This database is part of the National Medical Information System (NMIS). The National Health Care Practitioner Database (NHCPD) supports Veterans Health Administration Privacy Act requirements by segregating personal information about health care practitioners such as name and social security number from patient information recorded in the National Patient Care Database for Ambulatory Care Reporting and Primary Care Management Module.

AHRQ's database on Social Determinants of Health (SDOH) was created under a project funded by the Patient Centered Outcomes Research (PCOR) Trust Fund. The purpose of this project is to create easy to use, easily linkable SDOH-focused data to use in PCOR research, inform approaches to address emerging health issues, and ultimately contribute to improved health outcomes.The database was developed to make it easier to find a range of well documented, readily linkable SDOH variables across domains without having to access multiple source files, facilitating SDOH research and analysis.Variables in the files correspond to five key SDOH domains: social context (e.g., age, race/ethnicity, veteran status), economic context (e.g., income, unemployment rate), education, physical infrastructure (e.g, housing, crime, transportation), and healthcare context (e.g., health insurance). The files can be linked to other data by geography (county, ZIP Code, and census tract). The database includes data files and codebooks by year at three levels of geography, as well as a documentation file.The data contained in the SDOH database are drawn from multiple sources and variables may have differing availability, patterns of missing, and methodological considerations across sources, geographies, and years. Users should refer to the data source documentation and codebooks, as well as the original data sources, to help identify these patterns

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.

Abstract

Taiwan launched a single-payer National Health Insurance program on March 1, 1995.

Documentation

Taiwan launched a single-payer National Health Insurance program on March 1, 1995. As of 2014, 99.9% of Taiwan\342\200\231s population were enrolled. Foreigners in Taiwan are also eligible for this program. The database of this program contains registration files and original claim data for reimbursement. Large computerized databases derived from this system by the National Health Insurance Administration (the former Bureau of National Health Insurance, BNHI), Ministry of Health and Welfare (the former Department of Health, DOH), Taiwan and maintained by the National Health Research Institutes, Taiwan, are provided to scientists in Taiwan for research purposes.

An article describing these data in greater detail can be found here: Lessons From the Taiwan National Health Insurance Research Database

Patient characteristics Individuals enrolled in the Taiwanese national healthcare system

Data overview Data categories Inpatient Outpatient Pharmacy data Over-the-counter drugs Chinese medicine Clinician information Hospital information

Linkages include Household Birth certificate Death certificate Cancer Immunization record Reportable infectious disease

Notes If you are interested in a collaboration working with these data, please contact the Dr Ann Hsing at .

The Child Health System in Wales; includes birth registration and monitoring of child health examinations and immunisations.

The Child Health System in Wales; includes birth registration and monitoring of child health examinations and immunisations.

The dataset brings together data from local Child Health System databases which are held by NHS Trusts and used by them to administer child immunisation and health surveillance programmes.

The dataset contains all children born, resident or treated in Wales and born after 1987.

The global medical database software market is experiencing robust growth, driven by the increasing adoption of electronic health records (EHRs) and the rising need for efficient health information management (HIM) systems. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an estimated $45 billion by 2033. This expansion is fueled by several key factors: the increasing digitization of healthcare, the growing demand for data-driven insights to improve patient care and operational efficiency, and the expanding adoption of cloud-based solutions offering scalability and accessibility. Pharmaceutical companies and academic/research institutions are significant drivers, leveraging these systems for drug discovery, clinical trials management, and advanced research initiatives. However, challenges such as data security concerns, high implementation costs, and the need for robust interoperability between different systems pose restraints to market growth. The market is segmented by software type (EHR, HIM) and application (pharmaceutical companies, academic institutions, others), providing diverse opportunities for specialized vendors. Geographic expansion continues, with North America and Europe currently holding significant market share, but growth is anticipated across Asia-Pacific and other regions as healthcare infrastructure modernizes. The competitive landscape is dynamic, with established players like NextGen Healthcare and emerging companies like Pabau and EHR Your Way vying for market share. The success of individual vendors depends on factors including the scalability of their solutions, the depth of their data analytics capabilities, and the strength of their customer support network. The market's trajectory is heavily influenced by government regulations regarding data privacy and interoperability, the ongoing evolution of healthcare technology, and the increasing focus on personalized medicine. Further growth is likely to be seen in areas such as AI-powered diagnostics, predictive analytics, and advanced data visualization tools integrated within medical databases.

