The Office for Health Improvement and Disparities (OHID) has published the Public Health Outcomes Framework (PHOF) quarterly data update for March 2023.

The data is presented in an interactive tool that allows users to view it in a user-friendly format. The data tool also provides links to further supporting information, to aid understanding of public health in a local population.

The March release is in addition to the quarterly schedule for the PHOF (May, August, November and February) to incorporate new population estimates from the 2021 Census.

This update includes new data for 20 indicators.

• 1 indicator from the overarching domain, life expectancy at birth and at 65
• 7 indicators from the health improvement domain including hospital admissions related to children and older people, baby’s first feed breastmilk and percentage reporting a long term musculoskeletal (MSK) problem
• 12 indicators from the healthcare and premature mortality indicators including under 75 mortality from various causes and hip fractures

The trend data have been removed for 17 of these indicators as revised mid-year population estimates for 2012 to 2020, based on the 2021 Census, are not yet available.

See the indicator updates document on this page for full details of what’s in this update.

View previous Public Health Outcomes Framework data tool updates.

Public Health Indicators in Chicago

Natality, Mortality, Infectious Disease, Lead Poisoning and Economic Status

By City of Chicago [source]

About this dataset

This public health dataset contains a comprehensive selection of indicators related to natality, mortality, infectious disease, lead poisoning, and economic status from Chicago community areas. It is an invaluable resource for those interested in understanding the current state of public health within each area in order to identify any deficiencies or areas of improvement needed.

The data includes 27 indicators such as birth and death rates, prenatal care beginning in first trimester percentages, preterm birth rates, breast cancer incidences per hundred thousand female population, all-sites cancer rates per hundred thousand population and more. For each indicator provided it details the geographical region so that analyses can be made regarding trends on a local level. Furthermore this dataset allows various stakeholders to measure performance along these indicators or even compare different community areas side-by-side.

This dataset provides a valuable tool for those striving toward better public health outcomes for the citizens of Chicago's communities by allowing greater insight into trends specific to geographic regions that could potentially lead to further research and implementation practices based on empirical evidence gathered from this comprehensive yet digestible selection of indicators

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How to use the dataset

In order to use this dataset effectively to assess the public health of a given area or areas in the city: - Understand which data is available: The list of data included in this dataset can be found above. It is important to know all that are included as well as their definitions so that accurate conclusions can be made when utilizing the data for research or analysis. - Identify areas of interest: Once you are familiar with what type of data is present it can help to identify which community areas you would like to study more closely or compare with one another. - Choose your variables: Once you have identified your areas it will be helpful to decide which variables are most relevant for your studies and research specific questions regarding these variables based on what you are trying to learn from this data set.
- Analyze the Data : Once your variables have been selected and clarified take right into analyzing the corresponding values across different community areas using statistical tests such as t-tests or correlations etc.. This will help answer questions like “Are there significant differences between two outputs?” allowing you to compare how different Chicago Community Areas stack up against each other with regards to public health statistics tracked by this dataset!

Research Ideas

• Creating interactive maps that show data on public health indicators by Chicago community area to allow users to explore the data more easily.
• Designing a machine learning model to predict future variations in public health indicators by Chicago community area such as birth rate, preterm births, and childhood lead poisoning levels.
• Developing an app that enables users to search for public health information in their own community areas and compare with other areas within the city or across different cities in the US

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: public-health-statistics-selected-public-health-indicators-by-chicago-community-area-1.csv | Column name | Description | |:-----------------------------------------------|:--------------------------------------------------------------------------------------------------| | Community Area | Unique identifier for each community area in Chicago. (Integer) | | Community Area Name | Name of the community area in Chicago. (String) | | Birth Rate | Number of live births per 1,000 population. (Float) | | General Fertility Rate | Number of live births per 1,000 women aged 15-44. (Float) ...

Homeland Infrastructure Foundation-Level Data (HIFLD) geospatial data sets containing information on Public Health Departments.

Population Health (BRFSS: HRQOL)

Examining Trends, Disparities and Determinants of Health in the US Population

By Health [source]

About this dataset

The Behavioral Risk Factor Surveillance System (BRFSS) offers an expansive collection of data on the health-related quality of life (HRQOL) from 1993 to 2010. Over this time period, the Health-Related Quality of Life dataset consists of a comprehensive survey reflecting the health and well-being of non-institutionalized US adults aged 18 years or older. The data collected can help track and identify unmet population health needs, recognize trends, identify disparities in healthcare, determine determinants of public health, inform decision making and policy development, as well as evaluate programs within public healthcare services.

