100+ datasets found
  1. Synthetic Healthcare Database for Research (SyH-DR)

    • catalog.data.gov
    • healthdata.gov
    • +2more
    Updated Sep 16, 2023
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    Agency for Healthcare Research and Quality (2023). Synthetic Healthcare Database for Research (SyH-DR) [Dataset]. https://catalog.data.gov/dataset/synthetic-healthcare-database-for-research-syh-dr
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    Dataset updated
    Sep 16, 2023
    Dataset provided by
    Agency for Healthcare Research and Qualityhttp://www.ahrq.gov/
    Description

    The Agency for Healthcare Research and Quality (AHRQ) created SyH-DR from eligibility and claims files for Medicare, Medicaid, and commercial insurance plans in calendar year 2016. SyH-DR contains data from a nationally representative sample of insured individuals for the 2016 calendar year. SyH-DR uses synthetic data elements at the claim level to resemble the marginal distribution of the original data elements. SyH-DR person-level data elements are not synthetic, but identifying information is aggregated or masked.

  2. d

    CarePrecise Authoritative Hospital Database (AHD)

    • datarade.ai
    .csv, .xls
    Updated Aug 27, 2021
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    CarePrecise (2021). CarePrecise Authoritative Hospital Database (AHD) [Dataset]. https://datarade.ai/data-products/careprecise-authoritative-hospital-database-ahd-careprecise
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    .csv, .xlsAvailable download formats
    Dataset updated
    Aug 27, 2021
    Dataset authored and provided by
    CarePrecise
    Area covered
    United States of America
    Description

    [IMPORTANT NOTE: Sample file posted on Datarade is not the complete dataset, as Datarade permits only a single CSV file. Visit https://www.careprecise.com/healthcare-provider-data-sample.htm for more complete samples.] Updated every month, CarePrecise developed the AHD to provide a comprehensive database of U.S. hospital information. Extracted from the CarePrecise master provider database with information all of the 6.3 million HIPAA-covered US healthcare providers and additional sources, the Authoritative Hospital Database (AHD) contains records for all HIPAA-covered hospitals. In this database of hospitals we include bed counts, patient satisfaction data, hospital system ownership, hospital charges and cases by Zip Code®, and more. Most records include a cabinet-level or director-level contact. A PlaceKey is provided where available.

    The AHD includes bed counts for 95% of hospitals, full contact information on 85%, and fax numbers for 62%. We include detailed patient satisfaction data, employee counts, and medical procedure volumes.

    The AHD integrates directly with our extended provider data product to bring you the physicians and practice groups affiliated with the hospitals. This combination of data is the only commercially available hospital dataset of this depth.

    NEW: Hospital NPI to CCN Rollup A CarePrecise Exclusive. Using advanced record-linkage technology, the AHD now includes a new file that makes it possible to mine the vast hospital information available in the National Provider Identifier registry database. Hospitals may have dozens of NPI records, each with its own information about a unit, listing facility type and/or medical specialties practiced, as well as separate contact names. To wield the power of this new feature, you'll need the CarePrecise Master Bundle, which contains all of the publicly available NPI registry data. These data are available in other CarePrecise data products.

    Counts are approximate due to ongoing updates. Please review the current AHD information here: https://www.careprecise.com/detail_authoritative_hospital_database.htm

    The AHD is sold as-is and no warranty is offered regarding accuracy, timeliness, completeness, or fitness for any purpose.

  3. Healthcare Documentation Database

    • kaggle.com
    Updated Feb 26, 2024
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    Harshit Sharma (2024). Healthcare Documentation Database [Dataset]. https://www.kaggle.com/datasets/harshitstark/healthcare-documentation-database
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 26, 2024
    Dataset provided by
    Kaggle
    Authors
    Harshit Sharma
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    The "Healthcare Documentation Database" is a concise yet comprehensive collection of medical transcriptions spanning various specialties and patient encounters. Each entry includes a brief description of the medical encounter, categorized by specialty and accompanied by a unique sample name for easy reference. The transcriptions capture essential details such as patient history, symptoms, diagnoses, and treatments, providing valuable insights for healthcare professionals and researchers. This dataset serves as a valuable resource for analyzing trends, patterns, and outcomes across different medical disciplines, facilitating evidence-based decision-making and research advancements in healthcare. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F18544731%2Fb8dea5ab6b921b5affbb637fdd99de5c%2Fhealth_g1164501548.jpg?generation=1708926919496930&alt=media" alt="">

  4. HCUP Nationwide Ambulatory Surgery Sample (NASS) Database – Restricted...

    • catalog.data.gov
    • healthdata.gov
    • +1more
    Updated Jul 16, 2025
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    Agency for Healthcare Research and Quality, Department of Health & Human Services (2025). HCUP Nationwide Ambulatory Surgery Sample (NASS) Database – Restricted Access [Dataset]. https://catalog.data.gov/dataset/hcup-nationwide-ambulatory-surgery-sample-nass-database-restricted-access
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    Dataset updated
    Jul 16, 2025
    Description

