Healthcare fraud involves wide-ranging illegal behaviors. It includes such activities as individual physicians who bill insurance companies or the government for services that were never provided, as well as corporate behavior, such as pharmaceutical companies that falsify clinical tests in order to get unsafe drugs approved for use. Thousands die each year in the United States due to these behaviors, including deaths from incorrectly prescribed medications or from tainted drugs that were approved by the U.S. Food and Drug Administration based upon fraudulent testing and reporting. Thousands of additional patients likely are injured and killed by unnecessary surgeries performed by physicians who want to maximize their reimbursements. The illegal activities also add billions of dollars each year to the total healthcare cost in the U.S. Despite these costs, there is relatively little outrage as a result of the behaviors, largely because they remain hidden from public view. Healthcare fraud, as with almost all white-collar crime, is rarely detected and that prevents the frauds from becoming known to victims, law enforcement, and policy makers, which in turn prevents analysts from compiling a complete picture of the behaviors and prevents policymakers and law enforcement from developing efficient enforcement strategies. Moreover, the lack of detection assures perpetrators that they will get away with their crimes and limits the potential preventative effects of punishment. Lack of detection and reporting has been a particularly strong problem for those trying to control healthcare fraud and abuse in the United States and elsewhere. The enforcement mechanisms that have evolved have been strongly influenced by the difficulties of detecting the illegal behaviors.
Paul Jesilow and Bryan Burton
Courtney Van Houtven, Fiona Carmichael, Josephine Jacobs, and Peter C. Coyte
Across the globe, the most common means of supporting older disabled adults in their homes is through “informal care.” An informal carer is a family member or friend, including children or adults, who help another person because of their illness, frailty, or disability. There is a rich economics literature on the direct benefits of caregiving, including allowing the care recipient to remain at home for longer than if there was no informal care provided. There is also a growing literature outlining the associated costs of care provision. Although informal care helps individuals with disabilities to remain at home and is rewarding to many carers, there are often negative effects such as depression and lost labor market earnings that may offset some of these rewards. Economists have taken several approaches to quantify the net societal benefit of informal care that consider the degree of choice in caregiving decisions and all direct and indirect benefits and costs of informal care.
Martin Karlsson, Tor Iversen, and Henning Øien
An open issue in the economics literature is whether healthcare expenditure (HCE) is so concentrated in the last years before death that the age profiles in spending will change when longevity increases. The seminal article “aging of Population and HealthCare Expenditure: A Red Herring?” by Zweifel and colleagues argued that that age is a distraction in explaining growth in HCE. The argument was based on the observation that age did not predict HCE after controlling for time to death (TTD). The authors were soon criticized for the use of a Heckman selection model in this context. Most of the recent literature makes use of variants of a two-part model and seems to give some role to age as well in the explanation. Age seems to matter more for long-term care expenditures (LTCE) than for acute hospital care. When disability is accounted for, the effects of age and TTD diminish. Not many articles validate their approach by comparing properties of different estimation models. In order to evaluate popular models used in the literature and to gain an understanding of the divergent results of previous studies, an empirical analysis based on a claims data set from Germany is conducted. This analysis generates a number of useful insights. There is a significant age gradient in HCE, most for LTCE, and costs of dying are substantial. These “costs of dying” have, however, a limited impact on the age gradient in HCE. These findings are interpreted as evidence against the red herring hypothesis as initially stated. The results indicate that the choice of estimation method makes little difference and if they differ, ordinary least squares regression tends to perform better than the alternatives. When validating the methods out of sample and out of period, there is no evidence that including TTD leads to better predictions of aggregate future HCE. It appears that the literature might benefit from focusing on the predictive power of the estimators instead of their actual fit to the data within the sample.