Medical Service Study Areas (MSSAs)As defined by California's Office of Statewide Health Planning and Development (OSHPD) in 2013, "MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data" (Source). Each census tract in CA is assigned to a given MSSA. The most recent MSSA dataset (2014) was used. Spatial data are available via OSHPD at the California Open Data Portal. This information may be useful in studying health equity.Definitions:Race/Ethnicity: Race/ethnicity is categorized as: All races/ethnicities, Non-Hispanic (NH) White, NH Black, Asian/Pacific Islander, or Hispanic. "All races" includes all of the above, as well as other and unknown race/ethnicity and American Indian/Alaska Native. The latter two groups are not reported separately due to small numbers for many cancer sites.Racial/Ethnic Composition: Distribution of residents' race/ethnicity (e.g., % Hispanic, % non-Hispanic White, % non-Hispanic Black, % non-Hispanic Asian/Pacific Islander). (Source: US Census, 2010.)Rural: Percent of residents who reside in blocks that are designated as rural. (Source: US Census, 2010.)Foreign Born: Percent of residents who were born outside the United States. (Source: American Community Survey, 2008-2012.)Socioeconomic Status (Neighborhood Level): A composite measure of seven indicator variables created by principal component analysis; indicators include: education, blue-collar job, unemployment, household income, poverty, rent, and house value. Quintiles based on state distribution, with quintile 1 being the lowest SES and 5 being the highest. (Source: American Community Survey, 2008-2012.)Spatial extent: CaliforniaSpatial Unit: MSSACreated: n/aUpdated: n/aSource: California Health MapsContact Email: gbacr@ucsf.eduSource Link: https://www.californiahealthmaps.org/?areatype=mssa&address=&sex=Both&site=AllSite&race=&year=05yr&overlays=none&choropleth=Obesity

Department of State Hospitals Patient Population Demographic (Fiscal Effective Dates: 2010-2020)

The dataset contains information on California’s Medical Service Study Areas (MSSA), at the census tract level for 2000. MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data. MSSA areas are a geographic analysis unit defined by the California Office of Statewide Health Planning and Development. MSSA are a good foundation for needs assessment analysis, healthcare planning, and healthcare policy development.

The dataset contains information on California’s Medical Service Study Areas (MSSA). MSSAs are sub-city and sub-county geographical units used to organize and display population, demographic and physician data for 2000. Medical Service Study Areas are a geographic analysis unit defined by the California Office of Statewide Health Planning and Development. MSSA are a good foundation for needs assessment analysis, healthcare planning, and healthcare policy development.

This statistic shows the percentage of the U.S. population by age who did not receive needed medical care or experienced delays for very or somewhat serious condition due to cost from 2001 to 2022. In 2022, ** percent of the population between 18 and 49 years had delayed or not received medical treatment due to cost reasons.

About this dataset

Context

The dataset tabulates the Medical Lake population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of Medical Lake.

Content

The dataset constitues the following two datasets across these two themes

• Medical Lake, WA Population Breakdown by Gender
• Medical Lake, WA Population Breakdown by Gender and Age

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/.

Introduction

Medical Technology and Innovation Statistics: In recent years, there has been a remarkable acceleration in the pace of medical technology advancements. These are driven by factors such as technological advancements, increased funding for research and development, and the growing demand for innovative solutions to address healthcare challenges.

These advancements have the potential to revolutionize various aspects of healthcare delivery, from diagnostics and treatment to patient monitoring and disease prevention.

About this dataset

Context

The dataset tabulates the data for the Medical Lake, WA population pyramid, which represents the Medical Lake population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Medical Lake, WA, is 18.7.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Medical Lake, WA, is 16.2.
• Total dependency ratio for Medical Lake, WA is 34.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Medical Lake, WA is 6.2.

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 for the Medical Lake population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Medical Lake for the selected age group is shown in the following column.
• Population (Female): The female population in the Medical Lake for the selected age group is shown in the following column.
• Total Population: The total population of the Medical Lake for the selected age group is shown in the following column.

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 Medical Lake Population by Age. You can refer the same here

The dataset contains counts of inpatient visits leading to a discharge to hospice care. Inpatient visits included in the counts consist of individuals aged 18 or over with a discharge disposition leading to home or facility hospice care. The total counts per each individual year can be viewed based on different patient characteristics, including patient age groups, individual counties of residence, primary payer type, diagnosis category, and patient sex/race/ethnicity. The disease categories include circulatory conditions, diabetes, malignant/benign neoplasms, malnutrition, neurodegenerative disease, renal failure or other kidney diagnoses, respiratory conditions and circulatory conditions. The categories represent common groupings of diagnoses seen in other studies related to hospice care and were created by grouping together relevant medical MSDRG codes in the HCAI inpatient data.