    The largest all-payer ambulatory surgery database in the United States, the Healthcare Cost and Utilization Project (HCUP) Nationwide Ambulatory Surgery Sample (NASS) produces national estimates of major ambulatory surgery encounters in hospital-owned facilities. Major ambulatory surgeries are defined as selected major therapeutic procedures that require the use of an operating room, penetrate or break the skin, and involve regional anesthesia, general anesthesia, or sedation to control pain (i.e., surgeries flagged as "narrow" in the HCUP Surgery Flag Software). Unweighted, the NASS contains approximately 9.0 million ambulatory surgery encounters each year and approximately 11.8 million ambulatory surgery procedures. Weighted, it estimates approximately 11.9 million ambulatory surgery encounters and 15.7 million ambulatory surgery procedures. Sampled from the HCUP State Ambulatory Surgery and Services Databases (SASD) and State Emergency Department Databases (SEDD) in order to capture both planned and emergent major ambulatory surgeries, the NASS can be used to examine selected ambulatory surgery utilization patterns. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. The NASS contains clinical and resource-use information that is included in a typical hospital-owned facility record, including patient characteristics, clinical diagnostic and surgical procedure codes, disposition of patients, total charges, facility characteristics, and expected source of payment, regardless of payer, including patients covered by Medicaid, private insurance, and the uninsured. The NASS excludes data elements that could directly or indirectly identify individuals, hospitals, or states. The NASS is limited to encounters with at least one in-scope major ambulatory surgery on the record, performed at hospital-owned facilities. Procedures intended primarily for diagnostic purposes are not considered in-scope. Restricted access data files are available with a data use agreement and brief online security training.

  5. d

    CarePrecise Authoritative Physician Database

    • datarade.ai
    .csv
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    CarePrecise, CarePrecise Authoritative Physician Database [Dataset]. https://datarade.ai/data-products/careprecise-authoritative-physician-database-careprecise
    Explore at:
    .csvAvailable download formats
    Dataset authored and provided by
    CarePrecise
    Area covered
    United States of America
    Description

    [IMPORTANT NOTE: Sample file posted on Datarade is not the complete dataset, as Datarade permits only a single CSV file. Visit https://www.careprecise.com/healthcare-provider-data-sample.htm for more complete samples.] The APD is the only physician database with this deep pool of data, available for immediate download in Microsoft Access format and CSV files, for use with spreadsheet, database or CRM software on Windows PC, Mac or Linux.:

    100% of HIPAA-covered U.S. MD and DO physicians Their practice groups, with group size Independent practice indicator Sole proprietor indicator Their hospital affiliations All reported specialties, including the primary Years in practice Medical school attended Phone and fax numbers Rural/Urban practice indicator Practice and Mailing addresses Gender Current LEIE sanctions License Medicare practice PAC ID C-suite and director-level contacts for physician groups and hospitals Exclusive CoLoCode™ linkage between physicians practicing together and their group NPI records

  6. HCUP National Inpatient Database

    • redivis.com
    application/jsonl +7
    Updated May 11, 2024
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    Stanford Center for Population Health Sciences (2024). HCUP National Inpatient Database [Dataset]. http://doi.org/10.57761/d67b-fz41
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    application/jsonl, csv, avro, arrow, parquet, stata, sas, spssAvailable download formats
    Dataset updated
    May 11, 2024
    Dataset provided by
    Redivis Inc.
    Authors
    Stanford Center for Population Health Sciences
    Time period covered
    Jan 1, 2000 - Dec 31, 2021
    Description

    Abstract

    The NIS is the largest publicly available all-payer inpatient healthcare database designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. Unweighted, it contains data from around 7 million hospital stays each year. Weighted, it estimates around 35 million hospitalizations nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels.

    Its large sample size is ideal for developing national and regional estimates and enables analyses of rare conditions, uncommon treatments, and special populations.

    Usage

    IMPORTANT NOTE: Some records are missing from the Severity Measures table for 2017 & 2018, but none are missing from any of the other 2012-2020 data. We are in the process of trying to recover the missing records, and will update this note when we have done so.

    Also %3Cu%3EDO NOT%3C/u%3E

    use this data without referring to the NIS Database Documentation, which includes:

    • Description of NIS Database
    • Restrictions on Use

    %3C!-- --%3E

    • Data Elements
    • Additional Resources for Data Elements
    • ICD-10-CM/PCS Data Included in the NIS Starting with 2015 (More details about this transition available here.)
    • Known Data Issues
    • NIS Supplemental Files
    • HCUP Tools: Labels and Formats
    • Obtaining HCUP Data

    %3C!-- --%3E

    Before Manuscript Submission

    All manuscripts (and other items you'd like to publish) must be submitted to

    phsdatacore@stanford.edu for approval prior to journal submission.

    We will check your cell sizes and citations.

