Patient demographics and clinical data.

Demographics of the patient population.

Demographics of male patients and male control subjects.

Data for this publication are extracted each month as a snapshot in time from the Primary Care Registration database within the PDS (Personal Demographics Service) system. This release is an accurate snapshot as at 1 May 2025. GP Practice; Primary Care Network (PCN); Sub Integrated Care Board Locations (SICBL); Integrated Care Board (ICB) and NHS England Commissioning Region level data are released in single year of age (SYOA) and 5-year age bands, both of which finish at 95+, split by gender. In addition, organisational mapping data is available to derive PCN; SICBL; ICB and Commissioning Region associated with a GP practice and is updated each month to give relevant organisational mapping. Quarterly publications in January, April, July and October will include Lower Layer Super Output Area (LSOA) populations.

This dataset provides granular, patient-level diagnosis information for chronic conditions, including demographics, standardized condition codes, and diagnosis statuses. It is designed for healthcare analytics, enabling prevalence studies, trend analysis, and population health management. The schema supports interoperability and detailed stratification by demographic and clinical factors.

Demographics of patients (PA), carers (CA) and professionals (PR).

Demographics and geographic locations of eligible patients and enrolled participants. The patients were grouped based on disease state and age.

About this dataset

Context

The dataset tabulates the Keedysville population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Keedysville. The dataset can be utilized to understand the population distribution of Keedysville by age. For example, using this dataset, we can identify the largest age group in Keedysville.

Key observations

The largest age group in Keedysville, MD was for the group of age 45 to 49 years years with a population of 140 (11.26%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Keedysville, MD was the 85 years and over years with a population of 3 (0.24%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Keedysville is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Keedysville total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Keedysville Population by Age. You can refer the same here

US Healthcare Readmissions and Mortality

Evaluating Hospital Performance

By Health [source]

About this dataset

This dataset contains detailed information about 30-day readmission and mortality rates of U.S. hospitals. It is an essential tool for stakeholders aiming to identify opportunities for improving healthcare quality and performance across the country. Providers benefit by having access to comprehensive data regarding readmission, mortality rate, score, measure start/end dates, compared average to national as well as other pertinent metrics like zip codes, phone numbers and county names. Use this data set to conduct evaluations of how hospitals are meeting industry standards from a quality and outcomes perspective in order to make more informed decisions when designing patient care strategies and policies

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For more datasets, click here.

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How to use the dataset

This dataset provides data on 30-day readmission and mortality rates of U.S. hospitals, useful in understanding the quality of healthcare being provided. This data can provide insight into the effectiveness of treatments, patient care, and staff performance at different healthcare facilities throughout the country.

In order to use this dataset effectively, it is important to understand each column and how best to interpret them. The ‘Hospital Name’ column displays the name of the facility; ‘Address’ lists a street address for the hospital; ‘City’ indicates its geographic location; ‘State’ specifies a two-letter abbreviation for that state; ‘ZIP Code’ provides each facility's 5 digit zip code address; 'County Name' specifies what county that particular hospital resides in; 'Phone number' lists a phone contact for any given facility ;'Measure Name' identifies which measure is being recorded (for instance: Elective Delivery Before 39 Weeks); 'Score' value reflects an average score based on patient feedback surveys taken over time frame listed under ' Measure Start Date.' Then there are also columns tracking both lower estimates ('Lower Estimate') as well as higher estimates ('Higher Estimate'); these create variability that can be tracked by researchers seeking further answers or formulating future studies on this topic or field.; Lastly there is one more measure oissociated with this set: ' Footnote,' which may highlight any addional important details pertinent to analysis such as numbers outlying National averages etc..

This data set can be used by hospitals, research facilities and other interested parties in providing inciteful information when making decisions about patient care standards throughout America . It can help find patterns about readmitis/mortality along county lines or answer questions about preformance fluctuations between different hospital locations over an extended amount of time. So if you are ever curious about 30 days readmitted within US Hospitals don't hesitate to dive into this insightful dataset!

Research Ideas

• Comparing hospitals on a regional or national basis to measure the quality of care provided for readmission and mortality rates.
• Analyzing the effects of technological advancements such as telemedicine, virtual visits, and AI on readmission and mortality rates at different hospitals.
• Using measures such as Lower Estimate Higher Estimate scores to identify systematic problems in readmissions or mortality rate management at hospitals and informing public health care policy

Acknowledgements

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

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Readmissions_and_Deaths_-_Hospital.csv | Column name | Description | |:-------------------------|:---------------------------------------------------------------------------------------------------| | Hospital Name ...

