Things You Wanted to Know About Employer Health Insurance Plan (But Were Afraid to Ask)

1999 ◽  
Author(s):  
Alan Goldberg
Keyword(s):  
Health Insurance ◽  
Insurance Plan ◽  
Health Insurance Plan ◽  
Employer Health Insurance

Uncertainty and health insurance

2017 ◽  
Author(s):  
Jan Abel Olsen
Keyword(s):  
Health Insurance ◽  
Excess Demand ◽  
Financial Protection ◽  
Insurance Plan ◽  
Welfare Gain ◽  
Health Insurance Plan ◽  
Insurance Contracts ◽  
Efficiency Losses ◽  
Potential Efficiency

This chapter seeks to explain why most people prefer to have a health insurance plan. Two types of uncertainty give rise to the demand for financial protection: people do not know if they will ever come to need healthcare, and they do not know the full financial implications of illness. Health insurance would take away—or at least reduce—such financial uncertainties associated with future illnesses. A model is presented to show the so-called welfare gain from health insurance. This is followed by an investigation into the potential efficiency losses of health insurance, due to excess demand for services. In the last section, a different efficiency problem is discussed: when people have an incentive to signal ‘false risks’, this can lead to there being no market for insurance contracts which reflect ‘true risks’.

scholarly journals A Comparison Between Subjective and Objective Methods of Predicting Health Care Expenses to Support Consumers’ Health Insurance Plan Choice

2018 ◽  
Vol 3 (1) ◽  
pp. 238146831878109 ◽  
Author(s):  
Mary C. Politi ◽  
Enbal Shacham ◽  
Abigail R. Barker ◽  
Nerissa George ◽  
Nageen Mir ◽  
...  
Keyword(s):  
Health Care ◽  
Health Insurance ◽  
Health Care Utilization ◽  
Subjective Health ◽  
Care Utilization ◽  
Insurance Plan ◽  
Health Insurance Plan ◽  
Subjective Health Status ◽  
Reported Health ◽  
Nationally Representative

Objective. Numerous electronic tools help consumers select health insurance plans based on their estimated health care utilization. However, the best way to personalize these tools is unknown. The purpose of this study was to compare two common methods of personalizing health insurance plan displays: 1) quantitative healthcare utilization predictions using nationally representative Medical Expenditure Panel Survey (MEPS) data and 2) subjective-health status predictions. We also explored their relations to self-reported health care utilization. Methods. Secondary data analysis was conducted with responses from 327 adults under age 65 considering health insurance enrollment in the Affordable Care Act (ACA) marketplace. Participants were asked to report their subjective health, health conditions, and demographic information. MEPS data were used to estimate predicted annual expenditures based on age, gender, and reported health conditions. Self-reported health care utilization was obtained for 120 participants at a 1-year follow-up. Results. MEPS-based predictions and subjective-health status were related ( P < 0.0001). However, MEPS-predicted ranges within subjective-health categories were large. Subjective health was a less reliable predictor of expenses among older adults (age × subjective health, P = 0.04). Neither significantly related to subsequent self-reported health care utilization ( P = 0.18, P = 0.92, respectively). Conclusions. Because MEPS data are nationally representative, they may approximate utilization better than subjective health, particularly among older adults. However, approximating health care utilization is difficult, especially among newly insured. Findings have implications for health insurance decision support tools that personalize plan displays based on cost estimates.

scholarly journals Decreased Colorectal Cancer Incidence and Incidence-Based Mortality in the Screening-Age Population of Ontario

2020 ◽  
Author(s):  
Lawrence F Paszat ◽  
Rinku Sutradhar ◽  
Elyse Corn ◽  
Jill Tinmouth ◽  
Nancy N Baxter ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Health Insurance ◽  
Insurance Plan ◽  
Health Insurance Plan ◽  
Ontario Health Insurance Plan ◽  
Eligible Population ◽  
Ontario Cancer Registry ◽  
Incidence And Mortality ◽  
Colorectal Cancer Incidence ◽  
Colorectal Screening

Abstract Background and Aims We aimed to evaluate trends in Ontario, Canada, 2002 to 2016, in uptake of colorectal evaluative procedures, colorectal cancer (CRC) incidence and incidence-based mortality in the colorectal screening-age population. Methods We defined the screening age-eligible population as persons 51 to 74 years of age with ≥1 year eligibility for the Ontario Health Insurance Plan, excluding those with a diagnosis of CRC in the Ontario Cancer Registry (OCR) prior to age 50 or January 1, 2002. We computed annual up-to-date status with colorectal evaluative procedures from billing claims, and CRC incidence from the OCR. In order to compute incidence-based CRC mortality, we included persons with a first diagnosis of CRC between the ages of 51 and 74, diagnosed between January 1, 1992 and December 31, 2001, still alive and &lt;75 years of age on January 1, 2002, based on cause of death from the OCR. Overall, age-stratified and sex-stratified trends were evaluated by Cochran–Armitage trend tests. Results Persons up to date with colorectal evaluative procedures increased from 628,214/2,782,061 (22.6%) in 2002 to 2,584,570/4,179,789 (62.2%) in 2016. CRC incidence fell from 129.3/100,000 in 2002 to 94.54/100,000 in 2016, and incidence-based CRC mortality fell from 40.8/100,000 to 24.1/100,000. Decreasing trends in overall and stratified incidence and mortality were all significant, except among persons 51 to 54 years old. Conclusions There was continued increase in persons up-to-date with colorectal evaluative procedures, and significant decrease in CRC incidence and incidence-based CRC mortality from 2002 through 2016.

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