In the United States, average employee premium contributions and deductibles as a percentage of median household income have risen in the past decade. In 2020, an employee’s total potential out-of-pocket medical costs (premium and deductible) amounted to 11.6 percent of median income. This included 6.9 percent in employee premium contributions and 4.7 percent in deductibles. However, states varied greatly in median income spent on premiums and deductibles, with workers in Mississippi having to spend on average 19 percent of their income on potential out-of-pocket medical costs.

Employer sponsored health insurance In 2020, over half of the U.S. population has some type of employment-based health insurance coverage. The Affordable Care Act penalizes large employers (with 50 or more full-time employees), if they do not provide health insurance to their employees. Nevertheless, of the uninsured aged under 65 years, the large majority worked either full or part-time (or someone in their household did).

Out-of-pocket medical costs Despite having insurance coverage, most plans have a deductible, the amount an insured must pay themselves that year before their insurance starts covering for them. The average annual deductible for single coverage amounted to roughly 1,700 U.S. dollars in 2021. Even after reaching their deductible, most insured have other forms of out-of-pocket health costs in the form of co-payments and co-insurance for health services or prescription drugs.

This dataset provides insights into the cost of living and average monthly income across various countries and regions worldwide from 2000 to 2023. It includes critical economic indicators such as housing costs, taxes, healthcare, education, transportation expenses, and savings rates. The data is ideal for analyzing economic trends, regional comparisons, and financial planning.

Column Descriptions: Country: The name of the country where the data was recorded. Region: The geographical region to which the country belongs (e.g., Asia, Europe). Year: The year when the data was recorded. Average_Monthly_Income: The average monthly income of individuals in USD. Cost_of_Living: The average monthly cost of living in USD, including essentials like housing, food, and utilities. Housing_Cost_Percentage: The percentage of income spent on housing expenses. Tax_Rate: The average tax rate applied to individuals' income, expressed as a percentage. Savings_Percentage: The portion of income saved monthly, expressed as a percentage. Healthcare_Cost_Percentage: The percentage of income spent on healthcare services. Education_Cost_Percentage: The percentage of income allocated to educational expenses. Transportation_Cost_Percentage: The percentage of income spent on transportation costs.

How much are low-income individuals willing to pay for health insurance, and what are the implications for insurance markets? Using administrative data from Massachusetts' subsidized insurance exchange, we exploit discontinuities in the subsidy schedule to estimate willingness to pay and costs of insurance among low-income adults. As subsidies decline, insurance take-up falls rapidly, dropping about 25 percent for each $40 increase in monthly enrollee premiums. Marginal enrollees tend to be lower-cost, indicating adverse selection into insurance. But across the entire distribution we can observe (approximately the bottom 70 percent of the willingness to pay distribution) enrollees' willingness to pay is always less than half of their own expected costs that they impose on the insurer. As a result, we estimate that take-up will be highly incomplete even with generous subsidies. If enrollee premiums were 25 percent of insurers' average costs, at most half of potential enrollees would buy insurance; even premiums subsidized to 10 percent of average costs would still leave at least 20 percent uninsured. We briefly consider potential explanations for these findings and their normative implications.

This graph shows the estimated percentage of consumers of medical cannabis in Italy in 2018, by monthly income. According to data, individuals earning between 500 and 1500 euros per month made up the largest percentage of consumers of cannabis for therapeutic use (20.9 percent), followed by individuals with monthly incomes of more than 1500 euros (14 percent).

Graph and download economic data for Unemployment Rate - Education and Health Services, Private Wage and Salary Workers (LNU04032240) from Jan 2000 to Sep 2025 about health, salaries, workers, education, 16 years +, wages, household survey, services, private, unemployment, rate, and USA.

According to a survey conducted in Hong Kong in 2016, around ** percent of households with monthly salary of ****** Hong Kong dollars or more owned private health insurance, while only ** percent of households with monthly salary of less than 10,000 Hong Kong dollars owned private health insurance.

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

AMCE: PT: >5 E: CO: NS: YOY: Medical, Health Care and Welfare data was reported at -0.600 % in Oct 2018. This records a decrease from the previous number of -0.500 % for Sep 2018. AMCE: PT: >5 E: CO: NS: YOY: Medical, Health Care and Welfare data is updated monthly, averaging -3.600 % from Jan 2017 (Median) to Oct 2018, with 22 observations. The data reached an all-time high of 12.600 % in Nov 2017 and a record low of -14.600 % in Mar 2017. AMCE: PT: >5 E: CO: NS: YOY: Medical, Health Care and Welfare data remains active status in CEIC and is reported by Ministry of Health, Labour and Welfare. The data is categorized under Global Database’s Japan – Table JP.G041: Monthly Labour Survey: Part-Time: Average Monthly Cash Earnings: Percentage Change.

