The Oxford Handbook of Health Economics (2)

Oxford Handbook

Here’s the first post about the book. If you want to know what I’ve been doing over the last few days, look at the red thingy. I’ve read roughly 700 pages so far. Book-blogging takes time, so I’ve been emphasizing reading over blogging.

This book covers a lot of stuff. There’s a lot more in there than I can justify covering here. That said, in a way I also feel that it’s necessary to note how little stuff the book actually covers: In more than a few chapters I’ve added remarks such as, ‘this topic is covered in much more detail in Juth and Munthe‘, or ‘for a much more comprehensive review, see Goldstein’s book‘. The book also covers stuff covered in greater detail here, here and here; as mentioned before I know a bit about these things already, though I haven’t felt like I’ve really had a great overview of the material. Having read books like this one, this one or perhaps this one may help understand some issues presented in specific chapters better, but you don’t really need to have done that – in most cases the chapters can stand on their own. I should mention that in one specific chapter (about addiction) I basically wrote in the margin at one point that the authors didn’t seem to know what they were talking about here, and that they should familiarize themselves with the medical- and neuroscientific research on the stuff they’d written about there (addiction) before writing any more stuff on that (specific) subtopic. It wasn’t a big part of the chapter though, and that has only happened once; most chapters are great, and none are what I’d really term ‘weak’ – I’m currently at either four or five stars on goodreads, probably a little bit closer to five than four. I should note that I have had similar ‘these guys don’t seem to know a lot about what the non-economists have found out about this stuff’- experiences as I had when reading the addiction chapter previously a few times when covering labour economics topics during my coursework; sometimes it seems to me that economists who’re very fond of their models (and the models of their antecessors) don’t really have a clue what’s really going on because they refuse to learn what people in other fields have already found out (perhaps because they assume that related work will not help them in their model-building efforts? (…if so, I think they’re wrong)) – it always bothers me.

Anyway, some observations from the book below:

Infectious diseases:

“From an economist’s perspective, infectious diseases are distinguished from many other health issues by the central role played by externalities.1 Control of infectious diseases yields both positive externalities (prevention and treatment can delay or reduce spread of infection to uninfected individuals) and negative externalities (overuse of treatment can lead to drug resistance, which has global consequences for treatment effectiveness). […] vaccination, an important tool in the prevention of infectious diseases, presents a classic public goods problem. Society gains from individual vaccination because of herd immunity, but this value is not recognized by individuals, who have an incentive to free-ride on vaccination by other individuals. […] disease reporting and eradication efforts are also public goods. […] a country’s incentives to control a freely moving disease like malaria are determined as much by its ability to stop the inflow of infected individuals as by the ability to control the disease within its own borders. Reducing malaria in a country could have transboundary benefits by incentivizing infection control in its neighboring countries as well. This principle also applies more generally to the challenge of global disease eradication. […] Eradication is a binary public good: the maximum benefits are achieved when the disease is completely gone.”

“Together, all infectious diseases account for more than 25 percent of premature death globally.”

“In sum, obtaining accurate information about potential epidemics is as much about reporting incentives as it is about detection technology.”

“from an economic perspective, disease burden may be a poor criterion to use for allocating treatment resources.”

Mental health:

“(OECD) nations commonly spend between 5 percent and 14 percent of their health dollar on mental health care […] this implies that OECD countries devote between 0.3 percent and 1.1 percent of their national incomes to treatment of mental disorders.2 […] It is important to note that the patterns of spending on mental health care are different from those observed in international comparisons of health care spending. […] there is more variation in mental health spending levels across nations than there is for health care. […] The commitment by OECD countries to promote community-based treatment and inclusion of people with mental disorders into the mainstream of society while also accepting the responsibility for public protection creates a policy tension that […] shapes public mental health spending. […] there have been notable reductions in the inpatient psychiatric capacity in virtually all OECD countries [since the 1960s]. […] [There is] growing variation in how each society sees the function of the psychiatric hospital. […] in France and the United States, two countries that spend similar shares of GDP on mental health care, France allocates roughly 80 percent of mental health spending on inpatient care (Verdoux 2007) and the United States about 36 percent (Mark et al. 2007). […] Mental health spending in the US as a share of total health spending has declined from nearly 11 percent in the 1970s to 6.2 percent in 2003”

“Cost-effectiveness evaluations of evidence-based treatments for depression suggest that they produce gains in Quality Adjusted Life Years (QALYs) at levels comparable to other medical treatments […] rates of treatment for the mental disorders, with some of the strongest effectiveness of care evidence, such as depression and anxiety disorders, are quite low […] mental health services are frequently funded and/or supplied by several bureaucratic departments all operating under fixed budgets. […] There may therefore exist opportunities for cost shifting. That is, strict rationing of mental health services may be seen as an opportunity to expand monies available for general medical care while allowing people with mental disorders to obtain care from the social care sector. […] recently the creation of combined trusts (mental health and social care) has tried to use organizational design to blunt incentives to cost shift created by fragmentation in financing.”