Users can search for sample policies, practices, and articles addressing health issues affecting schools and students. Topics include: asthma, school health programs, food safety, STIs, healthy eating, physical activity, sexual orientation, and teen pregnancy, among others. Background The School Health Database is maintained by the National School Boards Association (NSBA) and is supported by the Robert Woods Johnson Foundation and the Centers for Disease Control and Prevention (CDC). The School Health Database provides abstracts for policies and practices addressing health issues affecting schools and students. This database is useful for school policymakers. Topics include: asthma; communities of color; coordinated school health programs; food sa fety/food allergies; sexually transmitted infections; healthy eating; parent, family and community environment; physical activity; sexual orientation; gender identity; sun safety; teen pregnancy; t obacco use; and wellness. User Functionality Users can search approximately 2,000 abstracts. Users can search the database by: keyword, year, and target audience. Users can request more information or free materials by completing a Request Form on the website. Data Notes This database includes nearly 2,000 abstracts regarding programs and policies affecting the school health programs across the United States.

This database has been created following the completion of two scoping reviews that examined the production of migrant health reseach in Ireland covering the period 2000 - 2023 (Villarroel N, Hannigan A, Severoni S, Puthoopparambil S, MacFarlane A. Migrant health research in the Republic of Ireland: a scoping review. BMC Public Health. 2019 Mar 20;19(1):324. doi: 10.1186/s12889-019-6651-2 and Cronin A, Hannigan A, Ibrahim N, Seidler Y, Owoeye BO, Gasmalla W, Moyles T, MacFarlane A. An updated scoping review of migrant health research in Ireland. BMC Public Health. 2024 May 28;24(1):1425. doi: 10.1186/s12889-024-18920-0).This database lists all 142 studies included in this work and which were analysed using the 9 strategic areas identified in the World Health Organisation Strategy and Action Plan (SaAP) for Refugee and Migrant Health 2016–2023 (World Health Organization. EUR/RC66/8 Strategy and action plan for refugee and migrant health in the WHO European Region. 2016).The WHO SaAP lists 9 strategic priority areas (SA's) to improve refugee and migrant health;SA1: Collaborative action on migrant health issuesSA2: Advocacy for the right to health of refugees and migrantsSA3: Addressing the social determinants of healthSA4: Achieving public health preparednessSA5: Strengthening health systemsSA6: Communicable diseasesSA7: Noncommunicable diseasesSA8: Health screening and assessmentSA9: Improving health information and communicationFor further discussion on the framework analysis, please refer to the studies themselves.The creation of this database was a recommendation of the second scoping review, which is in line with Goal 4 of Ireland’s current National Intercultural Health Strategy (NIHS) (HSE. Second National Intercultural Health Strategy 2018–2023 [Internet]. 2018. https://www.hse.ie/eng/about/who/primarycare/socialinclusion/intercultural-health/intercultural-health-strategy.pdf). NIHS emphasises the need for the development of an accessible and comprehensive evidence base to guide policymaking and provide detailed analyses of health trends and needs within migrant communities. Such evidence supports public health education and offers critical oversight of migrant health research in Ireland. This database serves as a valuable resource for refugees, migrants, researchers, policymakers, NGOs, and community stakeholders. It provides easy access to the body of evidence, when drafting informed submissions to government bodies regarding service gaps and assists health service planners in developing evidence-based policy responses tailored to migrant populations.This database has undergone two rounds of user testing, engaging participants from diverse sectors, including academia, research governance, migrant-focused NGOs, policymakers, and postgraduate researchers. As a result, this iteration reflects their extensive feedback, ensuring its relevance, usability, and alignment with stakeholder needs.

The purpose of the collection of outpatient health statistics is to monitor, evaluate and plan curative and preventive health care at the primary and secondary level of health care system.

Data on outpatient statistics are an important source of information for population health monitoring indicators
and accessibility of outpatient health care activities in Slovenia. Health care providers collect data for each individual contact of the patients with the health service. It is reported by public and private healthcare providers.

Outpatient health statistics record contacts and services at general practicioners and specialist outpatient activities at the secondary level.