    For more information about how to cite PHS and PHS datasets, please visit:

    https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

    HCUP Online Tutorials

    For additional assistance, AHRQ has created the HCUP Online Tutorial Series, a series of free, interactive courses which provide training on technical methods for conducting research with HCUP data. Topics include an HCUP Overview Course and these tutorials:

    • The HCUP Sampling Design tutorial is designed to help users learn how to account for sample design in their work with HCUP national (nationwide) databases. • The Producing National HCUP Estimates tutorial is designed to help users understand how the three national (nationwide) databases – the NIS, Nationwide Emergency Department Sample (NEDS), and Kids' Inpatient Database (KID) – can be used to produce national and regional estimates. HCUP 2020 NIS (8/22/22) 14 Introduction • The Calculating Standard Errors tutorial shows how to accurately determine the precision of the estimates produced from the HCUP nationwide databases. Users will learn two methods for calculating standard errors for estimates produced from the HCUP national (nationwide) databases. • The HCUP Multi-year Analysis tutorial presents solutions that may be necessary when conducting analyses that span multiple years of HCUP data. • The HCUP Software Tools Tutorial provides instructions on how to apply the AHRQ software tools to HCUP or other administrative databases.

    New tutorials are added periodically, and existing tutorials are updated when necessary. The Online Tutorial Series is located on the HCUP-US website at www.hcupus.ahrq.gov/tech_assist/tutorials.jsp.

    Important notes about the 2015 data

    In 2015, AHRQ restructured the data as described here:

    https://hcup-us.ahrq.gov/db/nation/nis/2015HCUPNationalInpatientSample.pdf

    Some key points:

    • For the 2015 data, all diagnosis and procedure data elements, including any data elements derived from diagnoses and procedures, were moved out of the Core File and into the Diagnosis and Procedure Groups Files.
    • Prior to 2015, and for Q1-3 of 2015, the DX1-30 and PR1-15 variables (which use ICD-9 codes) variables were used, but starting in Q4 of 2015, the I10_DX1-30 and I10_PR1-I10-15 (which use ICD-10 codes) were used. The best way to identify discharges for quarter 1-3 or quarter 4 is based on the value of the diagnosis version (DXVER); For quarters 1-3, DXVER has a value of 9; while for quarter 4, DXVER has a value of 10.
    • Some other variables also transitioned in Q4 of 2015. Please refer to the link above for more details.
    • Starting in 2016, the diagnosis and procedure information returned to the Core file. Additional details about the data in 2016 are available here: https://hcup-us.ahrq.gov/db/nation/nis/NISChangesBeginningDataYr2016.pdf

    %3C!-- --%3E

    NIS Areas of Research and HCUP Publications

  7. NIS_2016

    • redivis.com
    application/jsonl +7
    Updated Jan 27, 2025
    + more versions
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    Center for Surgery and Public Health (2025). NIS_2016 [Dataset]. https://redivis.com/datasets/e4ms-4dp8mape8
    Explore at:
    avro, sas, parquet, csv, arrow, stata, spss, application/jsonlAvailable download formats
    Dataset updated
    Jan 27, 2025
    Dataset provided by
    Redivis Inc.
    Authors
    Center for Surgery and Public Health
    Description

    Usage

    The National (Nationwide) Inpatient Sample (NIS) is part of a family of databases and software tools developed for the Healthcare Cost and Utilization Project (HCUP). The NIS is the largest publicly available all-payer inpatient healthcare database designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. Unweighted, it contains data from around 7 million hospital stays each year. Weighted, it estimates around 35 million hospitalizations nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels.

  8. HCUP Nationwide Emergency Department Sample

    • datacatalog.med.nyu.edu
    Updated Nov 3, 2022
    + more versions
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    United States - Agency for Healthcare Research and Quality (AHRQ) (2022). HCUP Nationwide Emergency Department Sample [Dataset]. https://datacatalog.med.nyu.edu/dataset/10014
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    Dataset updated
    Nov 3, 2022
    Dataset provided by
    Agency for Healthcare Research and Qualityhttp://www.ahrq.gov/
    Authors
    United States - Agency for Healthcare Research and Quality (AHRQ)
    Time period covered
    Jan 1, 2006 - Present
    Area covered
    Texas, North Carolina, Nevada, Nebraska, Michigan, Hawaii, Georgia, Washington, D.C., Oregon, Missouri
    Description

    The Nationwide Emergency Department Sample (NEDS) is part of a family of databases and software tools developed for the Healthcare Cost and Utilization Project (HCUP). The NEDS is the largest all-payer emergency department (ED) database in the United States, yielding national estimates of hospital-based ED visits. The NEDS enables analyses of ED utilization patterns and supports public health professionals, administrators, policymakers, and clinicians in their decisionmaking regarding this critical source of care.