Annual Resident Population Estimates by Age Group, Sex, Race, and Hispanic Origin: April 1, 2010 to July 1, 2018 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through June. // Note: 'In combination' means in combination with one or more other races. The sum of the five race-in-combination groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. Responses of 'Some Other Race' from the 2010 Census are modified. This results in differences between the population for specific race categories shown for the 2010 Census population in this file versus those in the original 2010 Census data. For more information, see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/modified-race-summary-file-method/mrsf2010.pdf. // The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // For detailed information about the methods used to create the population estimates, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2017) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/programs-surveys/popest.html.

Patient demographics and baseline characteristics.

Demographics and disposition of study patients following final screening.

Comparison of demographics and disease characteristics between different health literacy profiles (n = 243).

This dataset consists of unstructured text reviews, categorical ratings, and demographics from patients and caregivers of patients on various psychiatric drugs. The current version of the dataset contains over 61,000 reviews for hundreds of medications used to treat psychiatric disorders. The list of medications to include was compiled using the search by illness function for WebMD's drug database, accessible at https://www.webmd.com/drugs/2/conditions/index. The conditions included are "depression," "anxiety", "anxiety with depression," "bipolar disorder," and "schizophrenia." Future updates will expand the dataset to include reviews added to WebMD since the last release of the dataset.

About this dataset

Context

The dataset tabulates the Santa Clara population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Santa Clara. The dataset can be utilized to understand the population distribution of Santa Clara by age. For example, using this dataset, we can identify the largest age group in Santa Clara.

Key observations

The largest age group in Santa Clara, CA was for the group of age 30 to 34 years years with a population of 15,852 (12.27%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Santa Clara, CA was the 80 to 84 years years with a population of 1,672 (1.29%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Santa Clara is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Santa Clara total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Santa Clara Population by Age. You can refer the same here

Medicare provides access to medical and hospital services for all Australian residents and certain categories of visitors to Australia. The Medicare Benefits Schedule (MBS) lists services that are subsidised by the Australian Government under Medicare. These reports provide patient age range and gender, number of services and total benefit amount per State/ Territory on Items in the MBS Schedule. An Item is a number that references a Medicare service. Item numbers are subject to change. Data is provided in the following formats: Excel/ xlxs: the human readable data for the current year is provided in individual excel files according to the relevant quarter. Historical data (1993-2015) may be found in the excel zipped file. CSV: the machine readable data for the current year is provided in individual csv files according to the relevant quarter. Historical data (1993-2015) may be found in the csv zipped file. Additional Medicare statistics may be found on the Department of Human Services website. Disclaimer: The information and data contained in the reports and tables have been provided by Medicare Australia for general information purposes only. While Medicare Australia takes care in the compilation and provision of the information and data, it does not assume or accept liability for the accuracy, quality, suitability and currency of the information or data, or for any reliance on the information and data. Medicare Australia recommends that users exercise their own care, skill and diligence with respect to the use and interpretation of the information and data.

This file contains raw data of all laboratory measurements presented in the paper. In addition, the file contains raw demographic data of the patients as summarized in the paper in Table 1.

About this dataset

Context

The dataset tabulates the Azusa population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Azusa. The dataset can be utilized to understand the population distribution of Azusa by age. For example, using this dataset, we can identify the largest age group in Azusa.

Key observations

The largest age group in Azusa, CA was for the group of age 20 to 24 years years with a population of 4,973 (10.08%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Azusa, CA was the 85 years and over years with a population of 407 (0.83%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Azusa is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Azusa total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Azusa Population by Age. You can refer the same here

Patient clinical demographics.

About this dataset

Context

The dataset tabulates the Heath population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Heath. The dataset can be utilized to understand the population distribution of Heath by age. For example, using this dataset, we can identify the largest age group in Heath.

Key observations

The largest age group in Heath, AL was for the group of age 70 to 74 years years with a population of 83 (34.87%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Heath, AL was the 85 years and over years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Heath is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Heath total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Heath Population by Age. You can refer the same here