The HRQOL surveillance system has developed a compact set of HRQOL measures such as a summary measure indicating unhealthy days which have been validated for population health surveillance purposes and have been widely implemented in practice since 1993. Within this study's dataset you will be able to access information such as year recorded, location abbreviations & descriptions, category & topic overviews, questions asked in surveys and much more detailed information including types & units regarding data values retrieved from respondents along with their sample sizes & geographical locations involved!

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How to use the dataset

This dataset tracks the Health-Related Quality of Life (HRQOL) from 1993 to 2010 using data from the Behavioral Risk Factor Surveillance System (BRFSS). This dataset includes information on the year, location abbreviation, location description, type and unit of data value, sample size, category and topic of survey questions.

Using this dataset on BRFSS: HRQOL data between 1993-2010 will allow for a variety of analyses related to population health needs. The compact set of HRQOL measures can be used to identify trends in population health needs as well as determine disparities among various locations. Additionally, responses to survey questions can be used to inform decision making and program and policy development in public health initiatives.

Research Ideas

• Analyzing trends in HRQOL over the years by location to identify disparities in health outcomes between different populations and develop targeted policy interventions.
• Developing new models for predicting HRQOL indicators at a regional level, and using this information to inform medical practice and public health implementation efforts.
• Using the data to understand differences between states in terms of their HRQOL scores and establish best practices for healthcare provision based on that understanding, including areas such as access to care, preventative care services availability, etc

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: rows.csv | Column name | Description | |:-------------------------------|:----------------------------------------------------------| | Year | Year of survey. (Integer) | | LocationAbbr | Abbreviation of location. (String) | | LocationDesc | Description of location. (String) | | Category | Category of survey. (String) | | Topic | Topic of survey. (String) | | Question | Question asked in survey. (String) | | DataSource | Source of data. (String) | | Data_Value_Unit | Unit of data value. (String) | | Data_Value_Type | Type of data value. (String) | | Data_Value_Footnote_Symbol | Footnote symbol for data value. (String) | | Data_Value_Std_Err | Standard error of the data value. (Float) | | Sample_Size | Sample size used in sample. (Integer) | | Break_Out | Break out categories used. (String) | | Break_Out_Category | Type break out assessed. (String) | | **GeoLocation*...

This Public Health Portfolio (Directly Funded Research - Programme and Training Awards) dataset contains NIHR directly funded research awards where the funding is allocated to an award holder or host organisation to carry out a specific piece of research or complete a training award. The NIHR also invests significantly in centres of excellence, collaborations, services and facilities to support research in England. Collectively these form NIHR infrastructure support. NIHR infrastructure supported projects are available in the Public Health Portfolio (Infrastructure Support) dataset which you can find here.NIHR directly funded research awards (Programmes and Training Awards) that were funded between January 2006 and the present extraction date are eligible for inclusion in this dataset. An agreed inclusion/exclusion criteria is used to categorise awards as public health awards (see below). Following inclusion in the dataset, public health awards are second level coded to one of the four Public Health Outcomes Framework domains. These domains are: (1) wider determinants (2) health improvement (3) health protection (4) healthcare and premature mortality.More information on the Public Health Outcomes Framework domains can be found here.This dataset is updated quarterly to include new NIHR awards categorised as public health awards. Please note that for those Public Health Research Programme projects showing an Award Budget of £0.00, the project is undertaken by an on-call team for example, PHIRST, Public Health Review Team, or Knowledge Mobilisation Team, as part of an ongoing programme of work.Inclusion CriteriaThe NIHR Public Health Overview project team worked with colleagues across NIHR public health research to define the inclusion criteria for NIHR public health research. NIHR directly funded research awards are categorised as public health if they are determined to be ‘investigations of interventions in, or studies of, populations that are anticipated to have an effect on health or on health inequity at a population level.’ This definition of public health is intentionally broad to capture the wide range of NIHR public health research across prevention, health improvement, health protection, and healthcare services (both within and outside of NHS settings). This dataset does not reflect the NIHR’s total investment in public health research. The intention is to showcase a subset of the wider NIHR public health portfolio. This dataset includes NIHR directly funded research awards categorised as public health awards. This dataset does not include public health awards or projects funded by any of the three NIHR Research Schools or NIHR Health Protection Research Units.DisclaimersUsers of this dataset should acknowledge the broad definition of public health that has been used to develop the inclusion criteria for this dataset. Please note that this dataset is currently subject to a limited data quality review. We are working to improve our data collection methodologies. Please also note that some awards may also appear in other NIHR curated datasets. Further InformationFurther information on the individual awards shown in the dataset can be found on the NIHR’s Funding & Awards website here. Further information on individual NIHR Research Programme’s decision making processes for funding health and social care research can be found here.Further information on NIHR’s investment in public health research can be found as follows:The NIHR is one of the main funders of public health research in the UK. Public health research falls within the remit of a range of NIHR Directly Funded Research (Programmes and Training Awards), and NIHR Infrastructure Support. NIHR School for Public Health here.NIHR Public Health Policy Research Unit here. NIHR Health Protection Research Units here.NIHR Public Health Research Programme Health Determinants Research Collaborations (HDRC) here.NIHR Public Health Research Programme Public Health Intervention Responsive Studies Teams (PHIRST) here.