  9. d

    CompanyData.com (BoldData) - Healthcare Company Data (2.5M Companies)

    • datarade.ai
    Updated Nov 13, 2020
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    CompanyData.com (BoldData) (2020). CompanyData.com (BoldData) - Healthcare Company Data (2.5M Companies) [Dataset]. https://datarade.ai/data-products/healthcare-data-bolddata
    Explore at:
    .json, .csv, .xls, .txtAvailable download formats
    Dataset updated
    Nov 13, 2020
    Dataset authored and provided by
    CompanyData.com (BoldData)
    Area covered
    Niger, Micronesia (Federated States of), Finland, Chile, Burundi, Trinidad and Tobago, Tokelau, Nigeria, Kenya, Svalbard and Jan Mayen
    Description

    CompanyData.com, (BoldData), is your gateway to verified global business intelligence. Our Healthcare Company Database provides in-depth, accurate data on 2.5 million organizations across the healthcare industry—from hospitals and clinics to pharmaceutical companies, biotech firms, and medical equipment suppliers. Every record is sourced from official trade registers and healthcare authorities, ensuring regulatory compliance and unmatched data quality.

    We deliver comprehensive company profiles enriched with key firmographics, industry classifications, ownership structures, executive contact details, emails, direct phone numbers, and mobile data. Updated regularly and quality-checked against official sources, our healthcare data empowers organizations to make informed decisions across critical functions—from KYC verification and compliance to targeted sales campaigns, healthcare market analysis, CRM enrichment, and AI model development.

    To suit every workflow, we offer flexible delivery solutions including custom bulk files, self-service platform access, real-time API integrations, and on-demand enrichment services. Whether you're scaling a B2B marketing strategy or building healthcare analytics tools, our datasets are ready to plug into your operations.

    With coverage of over 380 million verified companies across all industries and regions, CompanyData.com (BoldData) offers the global reach and industry precision that modern organizations demand. Tap into our healthcare data solutions to discover new opportunities, reduce risk, and power smarter business growth across the global health economy.

  10. d

    Healthcare Professional Email List (1.2 million contacts) by Infotanks Media...

    • datarade.ai
    Updated Jun 21, 2021
    + more versions
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    Infotanks Media (2021). Healthcare Professional Email List (1.2 million contacts) by Infotanks Media [Dataset]. https://datarade.ai/data-products/healthcare-professional-email-list-infotanks-media
    Explore at:
    Dataset updated
    Jun 21, 2021
    Dataset authored and provided by
    Infotanks Media
    Area covered
    Cabo Verde, Burundi, Belgium, American Samoa, Bahrain, Brunei Darussalam, Honduras, Seychelles, Bulgaria, Aruba
    Description

    Facilitate marketing campaigns with the healthcare email list from Infotanks Media, including doctors, healthcare professionals, NPI numbers, physician specialties, and more. Buy targeted email lists of healthcare professionals and connect with doctors, specialists, and other healthcare professionals to promote your products and services. Hyper personalize campaigns to increase engagement for better chances of conversion. Reach out to our data experts today! Access 1.2 million physician contact database with 150+ specialties, including chiropractors, cardiologists, psychiatrists, and radiologists, among others. Get ready to integrate healthcare email lists from Infotanks Media to start email marketing campaigns through CRM and ESP. Contact us right now! Ensure guaranteed lead generation with segmented email marketing strategies for specialists, departments, and more. Make the best use of target marketing to progress and move closer to your business goals with email listing services for healthcare professionals. Infotanks Media provides 100% verified healthcare email lists with the highest email deliverability guarantee of 95%. Get a custom quote today as per your requirements. Enhance your marketing campaigns with healthcare email lists from 170+ countries to build your global outreach. Request your free sample today! Personalize your business communication and interactions to maximize conversion rates with high-quality contact data. Grow your business network in your target markets from anywhere globally with a guaranteed 95% contact accuracy of the healthcare email lists from Infotanks Media. Contact data experts at Infotanks Media from the healthcare industry to get a quick sample for free. Please write to us or call today!

    Hyper target within and outside your desired markets with GDPR and CAN-SPAM compliant healthcare email lists that get integrated into your CRM and ESPs. Balance out the sales and marketing efforts by aligning goals using email lists from the healthcare industry. Build strong business relationships with potential clients through personalized campaigns. Call Infotanks Media for a free consultation. Explore new geographies and target markets with a focused approach using healthcare email lists. Align your sales teams and marketing teams through personalized email marketing campaigns to ensure they accomplish business goals together. Add value and grow revenue to take your business to the next level of success. Double up your business and revenue growth with email lists of healthcare professionals. Send segmented campaigns to monitor behaviors and understand the purchasing habits of your potential clients. Send follow-up nurturing email marketing campaigns to attract your potential clients to become converted customers. Close deals sooner with detailed information of your prospects using the healthcare email list from Infotanks Media. Reach healthcare professionals on their preferred platform of communication with the email list of healthcare professionals. Identify, capture, explore, and grow in your target markets anywhere globally with a fully verified, validated, and compliant email database of healthcare professionals. Move beyond the traditional approach and automate sales cycles with buying triggers sent through email marketing campaigns. Use the healthcare email list from Infotanks Media to engage with your targeted potential clients and get them to respond. Increase email marketing campaign response rate to convert better! Reach out to Infotanks Media to customize your healthcare email lists. Call today!

