Moral hazard in insurance, value-based cost sharing, and the benefits of blissful ignorance

129

118

In this paper, we explore the role patient incentives play in slowing healthcare spending growth. Evidence suggests that while patients do indeed respond to financial incentives, cost-sharing does not uniformly improve value; rather, cost-sharing provisions must be deliberately structured and targeted to reduce care of low marginal value. Other mechanisms may be helpful in targeting particular populations or types of utilization. The spillover effects between privately insured and publicly insured populations as well as market imperfections suggest a potential role for public policy in promoting insurance design that slows spending growth while increasing the health that each dollar buys.

Section: Value-based Design Value-based Designmentioning

confidence: 96%

“…Phelps and Mooney (1993) analyzed utilization of medical services are less clear. Phelps and Mooney (1993) analyzed utilization of common, and expensive, procedures in hospitals around the state of New York. of common, and expensive, procedures in hospitals around the state of New York.…”

Section: Cross-price Effects Cross-price Effectsmentioning

confidence: 99%

Patient Cost-Sharing and Healthcare Spending Growth

Baicker¹,

Goldman

2011

129

118

“…Pauly and Blavin (2008) and Baicker, Mullainathan, and Schwartzstein (2015) summarize evidence that people have a systematic propensity to under-or overuse certain treatments at the margin. For example, Choudhry et al (2011) document that many recent heart attack victims do not adhere to drug Handel and Kolstad (2015b) "Uninformed" consumers leave substantial dollars on table when "over-choosing" generous insurance coverage, relative to "informed" consumers.…”

Section: Consumer Ignorance and Misinformation In Health Marketsmentioning

confidence: 99%

“…Baicker, Mullainathan, and Schwartzstein (2015) argue that it is difficult to rationalize such examples in a framework where consumers accurately trade off health benefits against the copay. Others argue that consumer misinformation is likely a key reason why consumers act as if they misweight treatment benefits (for example, Pauly and Blavin 2008). These findings have important policy implications: in many cases, when consumers make poor health choices it both increases long-run health costs and reduces consumer health, and everyone loses.…”

Section: Health Treatmentmentioning

confidence: 99%

Frictions or Mental Gaps: What's Behind the Information We (Don't) Use and When Do We Care?

Handel

Schwartzstein²

2018

152

In a number of situations, there is strong evidence that people do not translate readily available information into the knowledge that would help them make better decisions. For example, people may choose a health insurance plan that costs $500 per year more in premiums in order to obtain a deductible that is $250 lower-despite having access to open enrollment booklets containing relevant information (Handel 2013;Bhargava, Loewenstein, and Sydnor 2017). People buy branded drugs over equivalent but less-expensive generics (Bronnenberg, Dubé, Gentzkow, and Shapiro 2015) even though information printed on the package reveals their equivalence. Investors pay a range of fees for investing in S&P 500 index funds-and index funds with higher fees have meaningful market shares (Hortaçsu and Syverson 2004). Consumers appear to demand the wrong cell phone plans given their previous usage patterns (Grubb and Osborne 2015).Why don't people use available information? The many possibilities discussed in the research literature broadly fall into two camps, which we refer to as frictions and mental gaps. The frictions camp focuses on costs of acquiring and processing information. A consumer shopping in a health insurance exchange incurs a cost to explore more of the options in the choice set and to assess them. This camp, and the closely related framework of "rational inattention," maintains the neoclassical assumption that people form accurate beliefs using the information that is worth

“…The uncertainty of medical spending gives rise to the demand for health insurance (Arrow, 1963); at the same time, the presence of moral hazard implies that full insurance is not optimal and consumers should remain liable for some spending through deductibles and/or coinsurance (Pauly, 1968). Exactly how much risk consumers should face in order to achieve an efficient outcome depends on both the price elasticity of demand for medical care and on the quality of their information about the effectiveness of different medical treatments (Chernew, Rosen, and Fendrick, 2007;Pauly and Blavin, 2008). In the real world, determining the optimal level of coinsurance is further complicated by the significant tax subsidy to employment-related health insurance, in which health insurance premiums paid by employers are not taxed as income to employees, an arrangement which very likely results in coinsurance rates that are suboptimally low for many people-that is, they face too little risk from an efficiency perspective (Feldstein, 1973;Feldstein and Friedman, 1977).…”

Section: How Much Medical Spending Risk Should Households Face?mentioning

confidence: 99%

The Evolution of Medical Spending Risk

Gruber

Levy²

2009

How has the economic risk of health spending changed over time for U.S. households? We describe trends in aggregate health spending in the United States and how private insurance markets and public insurance programs have changed over time. We then present evidence from Consumer Expenditure Survey microdata on how the distribution of household spending on health -- that is, out-of-pocket payments for medical care plus the household's share of health insurance premiums -- has changed over time. This distribution has shifted up over time -- households spend more on medical care and insurance than they used to -- but for the purposes of measuring change in risk, it is not the mean but the dispersion of this distribution that is of interest. We consider two measures of dispersion that serve as proxies for household risk: the standard deviation of the distribution of household health spending and the ratio of the 90th percentile of spending to the median (the so-called "90/50 gap"). We find, surprisingly, that neither has increased despite the rapid rise in aggregate health spending. This conclusion holds true for broad subgroups of the population (for example, the nonelderly as a group) but not for some narrowly-defined subgroups (for example, low-income families with children). We next consider how much risk households should face, from the perspective of economic efficiency. Household risk may not have changed much over the past several decades, but do we have any evidence that this level represents either too much or too little risk? Finally, we discuss implications for public policy -- in particular, for current debates over expanding health insurance coverage to the uninsured.