This is Health insurance Data to analyze Sales , internal operations and market size of a health insurance company . To analyze the sales, internal operations, and market size of a health insurance company, you would need access to relevant data. While I don't have real-time data, I can provide you with a general outline of the types of data you may need to analyze these aspects. Here are some key data points to consider:

Sales Analysis:

Monthly/quarterly/annual premium revenue Number of policies sold Premiums by product types (e.g., individual, family, group) Sales channels (e.g., agents, brokers, online) Internal Operations Analysis:

Claims data: Number of claims filed, paid, and denied Claim settlement time and ratios Customer service metrics (e.g., response time, satisfaction ratings) Underwriting metrics (e.g., policy acceptance rate, risk assessment) Market Analysis:

Market share: Percentage of the total health insurance market held by the company Competition analysis: Market share of competitors, their product offerings, and pricing Demographics: Age, income, location, and other relevant demographic information of policyholders Regulatory factors: Changes in regulations or laws affecting the health insurance industry Other data points that could be useful for analysis include customer retention rates, profitability analysis, marketing expenditure, and customer feedback.

Keep in mind that this is a general overview, and the specific data requirements may vary based on your company's unique goals and objectives. Additionally, it's important to handle and analyze this data in compliance with relevant privacy and data protection laws.

The Los Angeles County Climate Vulnerability Assessment identified and incorporated 29 social vulnerability indicators. These indicators are listed below alongside their description and data source. Full report: https://ceo.lacounty.gov/cva-report/Note: All indicators are at the census tract level. Census tracts with no population (data) are omitted from this layer. Indicator Description Source Countywide Average

Asian Percent identifying as non-Hispanic Asian US Census Bureau, American Community Survey 2018 5-Year Estimates 14.4%

Asthma Age-adjusted rate of emergency department visits for asthma California Environmental Health Tracking Program (CEHTP) and Office of Statewide Health Planning and Development (OSHPD) 52.2

Black Percent identifying as non-Hispanic black or African American US Census Bureau, American Community Survey 2018 5-Year Estimates 7.9%

Cardiovascular Age-adjusted rate of emergency department visits for heart attacks per 10,000 California Environmental Health Tracking Program (CEHTP) and Office of Statewide Health Planning and Development (OSHPD) 8.4

Children Percent of people 18 and under US Census Bureau, American Community Survey 2018 5-Year Estimates 24.9%

Disability Percent of persons with either mental or physical disability US Census Bureau, American Community Survey 2018 5-Year Estimates 9.9%

Female Percent female US Census Bureau, American Community Survey 2018 5-Year Estimates 50.7%

Female householder Percent of households that have a female householder with no spouse present US Census Bureau, American Community Survey 2018 5-Year Estimates 16.2%

Foreign born Percent of the total population who was not born in the United States or Puerto Rico US Census Bureau, American Community Survey 2018 5-Year Estimates 35.2%

Hispanic Latinx Percent identifying as Hispanic or Latino US Census Bureau, American Community Survey 2018 5-Year Estimates 48.5%

Households without vehicle access Percent of households without access to a personal vehicle US Census Bureau, American Community Survey 2018 5-Year Estimates 8.8%

Library access Each tract's average block distance to nearest library LA County Internal Services Department 1.14 miles

Limited English Percent limited English speaking households US Census Bureau, American Community Survey 2018 5-Year Estimates 13.6%

Living in group quarters Percent of persons living in (either institutionalized or uninstitiutionalized) group quarters US Census Bureau, American Community Survey 2018 5-Year Estimates 1.8%

Median income Median household income of census tract US Census Bureau, American Community Survey 2018 5-Year Estimates $69,623

Mobile homes Percent of occupied housing units that are mobile homes US Census Bureau, American Community Survey 2018 5-Year Estimates 1.8%

No health insurance Percent of persons without health insurance US Census Bureau, American Community Survey 2018 5-Year Estimates 0.2%

No high school diploma Percent of persons 25 and older without a high school diploma US Census Bureau, American Community Survey 2018 5-Year Estimates 10.8%

No internet subscription Percent of the population without an internet subscription US Census Bureau, American Community Survey 2018 5-Year Estimates 22.6%

Older adults Percent of people 65 and older US Census Bureau, American Community Survey 2018 5-Year Estimates 18.4%

Older adults living alone Percent of households in which the householder is 65 and over who and living alone US Census Bureau, American Community Survey 2018 5-Year Estimates 12.9%

Outdoor workers Percentage of outdoor workers - agriculture, fishing, mining, extractive, construction occupations US Census Bureau, American Community Survey 2018 5-Year Estimates 8.0%

Poverty Percent of the population living in a family earning below 100% of the federal poverty threshold US Census Bureau, American Community Survey 2018 5-Year Estimates 5.4%