  11. E

    The French National Healthcare Data System

    • healthinformationportal.eu
    html
    Updated Jan 17, 2023
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    Directorate of Research, Studies, Evaluation and Statistics (DREES), La Caisse Nationale d’Assurance Maladie et de Travailleurs Salariés (CNAMTS), Institut national de la santé et de la recherche médicale (INSERM), Agence technique pour l’information sur l’hospitalisation (ATIH), Institut National des Données de Santé (INDS) (2023). The French National Healthcare Data System [Dataset]. https://www.healthinformationportal.eu/national-node/france/sources
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset authored and provided by
    Directorate of Research, Studies, Evaluation and Statistics (DREES), La Caisse Nationale d’Assurance Maladie et de Travailleurs Salariés (CNAMTS), Institut national de la santé et de la recherche médicale (INSERM), Agence technique pour l’information sur l’hospitalisation (ATIH), Institut National des Données de Santé (INDS)
    License

    https://www.snds.gouv.fr/SNDS/Processus-d-acces-aux-donneeshttps://www.snds.gouv.fr/SNDS/Processus-d-acces-aux-donnees

    Area covered
    France
    Variables measured
    title, topics, acronym, country, language, data_owners, description, free_keywords, alternative_title, access_information, and 6 more
    Measurement technique
    Multiple sources
    Description

    The National Health Data System (SNDS) will make it possible to link:

    • health insurance data (SNIIRAM database);
    • hospital data (PMSI database);
    • the medical causes of death (base of the CépiDC of Inserm);
    • disability-related data (from MDPH - CNSA data);
    • a sample of data from complementary health insurance organisations.

    The first two categories of data are already available and constitute the first version of the SNDS. The medical causes of death should feed the SNDS from the second half of 2017. The first data from the CNSA will arrive from 2018 and the sample of complementary organizations in 2019.

    The purpose of the SNDS is to make these data available in order to promote studies, research or evaluations of a nature in the public interest and contributing to one of the following purposes:

    • health information;
    • the implementation of health policies;
    • knowledge of health expenditure;
    • informing professionals and establishments about their activities;
    • innovation in the fields of health and medico-social care;
    • monitoring, surveillance and health security.
  12. E

    IMA-AIM data set including Permanent Sample

    • healthinformationportal.eu
    html
    Updated Mar 2, 2022
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    IMA-AIM (2022). IMA-AIM data set including Permanent Sample [Dataset]. https://www.healthinformationportal.eu/health-information-sources/ima-aim-data-set-including-permanent-sample
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Mar 2, 2022
    Dataset authored and provided by
    IMA-AIM
    License

    https://aim-ima.be/Donnees-individuelles-realiser-l?lang=frhttps://aim-ima.be/Donnees-individuelles-realiser-l?lang=fr

    Variables measured
    sex, title, topics, country, language, data_owners, description, contact_name, geo_coverage, contact_email, and 12 more
    Measurement technique
    Hospital resources & Healthcare resources
    Description

    IMA-AIM can provide you with detailed data on the health care system in Belgium. Their data collection includes information on the reimbursed care and medicines of the 11 million citizens insured in our country. The data is collected by the 7 health insurance funds and processed, analysed and made available for research by IMA-AIM.

    The seven health insurance funds in Belgium collect a lot of data about their members in order to be able to carry out their tasks. IMA-AIM brings these data together in databases for the purpose of analysis and research. The databases contain three types of data: population data (demographic and socio-economic characteristics), information about reimbursed health care and information about reimbursed medicines.

    The Permanent Sample (EPS) is a longitudinal dataset containing data from the Population, Health Care and Pharmanet databases, as well as data on hospitalisations. The data are available in separate datasets per calendar year. The aim of EPS is to make the administrative data of the health insurance funds permanently available to a number of federal and regional partners. More information about the EPS: https://metadata.ima-aim.be/nl/app/bdds/Ps

  13. Database Creation Description and Data Dictionaries

    • figshare.com
    txt
    Updated Aug 11, 2016
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    Jordan Kempker; John David Ike (2016). Database Creation Description and Data Dictionaries [Dataset]. http://doi.org/10.6084/m9.figshare.3569067.v3
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    txtAvailable download formats
    Dataset updated
    Aug 11, 2016
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Jordan Kempker; John David Ike
    License

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

    Description

    There are several Microsoft Word documents here detailing data creation methods and with various dictionaries describing the included and derived variables.The Database Creation Description is meant to walk a user through some of the steps detailed in the SAS code with this project.The alphabetical list of variables is intended for users as sometimes this makes some coding steps easier to copy and paste from this list instead of retyping.The NIS Data Dictionary contains some general dataset description as well as each variable's responses.

