This dataset compiles heat flow and temperature gradient data from over 44,000 wells across the United States, along with more than 6,000 related geothermal exploration resources. Originally assembled prior to 2014 for the now-retired National Geothermal Data System (NGDS), the collection includes curated well data, scanned field notes, temperature-depth curves, publications, maps, and other supporting documents. SMU Geothermal Laboratory contributed two different nationwide heat flow databases to the project. One is based on equilibrium temperature measurements (over 14,000 sites) and the other is based on corrected bottom hole temperature (BHT) data from oil and gas industry wells (over 30,000 sites). In addition, scanned field notes and temperature-depth curves were associated with approximately 6,000 specific sites in the heat flow database. Records were corrected and overlapping sites in the equilibrium heat flow database were linked between the original SMU National database and the UND Global Heat Flow database. New or related sites, which were not previously published because they lacked full heat flow content, are now included as gradient only information along with their detailed temperature data to fill in data gaps. Finally, SMU submitted over 920 scanned publications, reports, and maps suitable for full text searching. The dataset is provided in two flat-structured zip archives: one containing the curated well data and another containing related resources. An Excel index file is provided for each archive, allowing filtering by well name, location, and description. Data files are labeled with state or institutional origin where available.

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

Discover the booming medical database software market! Learn about its $15 billion valuation in 2025, projected 12% CAGR to 2033, key drivers, regional trends, and leading companies. Explore EHR, HIM systems impacting healthcare.

The MN Public Health Data Access portal, maintained by the Minnesota Department of Health (MDH), provides data on over 20 health and environment topics. Data are accessible through charts, tables, and maps, and also may be downloaded from MDH's website. Users may use these data to inform state and local planning and policy, grant writing, research, and more.

This model combines stand density index (SDI), basal area loss, drought stress, and insect and disease surveys using an equal weight overlay. SDI determines the relative density of a stand, and was used in this model to identify where the density of small diameter trees is high. Basal area loss is defined as "the expectation that, without remediation, 25 percent or more of the standing live basal area of trees greater than 1 inch in diameter will die over the next 15 years (starting in 2005)." For the purposes of the New Mexico State Assessment, the basal area loss data layer represents areas of dense forest/woodlands with large diameter trees expected to experience mortality from insect and disease. SDI and basal area loss data layers were derived as a part of the 2006 National Insect and Disease Risk Map (NIDRM) and based on New Mexico's Forest Inventory Analysis Data from 1987-1999. Moisture stress depicts percent of normal precipitation for winter precipitation from 2006-2008 and was derived from PRISM precipitation data. Insect and disease outbreaks data was limited to past occurrence flyover data for western spruce budwrom and western tent catepillar and are based on USFS Forest Health Aerial Survey data from 1987-2008 .

The following datasets are based on the children and youth (under age 21) beneficiary population and consist of aggregate Mental Health Service data derived from Medi-Cal claims, encounter, and eligibility systems. These datasets were developed in accordance with California Welfare and Institutions Code (WIC) § 14707.5 (added as part of Assembly Bill 470 on 10/7/17). Please contact BHData@dhcs.ca.gov for any questions or to request previous years’ versions of these datasets. Note: The Performance Dashboard AB 470 Report Application Excel tool development has been discontinued. Please see the Behavioral Health reporting data hub at https://behavioralhealth-data.dhcs.ca.gov/ for access to dashboards utilizing these datasets and other behavioral health data.

Functional Annotation of Variants - Online Resource (FAVOR, https://favor.genohub.org) is a comprehensive whole-genome variant annotation database and a variant browser, providing hundreds of functional annotation scores from a variety of aspects of variant biological function. This FAVOR Essential Database is comprised of a collection of essential annotation scores for all possible SNVs (8,812,917,339) and observed indels (79,997,898) in Build GRCh38/hg38, including variant info, chromosome, position, reference allele, alternative allele, aPC-Conservation, aPC-Epigenetics, aPC-Epigenetics-Active, aPC-Epigenetics-Repressed, aPC-Epigenetics-Transcription, aPC-Local-Nucleotide-Diversity, aPC-Mappability, aPC-Mutation-Density, aPC-Protein-Function, aPC-Proximity-To-TSSTES, aPC-Transcription-Factor, CAGE promoter, CAGE, MetaSVM, rsID, FATHMM-XF, Gencode Comprehensive Category, Gencode Comprehensive Info, Gencode Comprehensive Exonic Category, Gencode Comprehensive Exonic Info, GeneHancer, LINSIGHT, CADD, rDHS. These annotation scores can be integrated into FAVORannotator (https://github.com/zhouhufeng/FAVORannotator) to create an annotated GDS (aGDS) file by storing the genotype data and their functional annotation data in an all-in-one file. The aGDS file can then facilitate a wide range of functionally-informed downstream analyses.

The ethics of health sector databases

The Heat Networks Planning Database (HNPD) provides a picture of both district and communal heat network deployment across the UK. It tracks the progress of projects through multiple stages including: inception; planning; construction; operation; and decommissioning. Data is sourced from reviewing planning applications and contacting developers, and is updated during the month following the end of each quarter. Previous data was uploaded under BEIS: Heat Networks Planning Database.

This dataset is comprised of a collection of example DMPs from a wide array of fields; obtained from a number of different sources outlined below. Data included/extracted from the examples include the discipline and field of study, author, institutional affiliation and funding information, location, date created, title, research and data-type, description of project, link to the DMP, and where possible external links to related publications or grant pages. This CSV document serves as the content for a McMaster Data Management Plan (DMP) Database as part of the Research Data Management (RDM) Services website, located at https://u.mcmaster.ca/dmps. Other universities and organizations are encouraged to link to the DMP Database or use this dataset as the content for their own DMP Database. This dataset will be updated regularly to include new additions and will be versioned as such. We are gathering submissions at https://u.mcmaster.ca/submit-a-dmp to continue to expand the collection.

