Cares data

The International Cardiac Arrest REsearch consortium (I-CARE) database includes baseline clinical information and continuous electroencephalography (EEG) recordings from 1,020 comatose patients with a diagnosis of cardiac arrest who were admitted to an intensive care unit from seven academic hospitals in the U.S. and Europe. Patients were monitored with 18 bipolar EEG channels over hours to days for the diagnosis of seizures and for neurological prognostication. Long-term neurological function was determined using the Cerebral Performance Category scale. Methods Full details available in this repository: Amorim, E., Zheng, W., Ghassemi, M., Aghaeeaval, M., Kandhare, P., Karukonda, V., Lee, J. W., Herman, S., sivaraju, a., Gaspard, N., Hofmeijer, J., van Putten, M. J., Sameni, R., Reyna, M., Clifford, G., & Westover, M. B. (2023). I-CARE: International Cardiac Arrest REsearch consortium Electroencephalography Database (version 1.0). Brain Data Science Platform. https://doi.org/10.60508/xwye-v214.

The Medical Care Cost Recovery National Database (MCCR NDB) provides a repository of summary Medical Care Collections Fund (MCCF) billing and collection information used by program management to compare facility performance. It stores summary information for Veterans Health Administration (VHA) receivables including the number of receivables and their summarized status information. This database is used to monitor the status of the VHA's collection process and to provide visibility on the types of bills and collections being done by the Department. The objective of the VA MCCF Program is to collect reimbursement from third party health insurers and co-payments from certain non-service-connected (NSC) Veterans for the cost of medical care furnished to Veterans. Legislation has authorized VHA to: submit claims to and recover payments from Veterans' third party health insurance carriers for treatment of non-service-connected conditions; recover co-payments from certain Veterans for treatment of non-service-connected conditions; and recover co-payments for medications from certain Veterans for treatment of non-service-connected conditions. All of the information captured in the MCCR NDB is derived from the Accounts Receivable (AR) modules running at each medical center. MCCR NDB is not used for official collections figures; instead, the Department uses the Financial Management System (FMS).

ONC uses the SK&A Office-based Provider Database to calculate the counts of medical doctors, doctors of osteopathy, nurse practitioners, and physician assistants at the state and count level from 2011 through 2013. These counts are grouped as a total, as well as segmented by each provider type and separately as counts of primary care providers.

Homeland Infrastructure Foundation-Level Data (HIFLD) geospatial data sets containing information on Urgent Care Facilities.

A list of all Home Health Agencies that have been registered with Medicare. The list includes addresses, phone numbers, and quality measure ratings for each agency.

Note: To align with other long term care programs, as of January 15, 2022, the Department has retired the standalone Adult Care Facility (ACF) Directory located at https://health.data.ny.gov/Health/Adult-Care-Facility-Directory/wssx-idhx/data. ACF data is posted online at https://health.data.ny.gov/Health/Health-Facility-Certification-Information/2g9y-7kqm and https://health.data.ny.gov/Health/Health-Facility-General-Information/vn5v-hh5r. Each licensed facility’s operating certificate number is located at https://health.data.ny.gov/Health/Health-Facility-Certification-Information/2g9y-7kqm and its capacity located at https://health.data.ny.gov/Health/Health-Facility-General-Information/vn5v-hh5r. To retrieve both sets of data, a user must download both referenced datasets with the understanding that the common delineator is the Facility ID, a site-specific identification assigned to each licensed ACF. Downloaded data will contain all licensed ACFs, and can be filtered in a variety of ways at the user’s discretion. Questions may be directed to the New York State Department of Health via the “Contact Dataset Owner” box on each page.

HUD CARES Act Allocation Data

  HUD CARES Act supplemental allocation amounts - cities and counties plus non-entitlement About HUD CARES Act Allocation Data: Links to several different datasets related to CARES ACT supplemental funding, including Treasury Dept and HUD allocations for cities, counties, tribal communities and non-entitlements. An additional dataset contains allocations for HHS Provider Relief Fund COVID-19 High-Impact Payments to individual providers by city and state. Click for more detail.
  Geography Level: State, City or CountyItem Vintage: Not Available
  Update Frequency: N/AAgency: HUDAvailable File Type: Excel (Links goes to same HUD CPD dataset link as listed in HUD Housing datasets listed above) 

  Return to Other Federal Agency Datasets Page

This dataset describes the number and density of health care services in each census tract in the United States. The data includes counts, per capita densities, and area densities per tract for many types of businesses in the health care sector, including doctors, dentists, mental health providers, hospitals, nursing homes, and pharmacies.

States report information from two reporting populations: (1) The Served Population which is information on all youth receiving at least one independent living services paid or provided by the Chafee Program agency, and (2) Youth completing the NYTD Survey. States survey youth regarding six outcomes: financial self-sufficiency, experience with homelessness, educational attainment, positive connections with adults, high-risk behaviors, and access to health insurance. States collect outcomes information by conducting a survey of youth in foster care on or around their 17th birthday, also referred to as the baseline population. States will track these youth as they age and conduct a new outcome survey on or around the youth's 19th birthday; and again on or around the youth's 21st birthday, also referred to as the follow-up population. States will collect outcomes information on these older youth at ages 19 or 21 regardless of their foster care status or whether they are still receiving independent living services from the State. Depending on the size of the State's foster care youth population, some States may conduct a random sample of the baseline population of the 17-year-olds that participate in the outcomes survey so that they can follow a smaller group of youth as they age. All States will collect and report outcome information on a new baseline population cohort every three years.

