Out of pocket
Gopi Shah Goda, Monica Farid & Jay Bhattacharya
NBER Working Paper, January 2016
Abstract:
The dependent care mandate is one of the most popular provisions of the 2010 Affordable Care Act (ACA). This provision requires that employer-based insurance plans cover health care expenditures for workers with children 26 years old or younger. While there has been considerable scholarly and policy interest in the effects of this mandate on health insurance coverage among young adults, there has been little scholarly work measuring the costs and incidence of this mandate and who pays the costs of it. In our empirical work, we exploit the fact that some states had dependent care mandates in years prior to the passage of the ACA. Using data from the Survey of Income and Program Participation (SIPP), we find that workers at firms with employer-based coverage – whether or not they have dependent children – experience an annual reduction in wages of approximately $1,200. Our results imply that the marginal costs of mandated employer-based coverage expansions are not entirely borne only by the people whose coverage is expanded by the mandate.
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Using Options to Measure the Full Value-Effect of an Event: Application to Obamacare
Paul Borochin & Joseph Golec
Journal of Financial Economics, forthcoming
Abstract:
Many event studies only measure a fraction of an event's full value effect because they do not adjust for market anticipation of the event. We present a method based on stock and options prices to measure the full effect that accounts for market anticipation. We apply the method to the passage of Obamacare. Our method estimates the full value effect of Obamacare on the healthcare sector as $55 billion, compared to $16 billion when market anticipation is ignored. The method is applicable to most major events because it only requires that some affected firms have traded stock options.
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Generosity and Prosocial Behavior in Healthcare Provision: Evidence from the Laboratory and Field
Michelle Brock, Andreas Lange & Kenneth Leonard
Journal of Human Resources, Winter 2016, Pages 133-162
Abstract:
Do health workers sometimes have intrinsic motivation to help their patients? We examine the correlation between the generosity of clinicians — as measured in a laboratory experiment — and the quality of care they provide (1) in their normal work environment, (2) when a peer observes them, and (3) six weeks after an encouragement visit from a peer. We find that clinicians defined as generous in the laboratory provide 8 percent better care in their normal work environment. On average, all clinicians provide 3 percent and 8 percent better care when observed by a peer and after encouragement, respectively. Importantly, generous clinicians react to peer scrutiny and encouragement in the same way as ungenerous clinicians.
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Ralph Koijen, Tomas Philipson & Harald Uhlig
Econometrica, January 2016, Pages 195–242
Abstract:
We provide a theoretical and empirical analysis of the link between financial and real health care markets. This link is important as financial returns drive investment in medical research and development (R&D), which, in turn, affects real spending growth. We document a “medical innovation premium” of 4–6% annually for equity returns of firms in the health care sector. We interpret this premium as compensating investors for government-induced profit risk, and we provide supportive evidence for this hypothesis through company filings and abnormal return patterns surrounding threats of government intervention. We quantify the implications of the premium for the growth in real health care spending by calibrating our model to match historical trends, predicting the share of gross domestic product (GDP) devoted to health care to be 32% in the long run. Policies that had removed government risk would have led to more than a doubling of medical R&D and would have increased the current share of health care spending by more than 3% of GDP.
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Racial and Ethnic Disparities in Health Care Access and Utilization Under the Affordable Care Act
Jie Chen et al.
Medical Care, February 2016, Pages 140–146
Objective: To examine racial and ethnic disparities in health care access and utilization after the Affordable Care Act (ACA) health insurance mandate was fully implemented in 2014.
Research Design: Using the 2011–2014 National Health Interview Survey, we examine changes in health care access and utilization for the nonelderly US adult population. Multivariate linear probability models are estimated to adjust for demographic and sociodemographic factors.
