therapeutic_b_bamlanivimab_courses_used, previous_week_therapeutic_c_bamlanivimab_etesevimab_courses_used

On September 17, 2021, this data set has had the following fields added: icu_patients_confirmed_influenza, icu_patients_confirmed_influenza_coverage, previous_day_admission_influenza_confirmed, previous_day_admission_infl

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

Overview

New York, NY – June 06, 2025 – Global Healthcare Predictive Analytics Market size is expected to be worth around US$ 160.3 billion by 2034 from US$ 18.5 billion in 2024, growing at a CAGR of 24.1% during the forecast period 2025 to 2034.

The global healthcare predictive analytics market is experiencing significant momentum, driven by the increasing demand for data-backed clinical and operational insights. Predictive analytics in healthcare leverages artificial intelligence (AI), machine learning (ML), and statistical algorithms to identify patterns and forecast patient outcomes, resource utilization, and disease progression. This technology enables hospitals, insurers, and public health agencies to proactively manage care delivery, reduce costs, and improve patient outcomes.

The rising prevalence of chronic diseases, such as diabetes, cardiovascular conditions, and cancer, has intensified the need for early risk detection and preventive strategies. Predictive analytics tools are being integrated into electronic health records (EHRs) to support clinical decision-making, optimize staffing, and prevent adverse events. Additionally, the COVID-19 pandemic accelerated adoption by highlighting the value of predictive models in outbreak forecasting and resource allocation.

Government initiatives to digitize healthcare infrastructure and promote value-based care further support market expansion. According to the U.S. Department of Health and Human Services (HHS), over 90% of hospitals have adopted certified EHR systems, facilitating data availability for advanced analytics.

As healthcare organizations increasingly prioritize outcome-based care, the market for predictive analytics is expected to witness robust growth over the coming years. The integration of real-time data processing and AI capabilities will continue to enhance precision in healthcare forecasting and intervention.

Analysis of ‘COVID-19 Reported Patient Impact and Hospital Capacity by Facility’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e6ff9332-7a6d-42a7-986b-3deb14475c11 on 13 February 2022.

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

The "COVID-19 Reported Patient Impact and Hospital Capacity by Facility" dataset from the U.S. Department of Health & Human Services, filtered for Connecticut. View the full dataset and detailed metadata here: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/anag-cw7u

The following dataset provides facility-level data for hospital utilization aggregated on a weekly basis (Friday to Thursday). These are derived from reports with facility-level granularity across two main sources: (1) HHS TeleTracking, and (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities.

The hospital population includes all hospitals registered with Centers for Medicare & Medicaid Services (CMS) as of June 1, 2020. It includes non-CMS hospitals that have reported since July 15, 2020. It does not include psychiatric, rehabilitation, Indian Health Service (IHS) facilities, U.S. Department of Veterans Affairs (VA) facilities, Defense Health Agency (DHA) facilities, and religious non-medical facilities.

For a given entry, the term “collection_week” signifies the start of the period that is aggregated. For example, a “collection_week” of 2020-11-20 means the average/sum/coverage of the elements captured from that given facility starting and including Friday, November 20, 2020, and ending and including reports for Thursday, November 26, 2020.

Reported elements include an append of either “_coverage”, “_sum”, or “_avg”.

A “_coverage” append denotes how many times the facility reported that element during that collection week.

A “_sum” append denotes the sum of the reports provided for that facility for that element during that collection week.

A “_avg” append is the average of the reports provided for that facility for that element during that collection week.

The file will be updated weekly. No statistical analysis is applied to impute non-response. For averages, calculations are based on the number of values collected for a given hospital in that collection week. Suppression is applied to the file for sums and averages less than four (4). In these cases, the field will be replaced with “-999,999”.

This data is preliminary and subject to change as more data become available. Data is available starting on July 31, 2020.

Sometimes, reports for a given facility will be provided to both HHS TeleTracking and HHS Protect. When this occurs, to ensure that there are not duplicate reports, deduplication is applied according to prioritization rules within HHS Protect.

For influenza fields listed in the file, the current HHS guidance marks these fields as optional. As a result, coverage of these elements are varied.

On May 3, 2021, the following fields have been added to this data set. hhs_ids previous_day_admission_adult_covid_confirmed_7_day_coverage previous_day_admission_pediatric_covid_confirmed_7_day_coverage previous_day_admission_adult_covid_suspected_7_day_coverage previous_day_admission_pediatric_covid_suspected_7_day_coverage previous_week_personnel_covid_vaccinated_doses_administered_7_day_sum total_personnel_covid_vaccinated_doses_none_7_day_sum total_personnel_covid_vaccinated_doses_one_7_day_sum total_personnel_covid_vaccinated_doses_all_7_day_sum previous_week_patients_covid_vaccinated_doses_one_7_day_sum previous_week_patients_covid_vaccinated_doses_all_7_day_sum

On May 8, 2021, this data set has been converted to a corrected data set. The corrections applied to this data set are to smooth out data anomalies caused by keyed in data errors. To help determine which records have had corrections made to it. An additional Boolean field called is_corrected has been added. To see the numbers as reported by the facilities, go to: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/uqq2-txqb

On May 13, 2021 Changed vaccination fields from sum to max or min fields. This reflects the maximum or minimum number report

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

Analysis of ‘Monthly provisional counts of deaths by age group and HHS region for select causes of death’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/d061abcf-387a-4240-85d3-9e12b172e966 on 27 January 2022.

