The American Health Values Survey was conducted by the National Opinion Research Center (NORC) at the University of Chicago in order to develop a typology of Americans based on their health values and beliefs. The survey examined values and beliefs related to health at both the individual as well as societal levels. The survey assessed the importance of health in day-to-day personal life (i.e. the amount of effort spent on disease prevention as well as appropriate seeking of medical care); equity, the value placed on the opportunity to succeed generally in life as well as on health equity; social solidarity, the importance of taking into account the needs of others as well as personal needs; health care disparities, views about how easy/hard it is for African Americans, Latinos and low-income Americans to get quality health care; and, the importance of the social determinants of health. In addition, the survey also explored views about how active government should be in health; collective efficacy, the ease of affecting positive community change by working with others; and health-related civic engagement e.g. the support of health charities and organizations working on health issues.

As of 2023, there were a total of *** health systems in the United States, according to the Agency for Healthcare Research and Quality (AHRQ). The AHRQ's definition of a health system is quite stringent and requires it to include at least one non-Federal acute care hospital, in total at least ** physicians, and at least ** primary care physicians. While the total number of health systems each year did not change much in the recorded time period, there were slight changes due to a number of reasons, such as mergers and acquisitions (M&A) and an increase in physicians (thus meeting requirements of a health system), among others.

This comprehensive dataset provides a detailed state-wise analysis of maternal health indicators in the United States from 2016 to 2021. It covers a broad spectrum of metrics such as maternal mortality rates, prenatal vitamin usage, insurance coverage during pregnancy, and numerous other critical health indicators. Each state is represented with data that includes both weighted percentages and confidence intervals, offering a nuanced view of maternal health across different regions. The dataset is an invaluable resource for understanding the dynamics of maternal health in the U.S., identifying trends, and pinpointing areas that require attention or intervention. It is particularly useful for healthcare researchers, policy analysts, and public health officials seeking to develop targeted strategies to improve maternal health outcomes and reduce disparities among different states and communities.

This is the complete dataset for the 500 Cities project 2016 release. This dataset includes 2013, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2013, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2009-2013, 2010-2014 estimates. More information about the methodology can be found at www.cdc.gov/500cities. Note: During the process of uploading the 2015 estimates, CDC found a data discrepancy in the published 500 Cities data for the 2014 city-level obesity crude prevalence estimates caused when reformatting the SAS data file to the open data format. . The small area estimation model and code were correct. This data discrepancy only affected the 2014 city-level obesity crude prevalence estimates on the Socrata open data file, the GIS-friendly data file, and the 500 Cities online application. The other obesity estimates (city-level age-adjusted and tract-level) and the Mapbooks were not affected. No other measures were affected. The correct estimates are update in this dataset on October 25, 2017.

This survey depicts the top areas where health IT is considered to be a very critical tool in the United States in 2016. According to the survey, ** percent of respondents stated that clinical integration is one area where health IT is considered to be a critical tool.

In 2023, over *** thousand healthcare data breaches were reported in the United States. The number of reported breaches in the U.S. healthcare system has gradually increased since 2016.

This dataset contains model-based county estimates for drug-poisoning mortality.

Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent).

Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2016 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published.

Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances.

Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates for 1999-2015 have been updated, and may differ slightly from previously published estimates. Differences are expected to be minimal, and may result from different county boundaries used in this release (see below) and from the inclusion of an additional year of data. Previously published estimates can be found here for comparison.(6) Estimates are unavailable for Broomfield County, Colorado, and Denali County, Alaska, before 2003 (7,8). Additionally, Clifton Forge County, Virginia only appears on the mortality files prior to 2003, while Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. These counties were therefore merged with adjacent counties where necessary to create a consistent set of geographic units across the time period. County boundaries are largely consistent with the vintage 2005-2007 bridged-race population file geographies, with the modifications noted previously (7,8).

REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm.

1. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html.

2. Rossen LM, Khan D, Warner M. Trends and geographic patterns in drug-poisoning death rates in the U.S., 1999–2009. Am J Prev Med 45(6):e19–25. 2013.

3. Rossen LM, Khan D, Warner M. Hot spots in mortality from drug poisoning in the United States, 2007–2009. Health Place 26:14–20. 2014.