*Mean ankle brachial indices were all greater than 1 despite one patient having arterial disease; this was due to this same patient also having diabetes mellitus.

Patient demographics and baseline characteristics.

The Household Component (HC) of the Medical Expenditure Survey (MEPS) is a nationally representative survey of the U.S. civilian population which collects medical expenditure data at both the person and household levels. The focus of the MEPS HC is to collect detailed data on demographic characteristics, health conditions, health status, use of medical care services, charges and payments, access to care, satisfaction with care, health insurance coverage, income, and employment. This file cont ains data obtained in Rounds 1, 2, and 3 of the survey and contains variables pertaining to survey administration, demographics, employment, health status, health insurance, and utilization.

Patient demographics and clinical information.

About this dataset

Context

The dataset tabulates the Medicine Lake 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 Medicine Lake. The dataset can be utilized to understand the population distribution of Medicine Lake by age. For example, using this dataset, we can identify the largest age group in Medicine Lake.

Key observations

The largest age group in Medicine Lake, MT was for the group of age 60 to 64 years years with a population of 30 (15.79%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Medicine Lake, MT was the 50 to 54 years years with a population of 1 (0.53%). 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 Medicine Lake is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Medicine Lake 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 Medicine Lake Population by Age. You can refer the same here

The Ryan White HIV/AIDS Program provides a comprehensive system of care that includes primary medical care and essential support services for people living with HIV who are uninsured or underinsured. The Ryan White Grants are Federal funds which offer services to HIV clients in the Austin area and surrounding 10 counties. Medical Transportation is a service available to Ryan White eligible clients to use to get to and from medical appointments. This data includes Client Id, Age Range (10 years) , Gender, Education, Insurance, Race , Ethnicity, Primary Language, Living Situation. It also includes the medical transportation type used, Agency that issued the transportation, Grant Type, Grant Dates and Grant Year.

Bone = bone metastases.Liver = liver metastases.Locally adv = locally advanced spread of cancer.Abdomen = Metastases within the abdomen distant from the pancreas.Lung = lung metastases.Media = mediastinal metastases.Peritoneal = peritoneal metastases.Retroper = retroperitoneal nodes or metastases.*Patient died during study.**Weights were obtained on the first and last day of the ascorbic acid infusions.

Finland Population Per Medical Doctors Graduates was up 0.5% in 2019, from a year earlier.

The US Healthcare Visits Statistics dataset includes data about the frequency of healthcare visits to doctor offices, emergency departments, and home visits within the past 12 months in the United States by age, race, Hispanic origin, poverty level, health insurance status, geographic region and other characteristics between 1997 and 2016.

Comprehensive demographic dataset for Medical Arts, Savannah, GA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

About Dataset

This dataset provides information about various medical conditions such as Cancer, Pneumonia, and Diabetic based on demographic, lifestyle, and health-related features. It contains randomly generated user data, including multiple missing values, making it suitable for handling imbalanced classification tasks and missing data problems.

Features

• id: Unique identifier for each user.
• full_name: Randomly generated user name.
• age: Age of the user (ranging from 18 to 90 years), with some missing values.
• gender: The gender of the user (categorized as Male, Female, or Non-Binary).
• smoking_status: Indicates the smoking status of the user (Smoker, Non-Smoker, Former-Smoker).
• bmi: Body Mass Index (BMI) of the user (ranging from 15 to 40), with some missing values.
• blood_pressure: Blood pressure levels of the user (ranging from 90 to 180 mmHg), with some missing values.
• glucose_levels: Blood glucose levels of the user (ranging from 70 to 200 mg/dL), with some missing values.
• condition: The target label indicating the medical condition of the user (Cancer, Pneumonia, or Diabetic), with imbalanced distribution (15% Cancer, 25% Pneumonia, 60% Diabetic).

Goal

The objective of this dataset is to predict the medical condition (Cancer, Pneumonia, Diabetic) of a user based on their demographic, lifestyle, and health-related features. This dataset can be used to explore strategies for dealing with imbalanced classes and missing data in healthcare applications. ​