A collection of health related personnel systems used for production of health related statistics about members of the armed services. This covers, casualty, mental health, Aeromedical evacuations, Medical counter measures, Operational deployment, Medical discharges, Medical Downgradings, Deliberate Self Harm, FMED1022 Safety Information. These are currently held as Access databases on the Asante infrastructure. A project is currently ongoing to move these to the NEMESIS application servers. These systems have an anonomised service number to prevent individuals being easily identified from the data. From the current systems there is a large number of copies of each of the databases - taken at various points in time to answer Parliamentary Questions, these like the manpower files are retained indefinitely.

The OECD Health database is an online database with comparative information on health policies and health care systems across the OECD countries (OECD). The purpose of the database is to give a broad overview of health care in the member countries. It offers a series of reports, which contain diverse cross-national policy data, on issues like long-term care for older people, high-performing health systems and private health insurance. Here we focus on policy data.

description: The LIMS (laboratory information management system) database is a computerized record of specimens - from serum samples to carcasses - sent to the National Wildlife Health Center (NWHC) for processing and diagnostic workup. Data include history and recordkeeping information (identifier numbers, species, sex, submitter information, etc); types of tests run (virology, bacteriology, parasitology, chemistry, etc.) and some test results for heavy metals, particularly lead; and diagnostic results. The diagnostic coding system is based on SNOMED terminology, with certain modifications and additions to fit Center needs. SNOMED, the Systematized Nomenclature of Medicine, is a structured nomenclature and classification of the terminology used in human and veterinary medicine. Terms are assigned in any or all of the following six categories for each diagnosis: topography - detailed anatomic term for the site of interest; morphology - information on the pathogenic change or process associated with the topography; etiology - cause or causal agent of the disease or dysfunction; disease - disease, disease entity or syndrome; link - qualifier to link one diagnosis to another.; abstract: The LIMS (laboratory information management system) database is a computerized record of specimens - from serum samples to carcasses - sent to the National Wildlife Health Center (NWHC) for processing and diagnostic workup. Data include history and recordkeeping information (identifier numbers, species, sex, submitter information, etc); types of tests run (virology, bacteriology, parasitology, chemistry, etc.) and some test results for heavy metals, particularly lead; and diagnostic results. The diagnostic coding system is based on SNOMED terminology, with certain modifications and additions to fit Center needs. SNOMED, the Systematized Nomenclature of Medicine, is a structured nomenclature and classification of the terminology used in human and veterinary medicine. Terms are assigned in any or all of the following six categories for each diagnosis: topography - detailed anatomic term for the site of interest; morphology - information on the pathogenic change or process associated with the topography; etiology - cause or causal agent of the disease or dysfunction; disease - disease, disease entity or syndrome; link - qualifier to link one diagnosis to another.

description:

The National Patient Care Database (NPCD), located at the Austin Information Technology Center, is part of the National Medical Information Systems (NMIS). The NPCD collects integrated patient care data from all Veterans Health Information Systems and Technology Architecture (VistA) IT systems. Data recorded in the VistA Patient Care Encounter (PCE) package, which captures clinical data resulting from ambulatory care patient encounters is transmitted to the NPCD using the Ambulatory Care Reporting (ACR) Module of the VistA Patient Information Management System (PIMS) package. The Ambulatory Care Reporting Module provides necessary information on patient treatment, what services were rendered to patients, who provided the services, and whether services reported were synchronized with the VA medical center database. Directive 2006-026 (05/05/2006) required the inclusion to patient care data capture requirements the capture of inpatient encounters for patients seen in outpatient clinics and inpatient billable professional services.Additionally, NPCD includes VistA Spinal Cord Dysfunction (SCD) package and Primary Care Management Module (PCMM) data. The SCD central registry in NPCD is used to provide VA-wide review of patient demographics, clinical aspects of injury and disease, and resource utilization involved in providing care to patients. As of October 2010, data for the Spinal Cord Dysfunction is being maintained in the Spinal Cord Injury and Disorders Outcomes (SCIDO) database; current SCD data in NPCD is residual data only. The data load and extraction process for SCD data in NPCD will be discontinued in FY12. The PCMM data in NPCD includes primary care patient to provider assignments and provider utilization data.The NPCD is used by Veterans Health Administration (VHA) program offices for a wide variety of tasks to include research and budget allocation to medical centers.