4. Rossen LM, Khan D, Hamilton B, Warner M. Spatiotemporal variation in selected health outcomes from the National Vital Statistics System. Presented at: 2015 National Conference on Health Statistics, August 25, 2015, Bethesda, MD. Available from: http://www.cdc.gov/nchs/ppt/nchs2015/Rossen_Tuesday_WhiteOak_BB3.pdf.

5. Rossen LM, Bastian B, Warner M, and Khan D. NCHS – Drug Poisoning Mortality by County: United States, 1999-2015. Available from: https://data.cdc.gov/NCHS/NCHS-Drug-Poisoning-Mortality-by-County-United-Sta/pbkm-d27e.

6. National Center for Health Statistics. County geog

The National Hospital Ambulatory Medical Care Survey (NHAMCS), conducted by the National Center for Health Statistics (NCHS), collects annual data on visits to emergency departments to describe patterns of utilization and provision of ambulatory care delivery in the United States. Data are collected from nonfederal, general, and short-stay hospitals from all 50 U.S. states and the District of Columbia, and are used to develop nationally representative estimates. The data include counts and rates of emergency department visits from 2016-2022 for the 10 leading primary diagnoses and reasons for visit, stratified by selected patient and hospital characteristics. Rankings for the 10 leading categories were identified using weighted data from 2022 and were then assessed in prior years.

This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The data are not archived at ICPSR. Users should consult the data owners (via the Roper Center for Public Opinion Research) directly for details on obtaining the data. This collection includes variable-level metadata of the 2016 poll Workplace and Health, a survey from National Public Radio/Robert Wood Johnson Foundation/Harvard T.H. Chan School of Public Health conducted by Social Science Research Solutions (SSRS). Topics covered in this survey include:Employment statusHours worked in a weekWork locationsWorkplace and healthBenefits available to workersPaid vacation daysPaid sick daysJob satisfactionPhysical health and safety conditions at workplaceViolence at workplaceStress experienced at workWorking outside of regular work hoursWorking from homeWorking when caring for a sick family memberPaid leave to care for family memberSupport for health in the workplacePersonal health in the workplaceSmoke-free work environmentWorkplace wellness programsMethod of paymentJob securityPersonal financesHealth insurance coveragePolitical party preferenceThe data and documentation files for this survey are available through the Roper Center for Public Opinion Research [Roper #31099576]. Frequencies and summary statistics for the 188 variables from this survey are available through the ICPSR social science variable database and can be accessed from the Variables tab.

Conducted by the National Association of County and City Health Officials (NACCHO), the purpose of this survey of local health departments (LHDs) was to advance and support the development of a database for LHDs to describe and understand their structure, function, and capacities. A core set of questions was submitted to every LHD. In addition, some LHDs received one of two randomly assigned modules of supplemental questions. Data from the National Profile of Local Health Departments survey are used by: LHD staff members to compare their LHD or those within their states to others nationwide; Policymakers at the local, state, and federal levels to inform public health policy and support projects to improve local public health practice; Universities to educate future public health workforce members about LHDs; Researchers to address questions about public health practice; andNACCHO staff to develop programs and resources that meet the needs of LHDs and to advocate effectively for LHDs. Data included as part of this collection includes the Restricted-Use (Restricted-Use Level 2) data of the National Profile of Local Health Departments 2016 study. The dataset includes 1930 cases for 1116 variables.

United States US: Life Expectancy at Birth: Total data was reported at 78.690 Year in 2016. This stayed constant from the previous number of 78.690 Year for 2015. United States US: Life Expectancy at Birth: Total data is updated yearly, averaging 74.766 Year from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 78.841 Year in 2014 and a record low of 69.771 Year in 1960. United States US: Life Expectancy at Birth: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision, or derived from male and female life expectancy at birth from sources such as: (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

NOTE: On October 19, 2021, estimates for 2016–2018 by health insurance status were revised to correct errors. Changes are highlighted and tagged at https://www.cdc.gov/nchs/data/hus/2019/012-508.pdf

Data on health conditions among children under age 18, by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time.

