US Counties Health Ranks Data Information And Top Performers 2016-2018

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The dataset contains additional information related to the data sources and years used to calculate the US counties ranks and data for the top performers and US overall values. The dataset comes in addition to the main dataset, US Counties Ranks By Health Outcomes And Determinants.

Complexity

Using America’s Health Rankings, University of Wisconsin Population Health Institute is providing every year since 2010, for nearly every county in US health ranking data.

The counties health rankings are based on counties and county equivalents (ranked places). Any entity that has its own FIPS county code was included in the rankings. Are included only counties and county equivalents within a state. The major goal of the Rankings is to raise awareness about the many factors that influence health and that health varies from place to place. Counties in each of the 50 states are ranked according to summaries of a variety of health measures. Those having high ranks, e.g. 1 or 2, are considered to be the “healthiest.” Counties are ranked relative to the health of other counties in the same state. Most of the data used were public data available at no charge. Measures based on vital statistics data, sexually transmitted disease rates and Behavioral Risk Factor Surveillance System (BRFSS) survey data were calculated for this project by staff at the National Center for Health Statistics and other units of the Centers for Disease Control and Prevention (CDC). The healthcare quality measures included were calculated by the authors of the Dartmouth Atlas of Healthcare, using Medicare claims data. In many ranked counties, some individual measures do not have a large enough sample size to report data for that measure. In these counties, the state average was assigned for any missing measure in order to calculate a rank for that category.

Top performers refer to the value for which only 10% of counties in the country are doing better, i.e., the 90th percentile or 10th percentile, depending on whether the measure is framed positively (e.g., high school graduation) or negatively (e.g., adult smoking).

Date Created

2010

Last Modified

2018

Version

2018

Update Frequency

Annual

Temporal Coverage

2007-2017

Spatial Coverage

United States

Source

John Snow Labs => University of Wisconsin Population Health Institute

Source License URL

John Snow Labs Standard License

Source License Requirements

Publicly available and free for research application but citation is required. Permission asked for commercial uses

Source Citation

University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2017.

Keywords

County Health Rankings, Determinants Of Health, Health Outcomes Measures, County Health Indicators, Ranking Data Sources, Ranking Data Years, County Health Indicators Top Performers, County Health Indicators Weights, Determinants Of Health Weights, Health Indicators Categories

Other Titles

US Counties Health Rankings Indicators Description And Data Sources, US Counties Health Rankings Additional Information And Top Performers

Name Description Type Constraints
County_Health_Rankings_Project_YearThe year when the County Health Rankings project results were released, including the ranking measures data and the additional measures datadaterequired : 1
Measure_TypeSpecifies whether the measure is a raking measure or an additional measurestringrequired : 1
Indicator_Name_Used_In_HeaderThe name used for the indicators in the main dataset US Counties Ranks By Health Outcomes And Determinantsstringrequired : 1
Indicator_CategoryOne of the two main categories of indicatorsstringenum : Array required : 1
Determinants_Of_Health_TypeOne of the four main types of determinants of healthstringenum : Array
Indicator_TypeThe type of indicator corresponding to health outcomes (population health status) or determinants of healthstringrequired : 1
IndicatorThe original name used for indicatorstringrequired : 1
Indicator_DescriptionThe detailed description provided for the indicatorsstring-
Indicator_Weight_PercentThe weight used for the calculation of the overall values, at health outcomes or determinants of health levelnumberlevel : Ratio
Data_SourcesThe source or sources corresponding to the original data usedstringrequired : 1
Data_YearsThe year or years corresponding to the original data usedstringrequired : 1
Top_Performers_ValueThe value for which only 10% of counties in the country are doing betternumberlevel : Ratio
US_Overall_ValueThe value calculated at US levelnumberlevel : Ratio
Value_TypeSpecifies the original form of top performers and US overall valuesstring-
County_Health_Rankings_Project_YearMeasure_TypeIndicator_Name_Used_In_HeaderIndicator_CategoryDeterminants_Of_Health_TypeIndicator_TypeIndicatorIndicator_DescriptionIndicator_Weight_PercentData_SourcesData_YearsTop_Performers_ValueUS_Overall_ValueValue_Type
2016Additional measurePopulationDemographicsTotal populationPopulationCensus Population Estimates2014
2017Additional measurePopulationDemographicsTotal populationPopulationCensus Population Estimates2015
2018Additional measurePopulationDemographicsTotal populationPopulationCensus Population Estimates2016
2016Additional measureChild_DeathsHealth StatusLength of lifeChild mortalityCDC WONDER mortality data2010-2013
2017Additional measureChild_DeathsHealth StatusLength of lifeChild mortalityCDC WONDER mortality data2007-2013
2018Additional measureChild_DeathsHealth StatusLength of lifeChild mortalityCDC WONDER mortality data2013-2016
2016Additional measureInfant_Mortality_RateHealth StatusLength of lifeInfant mortalityHealth Indicators Warehouse2006-2012
2016Additional measurePercent_Of_AsianDemographicsPopulation by race/ethnicityPercent AsianCensus Population Estimates2014
2017Additional measureInfant_Mortality_RateHealth StatusLength of lifeInfant mortalityHealth Indicators Warehouse2012-2015
2017Additional measurePercent_Of_AsianDemographicsPopulation by race/ethnicityPercent AsianCensus Population Estimates2015