Rent burden Percent of renters paying more than 30 percent of their monthly income on rent and utilities US Census Bureau, American Community Survey 2018 5-Year Estimates 16.1%

Renters Percentage of renters per census tract US Census Bureau, American Community Survey 2018 5-Year Estimates 54.3%

Transit access Percent of population residing within a ½ mile of a major transit stop Healthy Places Index, SCAG 52.8%

Tribal and Indigenous Percent identifying as non-Hispanic American Indian and Alaska native US Census Bureau, American Community Survey 2018 5-Year Estimates 54.9%

Unemployed Percent of the population over the age of 16 that is unemployed and eligible for the labor force US Census Bureau, American Community Survey 2018 5-Year Estimates 6.9%

Voter turnout rate Percentage of registered voters voting in the 2016 general election CA Statewide General Elections Database 2016 63.8%

Mean household income 11,274 (standard deviation 9,417) and median household income is KES 8,800 (or about USD 104.5 per month).Mean household expenditures: KES 13,957 (standard deviation 10,009).Number of observations  = 3431 for food and 3435 for all other items.

As of December 2022, the largest share of dentists in Denmark had a monthly income of between ****** and almost ****** Danish kroner. *** percent of dentists had a monthly income of ****** and more Danish kroner, while around **** percent of Danish dentists earned between ****** and approximately ****** Danish kroner per month. In the Danish health sector, the number of employed dentists decreased in recent years. In 2019, there were approximately ***** dentists employed in the healthcare sector.

 Dentists in Sweden 
In neighboring Sweden, on the other hand, the number of dentists employed in the healthcare sector increased during the past years. In 2019, approximately ***** dentists worked in the Swedish health sector. In 2021, the average monthly salary of dentists was ****** Swedish kronor. It was slightly higher among male than among female dentists.

 Number of dentists in Norway 
Also in Norway the number of employed dentists grew steadily from 2000 to 2021. During this period, the number increased by *****. In 2021, there were more than ***** dentists employed in the Norwegian healthcare sector.

Abstract (en): In 2008, a group of uninsured low-income adults in Oregon was selected by lottery to be given the chance to apply for Medicaid. This lottery provides an opportunity to gauge the effects of expanding access to public health insurance on the health care use, financial strain, and health of low-income adults using a randomized controlled design. The Oregon Health Insurance Experiment follows and compares those selected in the lottery (treatment group) with those not selected (control group). The data collected and provided here include data from in-person interviews, three mail surveys, emergency department records, and administrative records on Medicaid enrollment, the initial lottery sign-up list, welfare benefits, and mortality. This data collection has seven data files: Dataset 1 contains administrative data on the lottery from the state of Oregon. These data include demographic characteristics that were recorded when individuals signed up for the lottery, date of lottery draw, and information on who was selected for the lottery, applied for the lotteried Medicaid plan if selected, and whose application for the lotteried plan was approved. Also included are Oregon mortality data for 2008 and 2009. Dataset 2 contains information from the state of Oregon on the individuals' participation in Medicaid, Supplemental Nutrition Assistance Program (SNAP), and Temporary Assistance to Needy Families (TANF). Datasets 3-5 contain the data from the initial, six month, and 12 month mail surveys, respectively. Topics covered by the surveys include demographic characteristics; health insurance, access to health care and health care utilization; health care needs, experiences, and costs; overall health status and changes in health; and depression and medical conditions and use of medications to treat them. Dataset 6 contains an analysis subset of the variables from the in-person interviews. Topics covered by the survey questionnaire include overall health, health insurance coverage, health care access, health care utilization, conditions and treatments, health behaviors, medical and dental costs, and demographic characteristics. The interviewers also obtained blood pressure and anthropometric measurements and collected dried blood spots to measure levels of cholesterol, glycated hemoglobin and C-reactive protein. Dataset 7 contains an analysis subset of the variables the study obtained for all emergency department (ED) visits to twelve hospitals in the Portland area during 2007-2009. These variables capture total hospital costs, ED costs, and the number of ED visits categorized by time of the visit (daytime weekday or nighttime and weekends), necessity of the visit (emergent, ED care needed, non-preventable; emergent, ED care needed, preventable; emergent, primary care treatable), ambulatory case sensitive status, whether or not the patient was hospitalized, and the reason for the visit (e.g., injury, abdominal pain, chest pain, headache, and mental disorders). The collection also includes a ZIP archive (Dataset 8) with Stata programs that replicate analyses reported in three articles by the principal investigators and others: Finkelstein, Amy et al "The Oregon Health Insurance Experiment: Evidence from the First Year". The Quarterly Journal of Economics. August 2012. Vol 127(3). Baicker, Katherine et al "The Oregon Experiment - Effects of Medicaid on Clinical Outcomes". New England Journal of Medicine. 2 May 2013. Vol 368(18). Taubman, Sarah et al "Medicaid Increases Emergency Department Use: Evidence from Oregon's Health Insurance Experiment". Science. 2 Jan 2014. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. Presence of Common Scales: Patient Health Questionnaire-9 (PHQ-9) Total Severity Score SF-8 Health Survey Physical Component Score SF-8 Health Survey Mental Component Score Framingham Risk Score Response Rates: For the mail surveys, the response rates were 45 percent for the initial survey, 49 percent for the six month survey, and 41 percent for the 12 month survey. For the in-person survey the response rate was 59 percent. The individu...

