scholarly journals The Effects of Retiree Health Insurance Plan Characteristics on Retirees' Choice and Employers' Costs

2013 ◽  
Author(s):  
Robert Clark ◽  
Melinda Morrill ◽  
David Vanderweide
Keyword(s):  
Health Insurance ◽  
Insurance Plan ◽  
Health Insurance Plan ◽  
Retiree 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.

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