The National Patient Care Database (NPCD), located at the Austin Information Technology Center, is part of the National Medical Information Systems (NMIS). The NPCD collects integrated patient care data from all Veterans Health Information Systems and Technology Architecture (VistA) IT systems. Data recorded in the VistA Patient Care Encounter (PCE) package, which captures clinical data resulting from ambulatory care patient encounters is transmitted to the NPCD using the Ambulatory Care Reporting (ACR) Module of the VistA Patient Information Management System (PIMS) package. The Ambulatory Care Reporting Module provides necessary information on patient treatment, what services were rendered to patients, who provided the services, and whether services reported were synchronized with the VA medical center database. Directive 2006-026 (05/05/2006) required the inclusion to patient care data capture requirements the capture of inpatient encounters for patients seen in outpatient clinics and inpatient billable professional services.Additionally, NPCD includes VistA Spinal Cord Dysfunction (SCD) package and Primary Care Management Module (PCMM) data. The SCD central registry in NPCD is used to provide VA-wide review of patient demographics, clinical aspects of injury and disease, and resource utilization involved in providing care to patients. As of October 2010, data for the Spinal Cord Dysfunction is being maintained in the Spinal Cord Injury and Disorders Outcomes (SCIDO) database; current SCD data in NPCD is residual data only. The data load and extraction process for SCD data in NPCD will be discontinued in FY12. The PCMM data in NPCD includes primary care patient to provider assignments and provider utilization data.The NPCD is used by Veterans Health Administration (VHA) program offices for a wide variety of tasks to include research and budget allocation to medical centers.

This project used national databases to describe the incidence and distribution of fatal and nonfatal police shootings and to develop an empirically based typology of legal intervention homicides. To accomplish this, the study team evaluated the comprehensiveness of the National Violent Death Reporting System (NVDRS) for fatal police shootings along with various open-source databases. The study team also explained the variation across states in fatal police shootings using a validated national database (Washington Post "Fatal Force Database") and is currently examining the variation in fatal police shooting across urban vs. rural areas.

The Public Health Research Database (PHRD) is a linked asset which currently includes Census 2011 data; Mortality Data; Hospital Episode Statistics (HES); GP Extraction Service (GPES) Data for Pandemic Planning and Research data. Researchers may apply for these datasets individually or any combination of the current 4 datasets.

The purpose of this dataset is to enable analysis of deaths involving COVID-19 by multiple factors such as ethnicity, religion, disability and known comorbidities as well as age, sex, socioeconomic and marital status at subnational levels. 2011 Census data for usual residents of England and Wales, who were not known to have died by 1 January 2020, linked to death registrations for deaths registered between 1 January 2020 and 8 March 2021 on NHS number. The data exclude individuals who entered the UK in the year before the Census took place (due to their high propensity to have left the UK prior to the study period), and those over 100 years of age at the time of the Census, even if their death was not linked. The dataset contains all individuals who died (any cause) during the study period, and a 5% simple random sample of those still alive at the end of the study period. For usual residents of England, the dataset also contains comorbidity flags derived from linked Hospital Episode Statistics data from April 2017 to December 2019 and GP Extraction Service Data from 2015-2019.

The table county_2018 is part of the dataset Social Determinants of Health Database (SDOH), available at https://redivis.com/datasets/js6v-91cgjnnm6. It contains 3224 rows across 238 variables.

The State Health Practice Database for Research (SHPDR) captures cross-sectional and longitudinal variation in states’ statutes and laws to enable researchers to more effectively perform clinically oriented health economics research, and investigate the diffusion of medical technology and other health services research outcomes of interest.

A database providing detailed mortality and population data to those interested in the history of human longevity. For each country, the database includes calculated death rates and life tables by age, time, and sex, along with all of the raw data (vital statistics, census counts, population estimates) used in computing these quantities. Data are presented in a variety of formats with regard to age groups and time periods. The main goal of the database is to document the longevity revolution of the modern era and to facilitate research into its causes and consequences. New data series is continually added to this collection. However, the database is limited by design to populations where death registration and census data are virtually complete, since this type of information is required for the uniform method used to reconstruct historical data series. As a result, the countries and areas included are relatively wealthy and for the most part highly industrialized. The database replaces an earlier NIA-funded project, known as the Berkeley Mortality Database. * Dates of Study: 1751-present * Study Features: Longitudinal, International * Sample Size: 37 countries or areas

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.

Statistics of the ORBDA source database content at the dataset and patient levels.