Units of Response: Current and former youth in foster care

Type of Data: Administrative

Tribal Data: No

Periodicity: Annual

Demographic Indicators: Ethnicity;Race;Sex

SORN: Not Applicable

Data Use Agreement: https://www.ndacan.acf.hhs.gov/datasets/request-dataset.cfm

Data Use Agreement Location: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf

Granularity: Individual

Spatial: United States

Geocoding: FIPS Code

NOTE: Please Read Text File named "ERD Relationship Text" for Detailed Information.

This dataset represents a complete healthcare management system modeled as a relational database containing over 20 interlinked tables. It captures the entire lifecycle of healthcare operations from patient registration to diagnosis, treatment, billing, inventory, and vendor management. The data structure is designed to simulate a real-world hospital information system (HIS), enabling advanced analytics, data modeling, and visualization. You can easily visualize and explore the schema using tools like dbdiagram.io by pasting the provided table definitions.

The dataset covers multiple operational areas of a hospital including patient information, clinical operations, financial transactions, human resources, and logistics.

Patient Information includes personal, contact, and emergency details, along with identification and insurance. Clinical Operations include visits, appointments, diagnoses, treatments, and medications. Financial Transactions cover bills, payments, and vendor settlements. Human Resources include staff details, departments, and medical teams. Logistics and Inventory include equipment, medicines, supplies, and vendor relationships.

• Patients (STG_EHP_PATN) are linked to Appointments, Visits, Diagnoses, Treatments, Bills, and Insurance Policies.
• Medical Teams (STG_EHP_MEDT) connect Staff with Visits and Treatments.
• Allergies and Patient Allergies tables track patient-specific allergy information.
• Financial tables (Bills, Payments, Vendor Payments) are interconnected through reference numbers for consistent transaction tracing.
• Inventory tables record medicine and equipment stock movements, supply receipts, and vendor sourcing.

This dataset can be used for data modeling and SQL practice for complex joins and normalization, healthcare analytics projects involving cost analysis, treatment efficiency, and patient demographics, visualization projects in Power BI, Tableau, or Domo for operational insights, building ETL pipelines and data warehouse models for healthcare systems, and machine learning applications such as predicting patient readmission, billing anomalies, or treatment outcomes.

To explore the data relationships visually, go to dbdiagram.io, paste the entire provided schema code, and press 2 then 1 (or 2 and Enter) to auto-align the diagram. You’ll see an interactive Entity Relationship Diagram (ERD) representing the entire healthcare ecosystem.

Total Tables: 20+ Total Columns: 200+ Primary Focus: Patient Management, Clinical Operations, Billing, and Supply Chain

Recent expansions of unemployment insurance could raise unemployment by 1.6 percentage points but reduce cumulative deaths by 2.1 percent.

Letsel Informatie Systeem (LIS)

This data set contains the national average (mean) scores of Medicare-certified hospice providers on the Consumer Assessment of Healthcare Providers and Systems (CAHPS®) Hospice Survey measures.

Information on OCFS regulated child care programs, which includes program overview information and violation history.

Non-expenditure health care data provide information on institutions providing health care in countries, on resources used and on output produced in the framework of health care provision.

Data on health care form a major element of public health information as they describe the capacities available for different types of health care provision as well as potential 'bottlenecks' observed. The quantity and quality of health care services provided and the work sharing established between the different institutions are a subject of ongoing debate in all countries. Sustainability - continuously providing the necessary monetary and personal resources needed - and meeting the challenges of ageing societies are the primary perspectives used when analysing and using the data.

The resource-related data refer to both human and technical resources, i.e. they relate to:

• Health care staff: 'manpower' active in the health care sector (doctors, dentists, nurses, etc.);
• Heath workforce migration: migration movements of doctors and nurses;
• Health care facilities: technical capacity dimensions (hospital beds, beds in nursing and residential care facilities, etc.).

Annual national and regional data are provided in absolute numbers and in population-standardised rates (per 100 000 inhabitants).

Wherever applicable, the definitions and classifications of the System of Health Accounts (SHA) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). For hospital discharges, the International Shortlist for Hospital Morbidity Tabulation (ISHMT) is used.

Health care data on resources are largely based on administrative data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable.

Specialty clinics include freestanding surgical, chronic dialysis, and rehabilitation clinics as well as alternative birth centers. The complete data set of annual utilization data reported by specialty clinics contains descriptive information on services and encounters, basic information including the number of surgical operating rooms, number of surgeries performed, number of patients, number of encounters by service type, staffing, and major capital expenditures. Also included are type of ownership and payment source information.The documentation, including report forms, is available for each reporting year.

The Eldercare Locator is a searchable database that allows a user to search via zip code or city/ state for agencies at the State and local levels that provide services to older adults.

NHS England collect and publish data about people with dementia at each GP practice in England, to enable NHS GPs and commissioners to make informed choices about how to plan their dementia services around patients’ needs. The publication includes the rate of dementia diagnosis. As not everyone with dementia has a formal diagnosis, this statistic compares the number of people thought to have dementia with the number of people diagnosed with dementia, aged 65 and over. Where current monthly data for a GP practice is unavailable, the most recent data available are used (up to a maximum of 6 months). Prior to October 2022, dementia data were collected via the dementia data core contract service and published as the "Recorded Dementia Diagnoses" series. The data in these two publication series are not comparable. This is due to the retrospective application of codes to patient records and changes in patient registration, as well as differences in coverage and the specification of several the counts. Refer to the ‘Related Links’ for the supporting information page where details on these changes can be found.

As of October 30, 2019, this data set will no longer be updated. A new citizen request app, called MyNorfolk, has been implemented and data from that app is available in this Open Data portal.

The Norfolk Cares data set provides data from the IMPACT System. The data was collected by phone calls, emails, iPhone requests, and on-line requests. This data set includes service requests from November 2014 to October 2019.