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.

In the United States in 2022, the majority of diagnostic vendors only shared data to health information exchanges (HIE) on a regional or state level. While around ** percent said they contributed data to a private HIE.

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 Public Health Survey, a survey by Harvard School of Public Health/Robert Wood Johnson Foundation conducted by ICR Survey Research Group. Topics covered in this survey include: Goals of health professionals The data and documentation files for this survey are available through the Roper Center for Public Opinion Research [Roper #31092258]. Frequencies and summary statistics for the 110 variables from this survey are available through the ICPSR social science variable database and can be accessed from the Variables tab.

Public Health England (PHE) has published the Public Health Outcomes Framework (PHOF) quarterly data update for November 2020.

The data are presented in an interactive tool that allows users to view them in a user-friendly format. The data tool also provides links to further supporting information, to aid understanding of public health in a local population.

This update contains:

• more recent data for 42 indicators
• 5 indicators with a revised definition

See link to indicators updated document for full details of what’s in this update.

View previous Public Health Outcomes Framework data tool updates.

These indicators are presented by Public Health — Seattle & King County, in conjunction with the King County Hospitals for a Healthier Community (HHC). The data offer a comprehensive overview of demographics, health, and health behaviors among King County residents.

Users can search by key word or topic area to filter the table of contents displayed below. After clicking on an indicator, a summary tab will open and users can click on additional tabs to explore data analyzed by demographic characteristics, see how rates have changed over time, and view data for cities/neighborhoods. Most indicators are interactive and users can hover over maps or charts to find more information.

The data presented on this website may be reproduced without permission. Please use the following citation when reproducing: "Retrieved (date) from Public Health – Seattle & King County, Community Health Indicators. www.kingcounty.gov/chi"

Health indicators are quantifiable characteristics of a population which researchers use as supporting evidence for describing the health of a population. The researchers use a survey methodology to gather information about certain people, use statistics in an attempt to generalize the information collected to the entire population, then use the statistical analysis to make a statement about the health of a population. Health indicators are often used by governments to guide health care policy.

The following datasets are based on the adult (age 21 and over) beneficiary population and consist of aggregate MHS 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.

The basic purpose of the Health Interview Survey is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive. There are five types of records in this core survey, each in a separate data file. The variables in the Household File (Part 1) include type of living quarters, size of family, number of families in household, and geographic region. The variables in the Person File (Part 2) include sex, age, race, marital status, veteran status, education, income, industry and occupation codes, and limits on activity. These variables are found in the Condition, Doctor Visit, and Hospital Episode Files as well. The Person File also supplies data on height, weight, bed days, doctor visits, hospital stays, years at residence, and region variables. The Condition (Part 3), Doctor Visit (Part 4), and Hospital Episode (Part 5) Files contain information on each reported condition, two-week doctor visit, or hospitalization (twelve-month recall), respectively. A sixth, seventh, eighth, and ninth file have been added, along with the five core files. The Alcohol/Health Practices Supplement File (Part 6) includes information on diet, smoking and drinking habits, and health problems. The Bed Days and Dental Care Supplement File (Part 7) contains information on the number of bed days, the number of and reason for dental visits, treatment(s) received, type of dentist seen, and travel time for visit. The Doctor Services Supplement File (Part 8) supplies data on visits to doctors or other health professionals, reasons for visits, health conditions, and operations performed. The Health Insurance Supplement File (Part 9) documents basic demographic information along with medical coverage and health insurance plans, as well as differentiates between hospital, doctor visit, and surgical insurance coverage.

Partners in Information Access for the Public Health Workforce (PHPartners) is a web portal and current awareness service of information for the public health workforce. Alerts the communities to meetings, webinars, new web-born reports (analyses, statistics), datasets, and general news. Currently contains over 4,000 items. This resource was retired on September 14, 2021 and is no longer updated.

The Centers for Medicare & Medicaid Services (CMS) EHR Incentive Program provides incentive payments for eligible hospitals to adopt and meaningfully use certified health IT. Among the requirements to receive an incentive payment, participating hospitals must report on public health measures. These measures include the electronic reporting of data regarding: immunizations, emergency department visits (syndromic surveillance), reportable infectious disease laboratory results, and electronic patient data to specialized registries, like cancert. As of 2015, stage 2 of the EHR Incentive Program requires hospitals to report on three public health measures, when applicable, and modified stage 2 of the program requires hospitals to report on two of the three measures. This dataset includes the percentage of hospitals who reported on these measures in program years, 2013, 2014 and 2015.

