OBJECTIVE: To illustrate the impact of moral hazard for estimating relative rates of underinsurance and to present an adjustment method to correct for this source of bias. DATA SOURCES/STUDY SETTING: Secondary data from the 2005 Medical Expenditure Panel Survey (MEPS) are used in this study. We restrict attention to households that report having employer-sponsored insurance (ESI) for all members during the entire 2005 calendar year. STUDY DESIGN: Individuals or households are often classified as underinsured if out-of-pocket spending on medical care relative to income exceeds some threshold. In this paper, we show that, without adjustment, this common threshold measure of underinsurance will underestimate the number with low levels of insurance coverage due to moral hazard. We propose an adjustment method and apply it to the specific case of estimating the difference in rates of underinsurance among small- versus large-firm workers with full-year ESI. DATA COLLECTION/EXTRACTION: Data were abstracted from the MEPS website. All analyses were performed in Stata 9.2. PRINCIPAL FINDINGS: Applying the adjustment, we find that the underinsurance rate of small-firm households increases by approximately 20 percent with the adjustment for moral hazard and the difference in underinsurance rates between large-firm and small-firm households widens substantially. CONCLUSIONS: Adjusting for moral hazard makes a sizeable difference in the estimated prevalence of underinsurance using a threshold measure.
OBJECTIVE: To illustrate the impact of moral hazard for estimating relative rates of underinsurance and to present an adjustment method to correct for this source of bias. DATA SOURCES/STUDY SETTING: Secondary data from the 2005 Medical Expenditure Panel Survey (MEPS) are used in this study. We restrict attention to households that report having employer-sponsored insurance (ESI) for all members during the entire 2005 calendar year. STUDY DESIGN: Individuals or households are often classified as underinsured if out-of-pocket spending on medical care relative to income exceeds some threshold. In this paper, we show that, without adjustment, this common threshold measure of underinsurance will underestimate the number with low levels of insurance coverage due to moral hazard. We propose an adjustment method and apply it to the specific case of estimating the difference in rates of underinsurance among small- versus large-firm workers with full-year ESI. DATA COLLECTION/EXTRACTION: Data were abstracted from the MEPS website. All analyses were performed in Stata 9.2. PRINCIPAL FINDINGS: Applying the adjustment, we find that the underinsurance rate of small-firm households increases by approximately 20 percent with the adjustment for moral hazard and the difference in underinsurance rates between large-firm and small-firm households widens substantially. CONCLUSIONS: Adjusting for moral hazard makes a sizeable difference in the estimated prevalence of underinsurance using a threshold measure.
Authors: Jon Gabel; Roland McDevitt; Laura Gandolfo; Jeremy Pickreign; Samantha Hawkins; Cheryl Fahlman Journal: Health Aff (Millwood) Date: 2006 May-Jun Impact factor: 6.301
Authors: Lauren E Wisk; Ronald Gangnon; David J Vanness; Alison A Galbraith; John Mullahy; Whitney P Witt Journal: Health Serv Res Date: 2014-10-18 Impact factor: 3.402
Authors: Jeffrey A Berinstein; Shirley A Cohen-Mekelburg; Calen A Steiner; Megan McLeod; Mohamed Noureldin; John I Allen; Jeffrey T Kullgren; Akbar K Waljee; Peter D R Higgins Journal: Inflamm Bowel Dis Date: 2021-05-17 Impact factor: 7.290