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

Provisional counts of deaths by the month the deaths occurred, by age group and HHS region, for select underlying causes of death for 2019-2020. The dataset also includes monthly provisional counts of death for COVID-19, coded to ICD-10 code U07.1 as an underlying or multiple cause of death.

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

No description provided

The CMS Office of Enterprise Data and Analytics has developed CMS Program Statistics, which includes detailed summary statistics on national health care, Medicare populations, utilization, and expenditures, as well as counts for Medicare-certified institutional and non-institutional providers. CMS Program Statistics is organized into sections which can be downloaded and viewed separately. Tables and maps will be posted as they become finalized. CMS Program Statistics is replacing the Medicare and Medicaid Statistical Supplement, which was published annually in electronic form from 2001-2013.

This dataset represents preliminary weekly hospital respiratory data and metrics aggregated to national and state/territory levels reported to CDC’s National Health Safety Network (NHSN) beginning August 2020. This dataset updates weekly on Wednesdays with preliminary data reported to NHSN for the previous reporting week (Sunday – Saturday).

Data for reporting dates through April 30, 2024 represent data reported during a previous mandated reporting period as specified by the HHS Secretary. Data for reporting dates May 1, 2024 – October 31, 2024 represent voluntarily reported data in the absence of a mandate. Data for reporting dates beginning November 1, 2024 represent data reported during a current mandated reporting period. All data and metrics capturing information on respiratory syncytial virus (RSV) were voluntarily reported until November 1, 2024. All data included in this dataset represent aggregated counts, and include metrics capturing information specific to hospital capacity, occupancy, hospitalizations, and new hospital admissions with corresponding metrics indicating reporting coverage for a given reporting week. NHSN monitors national and local trends in healthcare system stress and capacity for all acute care and critical access hospitals in the United States.

For more information on the reporting mandate per the Centers for Medicare and Medicaid Services (CMS) requirements, visit: Updates to the Condition of Participation (CoP) Requirements for Hospitals and Critical Access Hospitals (CAHs) To Report Acute Respiratory Illnesses.

For more information regarding NHSN’s collection of these data, including full reporting guidance, visit: NHSN Hospital Respiratory Data.

For data that is considered final for a given reporting week (Sunday – Saturday), and reflects that which is used in NHSN HRD dashboards for publication each Friday, visit: https://data.cdc.gov/Public-Health-Surveillance/Weekly-Hospital-Respiratory-Data-HRD-Metrics-by-Ju/ua7e-t2fy/about_data.

CDC coordinates weekly forecasts of hospitalization admissions based on this data set. More information about flu forecasting can be found at About Flu Forecasting | FluSight | CDC, and information about COVID-19 forecasting and other modeling analyses for the Respiratory Virus Season are available at CFA's Insights for Respiratory Virus Season | CFA | CDC.

Source: CDC National Healthcare Safety Network (NHSN).

• Data source description (updated November 15, 2024): As of October 9, 2024, Hospital Respiratory Data (HRD; formerly Respiratory Pathogen, Hospital Capacity, and Supply data or 'COVID-19 hospital data') are reported to HHS through CDC's National Healthcare Safety Network (NHSN) based on updated requirements from the Centers for Medicare and Medicaid Services (CMS). These data were voluntarily reported to NHSN May 1, 2024 until November 1, 2024, at which time CMS began requiring acute care and critical access hospitals to electronically report information via NHSN about COVID-19, influenza, and RSV, hospital bed census and capacity. Hospital bed capacity and occupancy data for all patients and for patients with COVID-19 or influenza for collection dates prior to May 1, 2024, represent data reported during a previously mandated reporting

Rate of deaths by age/gender (per 100,000 population) for motor vehicle occupants killed in crashes, 2012 & 2014. 2012 Source: Fatality Analysis Reporting System (FARS). 2014 Source: National Highway Traffic Safety Administration's (NHTSA) Fatality Analysis Reporting System (FARS), 2014 Annual Report File Note: Blank cells indicate data are suppressed. Fatality rates based on fewer than 20 deaths are suppressed.

The Office of the Actuary in the Centers for Medicare and Medicaid Services (CMS) from time to time conducts studies on various aspects of the Medicare and Medicaid programs. The available studies include the following- Medicare Financial Status, Budget Impact, and Sustainability-Which Concept is Which, Actuarial Report on the Financial Outlook for Medicaid, Estimated Impact of Health Care Reform Proposals, Analysis of volume-and-intensity response to a price change for physicians services, Analysis of expenses in the last year of life.