Public sector health care financing:

“In general, it can be shown to be efficient for the consumer’s cost-share to be lower when he or she incurs large health care costs, but higher with relatively low costs. This can be accomplished via a plan with an initial deductible (under which consumers are responsible for 100 percent of their health care costs in a given period of time, up to the limit of the deductible), followed by one or more intervals of partial cost sharing, perhaps up to some maximum (a “stop-loss” provision) beyond which the plan pays 100 percent of any additional costs. […a related observation from another chapter: “In the pure theory of insurance, Arrow (1963) showed that, with proportional administrative loading, optimal coverage is full coverage above a deductible” – this result is called ‘Arrow’s theorem of the deductible’ and lots of people have written stuff about that one] […] The theoretical analysis of the efficient degree of consumer cost-sharing has focused on the trade-off between the gain from more complete insurance against the associated inefficiency of over-utilization, but in practice, the appropriate degree of cost-sharing should also depend on certain other factors, in particular, on the relative costs of administering plans with different degrees of cost-sharing. […] Patient cost-sharing as a means of controlling health services utilization and aggregate health care costs is an example of what in the health economics literature is called “demand-side incentives” (that is, incentives that affect the patients who use health services). A prominent theme in the health economics literature in recent years has been that services utilization and total health care spending in a given population also depend strongly on the incentives of the providers of health services who treat the patients and advise them on what services they should utilize (“supply-side incentives”). If utilization can be effectively controlled through supply-side incentives, the case for high user fees is less strong”

“In comparing the equity and efficiency properties of the social insurance model of funding health care with the general-revenue financing model, the first point that should be made is that, for those populations for which membership in the public plan is compulsory (which may be the entire population), the contributions that the insured are required to pay toward funding the plan […] are equivalent to a tax. […] This equivalence has two important consequences. First, it means that the equity and efficiency properties of the social insurance system can only meaningfully be analyzed as part of the overall system of raising government revenue for all purposes: As previously argued, it is not meaningful to separately analyze the equity and efficiency properties of the revenue raised for some particular purpose. In this sense, therefore, social insurance funding of health care involves the same issues as those arising when funding is from general revenue. Second, once it is recognized that the contributions paid into the social insurance system is only one of many sources of government revenue, it becomes clear that it is not in general efficient to match the revenues raised from this source with a particular kind of spending (health care). If one wants to explain why many countries still try, at least to some extent, to match health care expenditures under their public plans to specific types of revenue (such as social insurance contributions), one must appeal to other factors […], not economic efficiency or equity.”

Health care cost growth:

“The dominant factor contributing to rising spending is the development and diffusion of new medical technology […] The conclusion that technology is a primary driver of cost growth is based on a wide body of literature […] Alarm over health care cost growth is typically centered on the rise in health care expenditures at the population level. Expenditures reflect both unit costs (prices) and utilization patterns (quantities). Some interventions may reduce unit prices, but, because of the utilization response, may not reduce expenditures. […] This helps explain why innovative technology often raises expenditures in the health care sector, even though it is perceived to lower cost in other industries. For example, as technology reduced unit cost in the information technology sector, spending growth in the overall sector increased 26 percent annually from 1982 to 1996 (Haimowitz 1997). Expenditures are also not limited to any particular disease. Individuals cured of one disease inevitably get another. It is possible that reductions in expenditures on one disease may increase overall spending if competing conditions are more expensive. Finally, cost growth at the population level may not reflect trends in cost growth for particular services. Efforts to constrain spending in one area may simply generate greater spending in other areas. For example, in the United States, as inpatient spending growth slowed following implementation of prospective payment systems (PPS), outpatient spending soared (Miller and Sulvetta 1992).”

“In assessing cost containment strategies it is crucial to distinguish between those interventions that affect the trajectory of cost growth versus those that affect the level. […] This distinction is important in assessing the ability of systems which are more conservative in their adoption of new technology to control cost growth. A system that adopts new technology more slowly than another system may have the same rate of cost growth if the baseline level of costs is lower. For example, if a given country has a base spending rate that is 20 percent below that of another country, it will experience the same cost growth if it utilizes a new technology 20 percent less frequently.”

“decreased utilization associated with cost sharing does not disproportionately impact necessary care, as proponents of cost sharing would hope and standard economic theory would predict. Patients apparently reduce use of appropriate and inappropriate care in similar proportions […] Consistent with this view, many recent studies suggest patients reduce use of prescription drugs when faced with modestly higher copayments […] cost sharing has been demonstrated to have disproportionately negative effects on the quality and delivery of health care among low-income populations […] Adverse events, lower adherence, and decreased management of illness are associated with increased patient cost sharing […] the longer term consequences on health associated with lower utilization of high value services have yet to be fully evaluated. […] Because cost sharing is associated with lower costs, many health care payers view cost sharing as a means to reduce growth in health care (Chernew 2004). Yet there is virtually no evidence examining the impact of cost sharing on cost growth. It is possible higher cost sharing lowers spending, but does not alter the trajectory of spending growth. […] Although the debate about the relationship between physician and hospital supply and spending and costs will continue, it is important to note that much of this literature is related to the level of costs, not the trajectory. The limited evidence on cost growth suggests that even in the most successful settings […] the share of GDP devoted to health care still rises, albeit at a somewhat slower rate than in other markets.”

“Many observers have noted that the health care expenditures of individuals with chronic disease are much greater than expenditures of individuals without such disease […] The share of obese Medicare beneficiaries increased from 9.4 percent in 1987 to 22.5 percent in 2002 […] For this reason, some believe that initiatives aimed at improving health will save money. […] [However] most preventive services are not cost saving from a societal perspective. […] In general […] evidence of […] savings associated with disease management and pay for performance is weak. […] it is likely too optimistic to assume that better health will substantially lower the trajectory of health care spending. Health care costs were growing rapidly well before the epidemic of obesity and health care cost growth among the healthy persists. […] Because healthier beneficiaries live longer, and may demand a range of quality of life improving services, it would not be prudent to assume that better health, as desirable as it is, will substantially slow cost growth.”

February 6, 2014 - Posted by | Books, Economics, Health Economics, Infectious disease, Medicine, Psychology

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