  14. G

    Open Database of Healthcare Facilities

    • open.canada.ca
    • catalogue.arctic-sdi.org
    csv, esri rest +4
    Updated Mar 2, 2022
    + more versions
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    Statistics Canada (2022). Open Database of Healthcare Facilities [Dataset]. https://open.canada.ca/data/en/dataset/a1bcd4ee-8e57-499b-9c6f-94f6902fdf32
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    fgdb/gdb, esri rest, csv, html, pdf, wmsAvailable download formats
    Dataset updated
    Mar 2, 2022
    Dataset provided by
    Statistics Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    The Open Database of Healthcare Facilities (ODHF) is a collection of open data containing the names, types, and locations of health facilities across Canada. It is released under the Open Government License - Canada. The ODHF compiles open, publicly available, and directly-provided data on health facilities across Canada. Data sources include regional health authorities, provincial, territorial and municipal governments, and public health and professional healthcare bodies. This database aims to provide enhanced access to a harmonized listing of health facilities across Canada by making them available as open data. This database is a component of the Linkable Open Data Environment (LODE).

  15. n

    Hospital Admission Data from the Agency for HealthCare Research and Quality...

    • cmr.earthdata.nasa.gov
    Updated Apr 20, 2017
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    (2017). Hospital Admission Data from the Agency for HealthCare Research and Quality (AHRQ) [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1214136020-SCIOPS
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    Dataset updated
    Apr 20, 2017
    Time period covered
    Jan 1, 1970 - Present
    Description

    The Agency for Healthcare Research and Quality (AHRQ, formerly the Agency for Health Care Policy and Research) maintains the Healthcare Cost and Utilization Project (HCUP). HCUP is a Federal-State-industry partnership to build a standardized, multi-State health data system. AHRQ has taken the lead in developing HCUP databases, Web-based products, and software tools and making them available for restricted access public release.

    HCUP comprises a family of administrative longitudinal databases-including State-specific hospital-discharge databases and a national sample of discharges from community hospitals.

    HCUP databases contain patient-level information compiled in a uniform format with privacy protections in place. * The Nationwide Inpatient Sample (NIS) includes inpatient data from a national sample (about 20% of U.S. community hospitals) including roughly 7 million discharges from about 1,000 hospitals. It is the largest all-payer inpatient database in the U.S.; data are now available from 1988-1998. The NIS is ideal for developing national estimates, for analyzing national trends, and for research that requires a large sample size. * The State Inpatient Databases (SID) cover individual data sets in community hospitals from 22 participating States that represent more than half of all U.S. hospital discharges. The data have been translated into a uniform format to facilitate cross-State comparisons. The SID are particularly well-suited for policy inquiries unique to a specific State, studies comparing two or more States, market area research, and small area variation analyses.

    • The State Ambulatory Surgery Databases (SASD) contain data from ambulatory care encounters in 9 participating States. The SASD capture surgeries performed on the same day in which patients are admitted and released form hospital- affiliated ambulatory surgery sites. The SASD are well suited for research that requires complete enumeration of hospital-based ambulatory surgeries within market areas and States.
    • The project's newest restricted access public release is the Kids' Inpatient Database (KID), containing hospital inpatient stays for children 18 years of age and younger. Researchers and policymakers can use the KID to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The KID is the only all-payer inpatient care database for children in the U.S. It contains data from approximately 1.9 million hospital discharges for children. The data are drawn from 22 HCUP 1997 State Inpatient Databases and include a sample of pediatric general discharges from over 2,500 U.S. community hospitals (defined as short-term, non-Federal, general and specialty hospitals, excluding hospital units of other institutions). A key strength of the KID is that the large sample size enables analyses of both common and rare conditions; uncommon treatments, and organ transplantation. The KID also includes charge information on all patients, regardless of payer, including children covered by Medicaid, private insurance, and the uninsured.

      HCUP also contains powerful, user-friendly software that can be used with both HCUP data and with other administrative databases. The AHRQ has developed three powerful software tools Quality Indicators (QIs), Clinical Classification Software (CCS) and HCUPnet. See more on the agency's webpages.

  16. National Inpatient Sample (NIS) - Restricted Access Files

    • catalog.data.gov
    • healthdata.gov
    • +2more
    Updated Feb 22, 2025
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    Agency for Healthcare Research and Quality, Department of Health & Human Services (2025). National Inpatient Sample (NIS) - Restricted Access Files [Dataset]. https://catalog.data.gov/dataset/hcup-national-nationwide-inpatient-sample-nis-restricted-access-file
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    Dataset updated
    Feb 22, 2025
    Description

    The Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) is the largest publicly available all-payer inpatient care database in the United States. The NIS is designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. Unweighted, it contains data from more than 7 million hospital stays each year. Weighted, it estimates more than 35 million hospitalizations nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels. Starting with the 2012 data year, the NIS is a sample of discharges from all hospitals participating in HCUP, covering more than 97 percent of the U.S. population. For prior years, the NIS was a sample of hospitals. The NIS allows for weighted national estimates to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. The NIS's large sample size enables analyses of rare conditions, such as congenital anomalies; uncommon treatments, such as organ transplantation; and special patient populations, such as the uninsured. NIS data are available since 1988, allowing analysis of trends over time. The NIS inpatient data include clinical and resource use information typically available from discharge abstracts with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, discharge status, patient demographics (e.g., sex, age), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NIS excludes data elements that could directly or indirectly identify individuals. Restricted access data files are available with a data use agreement and brief online security training.