Results: The implementation of the ACA (year indicator 2014) is associated with significant reductions in the probabilities of being uninsured (coef=−0.03, P<0.001), delaying any necessary care (coef=−0.03, P<0.001), forgoing any necessary care (coef=−0.02, P<0.001), and a significant increase in the probability of having any physician visits (coef=0.02, P<0.001), compared with the reference year 2011. Interaction terms between the 2014 year indicator and race/ethnicity demonstrate that uninsured rates decreased more substantially among non-Latino African Americans (African Americans) (coef=−0.04, P<0.001) and Latinos (coef=−0.03, P<0.001) compared with non-Latino whites (whites). Latinos were less likely than whites to delay (coef=−0.02, P<0.001) or forgo (coef=−0.02, P<0.001) any necessary care and were more likely to have physician visits (coef=0.03, P<0.005) in 2014. The association between year indicator of 2014 and the probability of having any emergency department visits is not significant.
Conclusions: Health care access and insurance coverage are major factors that contributed to racial and ethnic disparities before the ACA implementation. Our results demonstrate that racial and ethnic disparities in access have been reduced significantly during the initial years of the ACA implementation that expanded access and mandated that individuals obtain health insurance.
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Rich, Poor, Singles, and Couples. Who Receives Medicaid in Old Age and Why?
Margherita Borella, Mariacristina De Nardi & Eric French
NBER Working Paper, January 2016
Abstract:
We use the Health and Retirement Survey (HRS) data set to study who receives Medicaid in old age and why. First, we conduct a descriptive analysis of Medicaid recipiency along a number of important observables. This analysis shows that, while fewer people with high permanent income receive Medicaid, a significant fraction of high permanent income people receive Medicaid at very old ages. It also shows that more single people receive Medicaid than people in couples, that people who just lost their spouse rapidly become very similar in their Medicaid recipiency and other important observable characteristics to people who have been single for much longer, and that bad health commoves with Medicaid recipiency. Finally, this analysis shows even people having long-term care insurance end up on Medicaid, but that the fraction of people in this group that is on Medicaid is one-third that of the entire population of the elderly. Second, multivariate regression analysis allows us to disentangle the effects of many observables on Medicaid recipiency while conditioning for others and reveals several interesting patterns. First, permanent income and other variables capturing economic background have a major role in determining individuals’ Medicaid coverage and explain much of the observed differences in Medicaid recipiency among singles, couples, and people who recently lost their spouse. Second, impairments in the activities of daily living and residency in a nursing home have a large effect on the probability of being on Medicaid, with the effect of nursing home residency being relatively large for those in the middle and upper income groups. Lastly, having long-term care insurance has no independent effect on the probability of ending up on Medicaid.
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Kamyar Nasseh, Marko Vujicic & Michael Glick
Health Economics, forthcoming
Abstract:
Periodontal disease has been linked to poor glycemic control among individuals with type 2 diabetes. Using integrated dental, medical, and pharmacy commercial claims from Truven MarketScan® Research Databases, we implement inverse probability weighting and doubly robust methods to estimate a relationship between a periodontal intervention and healthcare costs and utilization. Among individuals newly diagnosed with type 2 diabetes, we find that a periodontal intervention is associated with lower total healthcare costs (−$1799), lower total medical costs excluding pharmacy costs (−$1577), and lower total type 2 diabetes-related healthcare costs (−$408).
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Keith Kranker
Journal of Health Economics, March 2016, Pages 52–69
Abstract:
In recent decades, most states’ Medicaid programs have introduced disease management programs for chronically ill beneficiaries. Interventions assist beneficiaries and their health care providers to appropriately manage chronic health condition(s) according to established clinical guidelines. Cost containment has been a key justification for the creation of these programs despite mixed evidence they actually save money. This study evaluates the effects of a disease management program in Georgia by exploiting a natural experiment that delayed the introduction of high-intensity services for several thousand beneficiaries. Expenditures for medical claims decreased an average of $89 per person per month for the high- and moderate-risk groups, but those savings were not large enough to offset the total costs of the program. Impacts varied by the intensity of interventions, over time, and across disease groups. Heterogeneous treatment effect analysis indicates that decreases in medical expenditures were largest at the most expensive tail of the distribution.
