The Effect of Health Insurance on Health Care Utilization: Evidence from The Medical Expenditure Panel Survey 2000-2005

Author(s):  
Diether W. Beuermann
2006 ◽  
Vol 5 (1) ◽  
Author(s):  
Fei Liu ◽  
David M. Zimmer

AbstractThe switching of health insurance plans and health care utilization are potentially correlated with both observable and unobservable information. This paper presents a two-period model of health care utilization, and attempts to account for unobserved heterogeneity that simultaneously affects utilization and the decision to switch plans. Data used in this paper are drawn from the Medical Expenditure Panel Survey. Results indicate that non-HMO enrollees increase their utilization of non-emergency related care prior to switching to HMOs, and they decrease utilization after switching. Conversely, individuals enrolled in HMOs report lower levels of utilization before and higher utilization after they switch to non-HMOs.


Author(s):  
David M. Zimmer

Abstract This paper uses data from the Medical Expenditure Panel Survey to estimate the effect of COBRA on health care utilization among a sample of individuals who experience employment separation. The empirical specification employs a structural simultaneous equations model of insurance choice and utilization that is estimated by Maximum Simulated Likelihood. Results indicate that employment separators who elect COBRA appear to consume more health care compared to individuals who become temporarily uninsured. In addition, results do not indicate adverse selection into COBRA. Although COBRA enrollees consume more health care than temporary insurance losers, election appears to exhibit favorable selection with respect to physician utilization.


Author(s):  
Sharon Klein ◽  
Shangqing Jiang ◽  
Jacob R. Morey ◽  
Akila Pai ◽  
Donna M. Mancini ◽  
...  

Background: Heart failure (HF) constitutes a growing burden for public health and the US health care system. While the prevalence of HF is increasing, differences in health care utilization and expenditures within various sociodemographic groups remain poorly defined. Methods: We used the Medical Expenditure Panel Survey to assess annual health care utilization and expenditures from 2012 to 2017. Health care utilization was based on the annual frequency of various health care encounters. Annual total and out-of-pocket expenditures were evaluated for hospital inpatient stays, emergency room visits, outpatient visits, office-based medical provider visits, prescribed medicines, dental visits, home health aid visits, and other medical expenses. We performed univariable and multivariable regression analysis based on patient characteristics including sociodemographic and comorbidity variables. Results: Our results showed that total health care expenditures among patients with HF were $21 177 (95% CI, $18 819–$24 736) per year as compared with $5652 (95% CI, $5469–$5837) in those without HF ( P <0.001). Total expenditures within the population with HF were primarily being driven by expenditures associated with inpatient hospitalizations. Increasing number of comorbid conditions was associated with significant increases in total health care expenditures. Older age, female sex, earlier study years, number of comorbidities, higher level of education, and increasing family income brackets independently raised out-of-pocket expenditures. Conclusions: Our findings of increased health care utilization and expenditures based on sex, age, increasing number of comorbidities, wealthier income status, and increased education attainment level may be used for efforts aimed at better distributing health care resources to improve health outcomes in HF.


2021 ◽  
Vol 111 (12) ◽  
pp. 2157-2166
Author(s):  
Samuel H. Zuvekas ◽  
David Kashihara

The COVID-19 pandemic caused substantial disruptions in the field operations of all 3 major components of the Medical Expenditure Panel Survey (MEPS). The MEPS is widely used to study how policy changes and major shocks, such as the COVID-19 pandemic, affect insurance coverage, access, and preventive and other health care utilization and how these relate to population health. We describe how the MEPS program successfully responded to these challenges by reengineering field operations, including survey modes, to complete data collection and maintain data release schedules. The impact of the pandemic on response rates varied considerably across the MEPS. Investigations to date show little effect on the quality of data collected. However, lower response rates may reduce the statistical precision of some estimates. We also describe several enhancements made to the MEPS that will allow researchers to better understand the impact of the pandemic on US residents, employers, and the US health care system. (Am J Public Health. 2021;111(12):2157–2166. https://doi.org/10.2105/AJPH.2021.306534 )


2018 ◽  
Vol 3 (1) ◽  
pp. 238146831878109 ◽  
Author(s):  
Mary C. Politi ◽  
Enbal Shacham ◽  
Abigail R. Barker ◽  
Nerissa George ◽  
Nageen Mir ◽  
...  

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.


2003 ◽  
Vol 93 (10) ◽  
pp. 1740-1747 ◽  
Author(s):  
Jacqueline W. Lucas ◽  
Daheia J. Barr-Anderson ◽  
Raynard S. Kington

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