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.

Under request of PLoS ONE journal and in order to contribute to the transparency and replicability of research, the authors of the study “A performance analysis of public expenditure on maternal health in Mexico”; made the data available. Any other use than exploring or replicating the results of the afore-mentioned paper_inc is not authorized and shall not be used without previous authorization of the researchers. If you are interested in analyzing this database for original research purpose please contact Leticia Avila-Burgos (PI of the original study- leticia.avila@insp.mx) or Gustavo Nigenda (corresponding author- gnigenda@outlook.com)

These data are modelled using the OMOP Common Data Model v5.3.Correlated Data SourceNG tube vocabulariesGeneration RulesThe patient’s age should be between 18 and 100 at the moment of the visit.Ethnicity data is using 2021 census data in England and Wales (Census in England and Wales 2021) .Gender is equally distributed between Male and Female (50% each).Every person in the record has a link in procedure_occurrence with the concept “Checking the position of nasogastric tube using X-ray”2% of person records have a link in procedure_occurrence with the concept of “Plain chest X-ray”60% of visit_occurrence has visit concept “Inpatient Visit”, while 40% have “Emergency Room Visit”NotesVersion 0Generated by man-made rule/story generatorStructural correct, all tables linked with the relationshipWe used national ethnicity data to generate a realistic distribution (see below)2011 Race Census figure in England and WalesEthnic Group : Population(%)Asian or Asian British: Bangladeshi - 1.1Asian or Asian British: Chinese - 0.7Asian or Asian British: Indian - 3.1Asian or Asian British: Pakistani - 2.7Asian or Asian British: any other Asian background -1.6Black or African or Caribbean or Black British: African - 2.5Black or African or Caribbean or Black British: Caribbean - 1Black or African or Caribbean or Black British: other Black or African or Caribbean background - 0.5Mixed multiple ethnic groups: White and Asian - 0.8Mixed multiple ethnic groups: White and Black African - 0.4Mixed multiple ethnic groups: White and Black Caribbean - 0.9Mixed multiple ethnic groups: any other Mixed or multiple ethnic background - 0.8White: English or Welsh or Scottish or Northern Irish or British - 74.4White: Irish - 0.9White: Gypsy or Irish Traveller - 0.1White: any other White background - 6.4Other ethnic group: any other ethnic group - 1.6Other ethnic group: Arab - 0.6

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

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.

This noise database was developed to provide researchers and other interested stakeholders with noise measurement results that the National Institute for Occupational Safety and Health (NIOSH) has collected during health hazard evaluation (HHE) surveys from 1996 through 2013. HHEs are requested by employees or their representatives, or employers, to help learn whether health hazards are present at their workplace. The scope of HHEs varies based on the requestors’ concerns and the NIOSH project officers’ professional judgment. Only noise measurement results are included in this database; however, many HHEs include evaluation of exposures other than noise. Individual HHE reports are published on the NIOSH website. When available, the database provides a direct link to the HHE report for each of the noise measurement results.

The noise database contains workplace noise measurement results from 77 HHE reports, including over 808 personal noise exposure measurements and 582 area noise measurements. It also includes the following information: U.S. state or territory; Occupational Safety and Health Administration (OSHA) region; National Occupational Research Agenda (NORA) sector; North American Industry Classification System (NAICS) code; facility description; type of dosimeter or sound level meter used; whether a hearing conservation program was in place; whether a hearing protection was used; whether octave band data was collected; job title; noise-generating activities; location of noise measurements; start and end date for site visit; type (full-shift, partial-shift, or task-based) and duration of noise measurement; type of noise (continuous, impulsive, or intermittent); exposure to ototoxic chemicals; and results in decibels A-weighted (dBA) and percent dose according to OSHA and NIOSH noise measurement criteria. This database is an ongoing project and will be updated at least yearly to add the most recent HHE noise measurement data.

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.

To evaluate effects of human influence on the health of Puget Sound's pelagic ecosystems, we propose a sampling program across multiple oceanographic basins measuring key attributes of the pelagic foodweb. We will quantify seasonal abundance and composition of pelagic biota from lower trophic levels (e.g., bacteria and phytoplankton) to middle trophic levels (e.g., zooplankton, small pelagic fi...

This dataset contains data for the Healthcare Payments Data (HPD) Snapshot visualization. The Enrollment data file contains counts of claims and encounter data collected for California's statewide HPD Program. It includes counts of enrollment records, service records from medical and pharmacy claims, and the number of individuals represented across these records. Aggregate counts are grouped by payer type (Commercial, Medi-Cal, or Medicare), product type, and year. The Medical data file contains counts of medical procedures from medical claims and encounter data in HPD. Procedures are categorized using claim line procedure codes and grouped by year, type of setting (e.g., outpatient, laboratory, ambulance), and payer type. The Pharmacy data file contains counts of drug prescriptions from pharmacy claims and encounter data in HPD. Prescriptions are categorized by name and drug class using the reported National Drug Code (NDC) and grouped by year, payer type, and whether the drug dispensed is branded or a generic.

This data set is a compilation of heat flow data of uncertain origin. References as cited in Global Heat Flow Database were incomplete and thus could not be verified. This data compilation contains: data of unknown origin, unpublished data, data which has no full reference information or data which were extracted from other database. The remaining short citation and its related problem are listed in columns 18 and 19.