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Anticipatory Behavior in Response to Medicare Part D's Coverage Gap
Cameron Kaplan & Yuting Zhang
Health Economics, forthcoming
Abstract:
Under the standard Medicare Part D benefit structure, copayments for medications change discontinuously at certain levels of accumulative drug spending. Beneficiaries pay 25% of the cost of medications in the initial phase, 100% in the coverage gap, and 5% in the catastrophic phase. We examine whether individuals anticipate these copayment changes and adjust their consumption in advance. We use variation in birth-months of beneficiaries who enroll in Part D plans when they first turn 65. Birth-months generate exogenous variation in the end-of-year price because those who enroll earlier in the year are more likely to reach the coverage gap than those who enroll later. We study the impact of variation in end-of-year price on the first three months of medication use immediately following enrollment. We use difference-in-differences to adjust for seasonal trends in use, by comparing our main study group with those who receive low-income subsidies, and therefore do not face a coverage gap. We find strong evidence of anticipatory behavior, with an implied elasticity with respect to future prices ranging from −0.2 to −0.5. In addition, we find that beneficiaries modify their consumption by changing the quantity of prescriptions filled, instead of switching between brand-name and generic drugs.
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Reductions in Diagnostic Imaging With High Deductible Health Plans
Sarah Zheng et al.
Medical Care, February 2016, Pages 110–117
Background: Diagnostic imaging utilization grew rapidly over the past 2 decades. It remains unclear whether patient cost-sharing is an effective policy lever to reduce imaging utilization and spending.
Materials and Methods: Using 2010 commercial insurance claims data of >21 million individuals, we compared diagnostic imaging utilization and standardized payments between High Deductible Health Plan (HDHP) and non-HDHP enrollees. Negative binomial models were used to estimate associations between HDHP enrollment and utilization, and were repeated for standardized payments. A Hurdle model were used to estimate associations between HDHP enrollment and whether an enrollee had diagnostic imaging, and then the magnitude of associations for enrollees with imaging. Models with interaction terms were used to estimate associations between HDHP enrollment and imaging by risk score tercile. All models included controls for patient age, sex, geographic location, and health status.
Results: HDHP enrollment was associated with a 7.5% decrease in the number of imaging studies and a 10.2% decrease in standardized imaging payments. HDHP enrollees were 1.8% points less likely to use imaging; once an enrollee had at least 1 imaging study, differences in utilization and associated payments were small. Associations between HDHP and utilization were largest in the lowest (least sick) risk score tercile.
Conclusions: Increased patient cost-sharing may contribute to reductions in diagnostic imaging utilization and spending. However, increased cost-sharing may not encourage patients to differentiate between high-value and low-value diagnostic imaging services; better patient awareness and education may be a crucial part of any reductions in diagnostic imaging utilization.
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Bria Giacomino et al.
American Journal of Cardiology, forthcoming
Abstract:
Although prices for medical services are known to vary markedly between hospitals, it remains unknown whether variation in hospital prices is explained by differences in hospital quality or reimbursement from major insurers. We obtained “out-of-pocket” price estimates for coronary artery bypass grafting (CABG) from a random sample of U.S. hospitals for a hypothetical patient without medical insurance. We compared hospital CABG price to 1) “fair price” estimate from Healthcare Bluebook data using each hospital’s zip code and 2) Society of Thoracic Surgeons (STS) composite CABG quality score and risk-adjusted mortality rate. Among 101 study hospitals, 53 (52.5%) were able to provide a complete price estimate for CABG. The mean price for CABG was $151,271, and ranged from $44,824 - $448,038. Except for geographic census region, which was weakly associated with price, hospital CABG price was not associated with other structural characteristics or CABG volume (p >.10 for all). Likewise, there was no association between a hospital’s price for CABG with average reimbursement from major insurers within the same zip code (ρ = 0.07, p value = 0.6), STS composite quality score (ρ = 0.08, p value = 0.71), or risk-adjusted CABG mortality (ρ = -0.03 p value = 0.89). In conclusion, the price of CABG varied more than 10-fold across U.S. hospitals. There was no correlation between price information obtained from hospitals and the average reimbursement from major insurers in the same market. We also found no evidence to suggest that hospitals that charge higher prices provide better quality of care.