  17. d

    Healthcare Data- Healthcare Contact Data, Healthcare Professionals Data,...

    • datarade.ai
    Updated Nov 26, 2023
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    APISCRAPY (2023). Healthcare Data- Healthcare Contact Data, Healthcare Professionals Data, Scrape All Publicly Available Healthcare Related Data's | 50% Cost Saving [Dataset]. https://datarade.ai/data-products/healthcare-data-hospital-datasets-healthcare-professional-apiscrapy
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    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Nov 26, 2023
    Dataset authored and provided by
    APISCRAPY
    Area covered
    Russian Federation, Albania, New Zealand, Portugal, San Marino, Svalbard and Jan Mayen, Ukraine, United States of America, Sweden, United Kingdom
    Description

    Note:- Only publicly available data can be worked upon

    APISCRAPY leads the way in delivering hassle-free AI-driven healthcare data scraping, offering a seamless and ethical approach to accessing vital information. The platform excels in extracting Hospital Data, Healthcare Provider (HCP) Data, Pharma Data, telemedicine Data, and crucial COVID-19 Data, all without any associated costs.

    Ensuring accuracy and real-time updates, APISCRAPY's advanced technology navigates the intricacies of healthcare systems, providing users with valuable insights at no expense. Hospital Data, encompassing bed capacities and specialized services, is retrieved effortlessly to empower stakeholders in making informed decisions. The extraction of HCP Data supports collaboration and advancements in medical science without financial barriers.

    Pharma Data, Medical Imagery Data, and Medical Claims Data are sourced by APISCRAPY for market research, diagnostic breakthroughs, and streamlined financial workflows, respectively, all without incurring costs. Patient Data and Electronic Health Record (EHR) Data are handled with utmost privacy and compliance, enabling healthcare practitioners to access personalized information at no charge.

    In the realm of Telemedicine, APISCRAPY facilitates virtual healthcare services without imposing financial burdens. As a socially responsible entity, APISCRAPY offers free access to critical COVID-19 Data, contributing to global efforts in research and strategy development to combat the ongoing pandemic.

    APISCRAPY's commitment to providing cost-free, AI-driven healthcare data scraping underscores its dedication to making valuable information accessible to all, fostering a more inclusive and collaborative healthcare landscape. Through its innovative approach, APISCRAPY ensures that stakeholders can harness the power of data without financial constraints.

    [Related tags: Hospital Data, Healthcare Provider (HCP) Data,Pharma Data, Medical Imagery Data, Medical Claims Data, Patient Data, Electronic Health, Record (EHR) Data, Telemedicine Data, COVID-19 Data, Wearables Data , Donor Data, Healthcare Professionals Database , Healthcare data, Medical Data Extraction, Data Extraction, Web Scraping Medical Data]

  18. E

    National registry of health care providers

    • healthinformationportal.eu
    html
    Updated Sep 9, 2022
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    Croatian Institute of Public Health (2022). National registry of health care providers [Dataset]. https://www.healthinformationportal.eu/health-information-sources/national-registry-health-care-providers
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    htmlAvailable download formats
    Dataset updated
    Sep 9, 2022
    Dataset authored and provided by
    Croatian Institute of Public Health
    Variables measured
    sex, title, topics, country, language, data_owners, description, contact_name, geo_coverage, contact_email, and 12 more
    Measurement technique
    Registry data
    Description

    In a historical and developmental sense, the former one-year reporting on employees employed in healthcare grew during 1990/91. in the continuous collection and monitoring of data through the state Register of Health Professionals. The department maintains data on all healthcare workers and healthcare associates, and on administrative and technical staff for now only numerically, according to the number of permanent employees at the end of the year. In the future, it is intended to register employees who are not health-oriented and work in healthcare, and healthcare professionals who work outside the healthcare system can also be registered.

    Data on health workers and health care associates are required to be submitted not only by state and county-owned health institutions, but also by all private institutions, health workers who independently perform private practice, as well as trading companies for the performance of health activities, regardless of whether they have a contract with the Croatian Institute for health insurance.

    All employees are assigned a registration number (code) upon entry into the Registry's database on the day of employment. The connection with the Croatian Health Insurance Institute exists through the use of the registration number when registering, recognizing within the CEZIH system, as well as when registering prescriptions, referrals and other documents of the HZZO. that is, in monitoring and building the health information system.