Percentage rating working conditions as good (represented by percent of respondents who rated the indicators as ‘agree’ and ‘strongly agree’) for different indicators by gender, age group, years of service in the public hospital, and workforce categories.

The mean drug price by class, percent of mean monthly income (MMI) that the mean price represents across the three time points, and ratio of % of MMI in 2023 to % MMI in 2023 (pre-crisis-August 2019, early crisis- August 2019, most recent-April 2023).

Japan AMCE: >5 E: Special: YoY: Medical, Health Care & Welfare data was reported at 31.000 % in May 2018. This records an increase from the previous number of -18.800 % for Apr 2018. Japan AMCE: >5 E: Special: YoY: Medical, Health Care & Welfare data is updated monthly, averaging 0.350 % from Oct 2007 (Median) to May 2018, with 128 observations. The data reached an all-time high of 378.400 % in Feb 2009 and a record low of -63.700 % in Nov 2015. Japan AMCE: >5 E: Special: YoY: Medical, Health Care & Welfare data remains active status in CEIC and is reported by Ministry of Health, Labour and Welfare. The data is categorized under Global Database’s Japan – Table JP.G039: Monthly Labour Survey: Average Monthly Cash Earnings: Percentage Change.

This survey was conducted as part of an evaluation of the Robert Wood Johnson Foundation's Health Care for the Uninsured Program (HCUP), a program whose primary focus was the development and marketing of affordable health insurance products for small businesses. The survey investigated the number and types of small businesses that offered and did not offer insurance, the number and types of employees of small businesses who received and did not receive insurance, and whether the employers and employees participating in HCUP were different from those with other types of insurance or from those with no insurance. In addition, the survey was designed to test several hypotheses: whether employers facing an inelastic demand for their product or a tight labor market would be more likely to offer health insurance to their employees, and whether higher wages substitute for health insurance for certain groups of highly skilled or unionized workers. Firm-level data collected by the survey include number of permanent and temporary employees, employee turnover, fringe benefits offered to full- and part-time employees (e.g., paid vacation, paid sick leave, long-term disability insurance, life insurance, retirement plan, group health insurance), type of business, number of years owner had owned the company, age and legal form of the company, and gross revenue. Extensive information on health insurance was obtained from firms offering this benefit: total monthly premium paid for health insurance, percent of premium paid by the company, reasons that influenced the decision to provide health insurance, whether a Health Maintenance Organization (HMO) insurance plan was offered, whether a deductible or co-payment was required for hospital inpatient services, and whether hospital room and board, physician office visits, maternity care, prescription drugs, inpatient mental health treatment, or substance abuse treatment were covered. These firms were also queried about recent changes in the number of health plan enrollees, deductibles, co-insurance rates, benefits offered, employer premium share, recent changes in health insurance carriers and reasons for changing, and recent increases in premiums and their effects on the firm's prices, profits, wages, and number of employees. Companies not offering health insurance were asked why they did not offer this benefit and were queried about factors that might influence them to offer a health plan. Individual-level data on employees include sex, age, marital status, length of employment, number of hours worked during the last week, salary or wage, health plan participation, amount of health premium paid by the employee, and whether the employee had health coverage from another source.

Male health and medical professionals earned 160,000 Russian rubles per month on average in 2024. To compare, the average monthly wage of women working in that sector was six percent lower, at 151,000 Russian rubles.

Japan AMCE: >5 E: CO: NS: YoY: Medical, Health Care & Welfare data was reported at -0.600 % in May 2018. This records an increase from the previous number of -1.800 % for Apr 2018. Japan AMCE: >5 E: CO: NS: YoY: Medical, Health Care & Welfare data is updated monthly, averaging -0.200 % from Oct 2007 (Median) to May 2018, with 128 observations. The data reached an all-time high of 11.900 % in Feb 2008 and a record low of -15.000 % in Aug 2009. Japan AMCE: >5 E: CO: NS: YoY: Medical, Health Care & Welfare data remains active status in CEIC and is reported by Ministry of Health, Labour and Welfare. The data is categorized under Global Database’s Japan – Table JP.G039: Monthly Labour Survey: Average Monthly Cash Earnings: Percentage Change.

Which factors are associated with the uptake of clinical breast examination?