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Tami Gurley-Calvez et al.
Health Services Research, forthcoming
Objective: To examine the impact of a 2007 redesign of West Virginia's Medicaid program, which included an incentive and “nudging” scheme intended to encourage better health care behaviors and reduce Emergency Department (ED) visits.
Study Design: We utilized a “differences in differences” technique with individual and time fixed effects to assess the impact of redesign on ED visits. Starting in 2007, categorically eligible Medicaid beneficiaries were moved from traditional Medicaid to the new Mountain Health Choices (MHC) Program on a rolling basis, approximating a natural experiment. Members chose between a Basic plan, which was less generous than traditional Medicaid, or an Enhanced plan, which was more generous but required additional enrollment steps.
Principal Findings: We found that contrary to intentions, the MHC program increased ED visits. Those who selected or defaulted into the Basic plan experienced increased overall and preventable ED visits, while those who selected the Enhanced plan experienced a slight reduction in preventable ED visits; the net effect was an increase in ED visits, as most individuals enrolled in the Basic plan.
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The Impact of the Medicare Hospital Readmission Reduction Program in New York State
Brian McGarry, Albert Blankley & Yue Li
Medical Care, February 2016, Pages 162–171
Background: Medicare’s Hospital Readmission Reduction Program (HRRP) created clear financial incentives for hospitals to prevent readmissions. Although existing evidence suggests readmission rates have been declining, the direct contribution of this policy to these reductions is unclear. Furthermore, it is unknown whether HRRP has produced unintended effects, including the substitution of outpatient hospital care for readmissions.
Research Design: Difference-in-difference estimation using prepolicy and postpolicy hospital claims data and the proportion of a hospital’s inpatient revenue at risk for HRRP penalization to identify policy exposure. Policy effects are estimated using multivariate logistic regressions.
Results: We find significant global reductions in readmissions in the postpolicy years, but no evidence of a differential policy effect on patients discharged from hospitals at risk for proportionally larger HRRP penalties in either postpolicy year 1 [adjusted odd ratio (AOR) =1.00, P=0.733] or 2 (AOR=1.01, P=0.315). HRRP did increase the odds of patients from hospitals facing greater financial risk having a 30-day ED visit in both postpolicy years (AOR=1.04, P=0.009 and AOR=1.07, P<0.001).
Conclusions: Our findings suggest that while readmissions have decreased in New York State, these declines may not be directly attributable to HRRP penalties. The policy did produce significant potentially unintended effects in the form of greater postdischarge ED utilization among facilities facing proportionally larger penalties.
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Why Are Obstetric Units in Rural Hospitals Closing Their Doors?
Peiyin Hung et al.
Health Services Research, forthcoming
Data Sources: Hospital discharge data from Healthcare Cost and Utilization Project's Statewide Inpatient Databases, American Hospital Association Annual Survey, and Area Resource File for 2010, as well as 2013–2014 telephone interviews of all 306 rural hospitals in nine states with at least 10 births in 2010. Via interview, we ascertained obstetric unit status, reasons for closures, and postclosure community capacity for prenatal care.
Principal Findings: Exactly 7.2 percent of rural hospitals in the study closed their obstetric units. These units were smaller in size, more likely to be privately owned, and located in communities with lower family income, fewer obstetricians, and fewer family physicians. Prenatal care was still available in 17 of 19 communities, but local women would need to travel an average of 29 additional miles to access intrapartum care.
Conclusions: Rural obstetric unit closures are more common in smaller hospitals and communities with a limited obstetric workforce. Concerns about continuity of rural maternity care arise for women with local prenatal care but distant intrapartum care.