    As an integral part of the same, relational databases also include data on health organizational units, representing the Register of Health Institutions. Namely, in addition to data on employees, the Registry, based on the decision of the Ministry of Health on work authorization, also records basic data on health institutions, surgeries and all other types of independent health units, regardless of the contract with the Croatian Health Insurance Institute or the type of ownership. As for employees, received data on the opening, closing, change of name, address, type and activity of the health organizational unit is also updated daily.

    Thus, the organizational structure of healthcare is monitored through the database, according to levels of healthcare, types of healthcare institutions, healthcare activities performed by institutions, divisions with regard to the type of ownership as well as territorial distribution.

    In addition to the importance of data on human potential and space, that is, the units where health care is provided, medical equipment is also an important factor in management and planning. One part of the department's work is related to the collection of data on this material resource. In the near future, it is planned to form a Register of Medically Expensive Equipment, which would be technologically and functionally connected with the existing two registers into a whole register of resources in healthcare.

    Also, the statistical research aims to include those entities that are not part of the health system, and in which health workers work, i.e. health activities are performed, such as long-term care homes, which means expanding the existing data of the Register of Health Institutions.

    In the last decade, a new IT application of the Registry of Health Care Professionals was created and an even better connection with the Croatian Institute for Health Insurance, for example through the use of the so-called population register or the register of insured persons. The register continues to be the source of data and the authorized institution for the delivery of data to international bodies such as the WHO and the joint WHO/Eurostat/OECD database. Within the scope of the Department's activities are also activities in international initiatives and programs, and with regard to the problems of statistical monitoring, shortages and planning of health workers. Since 2012, we have been involved in the implementation of the "Global Code of Practice on International Recruitment of Health Personnel", a recommendation that is also an instrument in the regulation, improvement and establishment of standards in the migration process.

    In the same year, the Department was involved in the work in the part of the program platform on the topic of Joint Action on European Health Workforce Planning and Forecasting.

    Also, during the past years, there has been cooperation on the topic of health workers within the framework of the South-eastern Europe Health Network (SEEHN).

  19. EMRBots: a 10,000-patient database

    • figshare.com
    zip
    Updated Sep 3, 2018
    + more versions
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    Uri Kartoun (2018). EMRBots: a 10,000-patient database [Dataset]. http://doi.org/10.6084/m9.figshare.7040060.v3
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    zipAvailable download formats
    Dataset updated
    Sep 3, 2018
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Uri Kartoun
    License

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

    Description

    A 10,000-patient database that contains in total 10,000 virtual patients, 36,143 admissions, and 10,726,505 lab observations.

  20. HCUP Nationwide Emergency Department Database (NEDS) Restricted Access File

    • catalog.data.gov
    • data.virginia.gov
    • +1more
    Updated Jul 29, 2025
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    Agency for Healthcare Research and Quality, Department of Health & Human Services (2025). HCUP Nationwide Emergency Department Database (NEDS) Restricted Access File [Dataset]. https://catalog.data.gov/dataset/hcup-nationwide-emergency-department-database-neds-restricted-access-file
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    Dataset updated
    Jul 29, 2025
    Description

    The Healthcare Cost and Utilization Project (HCUP) Nationwide Emergency Department Sample (NEDS) is the largest all-payer emergency department (ED) database in the United States. yielding national estimates of hospital-owned ED visits. Unweighted, it contains data from over 30 million ED visits each year. Weighted, it estimates roughly 145 million ED visits nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. Sampled from the HCUP State Inpatient Databases (SID) and State Emergency Department Databases (SEDD), the HCUP NEDS can be used to create national and regional estimates of ED care. The SID contain information on patients initially seen in the ED and subsequently admitted to the same hospital. The SEDD capture information on ED visits that do not result in an admission (i.e., treat-and-release visits and transfers to another hospital). Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. The NEDS contain information about geographic characteristics, hospital characteristics, patient characteristics, and the nature of visits (e.g., common reasons for ED visits, including injuries). The NEDS contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes ED charge information for over 85% of patients, regardless of expected payer, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NEDS excludes data elements that could directly or indirectly identify individuals, hospitals, or states.Restricted access data files are available with a data use agreement and brief online security training.

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Agency for Healthcare Research and Quality (2023). Synthetic Healthcare Database for Research (SyH-DR) [Dataset]. https://catalog.data.gov/dataset/synthetic-healthcare-database-for-research-syh-dr
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Synthetic Healthcare Database for Research (SyH-DR)

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9 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 16, 2023
Dataset provided by
Agency for Healthcare Research and Qualityhttp://www.ahrq.gov/
Description

The Agency for Healthcare Research and Quality (AHRQ) created SyH-DR from eligibility and claims files for Medicare, Medicaid, and commercial insurance plans in calendar year 2016. SyH-DR contains data from a nationally representative sample of insured individuals for the 2016 calendar year. SyH-DR uses synthetic data elements at the claim level to resemble the marginal distribution of the original data elements. SyH-DR person-level data elements are not synthetic, but identifying information is aggregated or masked.

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