This data is compiled by the Cook County Department of Public Health using data from the Illinois Department of Public Health Vital Statistics. It includes the annual number of deaths, crude and age-adjusted death rates by selected causes of death. Further analysis is available by age group, race/ethnicity, gender and decedent's place of residence in suburban Cook County at the time of their death. Note: Counts suppressed for events between 1 and 4, Rates not calculated for events less than 20

U.S. Mortality and Health Indicators

Impact of Risk Factors on Population Health Outcomes

By Data Society [source]

About this dataset

This dataset provides county-level mortality and health indicators that are useful for measuring the impact of health policies in the United States. It includes data elements and values from over a dozen categories, including Demographics, Leading Causes of Death, Summary Measures of Health, Measures of Birth and Death, Relative Health Importance, Vulnerable Populations and Environmental Health, Preventive Services Use, Risk Factors and Access to Care. Additionally, this dataset offers Healthy People 2010 Targets and US Percentages or Rates for easy comparison across states. With comprehensive information for each county in each indicator domain available here at your fingertips could help you get insight into American population health from the local level like never before. Discover trends on disease outbreaks or immunizations that are unprecedentedly localized with insights from this dataset!

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How to use the dataset

This dataset contains various data elements related to the mortality and health of the US population at various levels such as county, state, etc. This dataset is an ideal source of information for researchers and policy makers who are interested in exploring patterns in the mortality and health of US citizens.

In order to use this dataset effectively, it is important to understand the different indicators included as well as how to interpret these indicators. In this guide we will look at each indicator domain separately so that users can easily identify which relevant data elements they need for their analysis.

Demographics: The Demographics indicator domain includes data elements related to demographic characteristics such as age composition, gender composition etc. These indicators can be used to explore trends across different parts of the country or identify disparities among populations.

Leading Causes of Death: The Leading Causes of Death indicator domain contains information on fatalities by cause over a set period of time -- either two years or five years depending on availability -- so that researchers can identify causes that pose major threats to public health overall or in more specific regions such as certain counties. It is important to note that these largely report figures based on death certificates which may not always tell an exact story due to reporting inaccuracies caused by both individual factors and registration biases across counties/states over time.

 **Summary Measures Of Health**: The Summary Measures Of Health Indicator Domain includes measures commonly used for gauging overall population health such as birth rates and death rates but also key quality-of-life considerations like prevalence rate physical activity rate . These can be used together with other data sources (such as income info) when analyzing population health outcomes from a broader perspective than individual diseases or conditions would allow for . 

 **Measures Of Birth And Death**: This category provides further insight into the important summary level figures mentioned earlier by providing observations about frequency , timing , type etc where available . Additionally , it offers valuable insights about trends related specifically (among others ) out - migration /in - migration mortality ratio changes/births outside hospitals marriage age / labor force participation trends etc – all essential ingredients when trying solve complex issues related improving public one's life expectancy positively  

 **Relative Health Importance & Vulnerable Populations And Environment Capacity :** This section covers two closely intertwined fields revealing how they interact – socioeconomic status disparities & environment quality – around boundaries & neighborhoods influencing risks factors (not only related medical matters ) aspects such disabilities insurance coverage alcohol use & smoking habits road fatalities veh

Research Ideas

• Using the Health Status Indicators as input features, machine learning models can be built to predict county-level mortality rate, which can then be used as an important indicator for health and medical resource allocation.
• The data can also be used to analyze the social determinants of health in different counties by combining with socioeconomic indicators such as poverty, population density and educational attainment levels.
• Additionally, the dataset could help assess th...

PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC). Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES provides health data for small areas across the country. This allows local health departments and jurisdictions, regardless of population size and rurality, to better understand the burden and geographic distribution of health measures in their areas and assist them in planning public health interventions. PLACES provides model-based, population-level analysis and community estimates of health measures to all counties, places (incorporated and census designated places), census tracts, and ZIP Code Tabulation Areas (ZCTAs) across the United States.

PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC). Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES provides health data for small areas across the country. This allows local health departments and jurisdictions, regardless of population size and rurality, to better understand the burden and geographic distribution of health measures in their areas and assist them in planning public health interventions. PLACES provides model-based, population-level analysis and community estimates of health measures to all counties, places (incorporated and census designated places), census tracts, and ZIP Code Tabulation Areas (ZCTAs) across the United States.