SOURCE: NCHS, National Health Interview Survey, Family Core and Sample Child questionnaires. For more information on the National Health Interview Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

This national report summarizes key findings from the 2016 National Survey on Drug Use and Health (NSDUH) for indicators of substance use and mental health among people aged 12 years old or older in the civilian, noninstitutionalized population of the United States. Estimates include tobacco use, alcohol use, illicit drug use, opioid use, substance use disorders, major depressive episode, any mental illness, serious mental illness, suicide, co-occurring disorders, and receipt of treatment or services.

As of 2023, there were a total of *** health systems in the United States, according to the Agency for Healthcare Research and Quality (AHRQ). The large majority (** percent) were secular nonprofit health systems, while just **, or ***** percent, were for-profit or investor-owned health systems. During the recorded time period, the number of public/government health systems increased to ***, while the number of church-operated ones decreased to **. The AHRQ's definition of a health system is quite stringent and requires it to include at least one non-Federal acute care hospital, in total at least 50 physicians, and at least 10 primary care physicians.

This dataset provides data at the county level for the contiguous United States. It includes weekly United States Drought Monitor (USDM) data from 2000-2016 provided by the Cooperative Institute for Climate and Satellites - North Carolina. Please refer to the metadata attachment for more information.

These data are used by the CDC's National Environmental Public Health Tracking Network to generate drought measures. Learn more about drought on the Tracking Network's website: https://ephtracking.cdc.gov/showDroughtLanding.

By using these data, you signify your agreement to comply with the following requirements: 1. Use the data for statistical reporting and analysis only. 2. Do not attempt to learn the identity of any person included in the data and do not combine these data with other data for the purpose of matching records to identify individuals. 3. Do not disclose of or make use of the identity of any person or establishment discovered inadvertently and report the discovery to: trackingsupport@cdc.gov. 4. Do not imply or state, either in written or oral form, that interpretations based on the data are those of the original data sources and CDC unless the data user and data source are formally collaborating. 5. Acknowledge, in all reports or presentations based on these data, the original source of the data and CDC. 6. Suggested citation: Centers for Disease Control and Prevention. National Environmental Public Health Tracking Network. Web. Accessed: insert date. www.cdc.gov/ephtracking.

Problems or Questions? Email trackingsupport@cdc.gov.

The National Hospital Care Survey (NHCS) is designed to provide accurate and reliable health care statistics that answer key questions of interest to health care and public health professionals, researchers, and health care policy makers. This includes tracking the latest trends affecting hospitals and health care organizations and factors that influence the use of health care resources, the quality of health care, and disparities in health care services provided to population subgroups in the United States. NHCS collects data on patient care in hospital-based settings to describe patterns of health care delivery and utilization in the United States. Settings include inpatient, emergency (EDs), and outpatient departments (OPDs). The survey will provide hospital utilization statistics for the Nation. In addition, NHCS will also be able to monitor national trends in substance use-related ED visits including opioid visits.

United States US: Mortality Rate: Infant: per 1000 Live Births data was reported at 5.600 Ratio in 2016. This records a decrease from the previous number of 5.700 Ratio for 2015. United States US: Mortality Rate: Infant: per 1000 Live Births data is updated yearly, averaging 10.000 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 25.900 Ratio in 1960 and a record low of 5.600 Ratio in 2016. United States US: Mortality Rate: Infant: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted Average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

United States US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 11.800 NA in 2016. This records an increase from the previous number of 11.600 NA for 2015. United States US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 11.800 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 14.600 NA in 2000 and a record low of 11.600 NA in 2015. United States US: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

United States US: Cause of Death: by Injury: % of Total data was reported at 6.600 % in 2016. This records an increase from the previous number of 6.400 % for 2015. United States US: Cause of Death: by Injury: % of Total data is updated yearly, averaging 6.300 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 6.600 % in 2016 and a record low of 5.900 % in 2000. United States US: Cause of Death: by Injury: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.; ; Derived based on the data from WHO's Global Health Estimates.; Weighted average;

United States CES: AAE: Healthcare: Health Insurance data was reported at 3,160.000 USD in 2016. This records an increase from the previous number of 2,977.000 USD for 2015. United States CES: AAE: Healthcare: Health Insurance data is updated yearly, averaging 983.000 USD from Dec 1984 (Median) to 2016, with 33 observations. The data reached an all-time high of 3,160.000 USD in 2016 and a record low of 370.000 USD in 1984. United States CES: AAE: Healthcare: Health Insurance data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.H039: Consumer Expenditure Survey.