As health care costs continue to rise, governments and private payers are being forced to make difficult coverage decisions about new health care treatments. Cost-effectiveness (CE) analysis is the main method used to prioritize this spending. The self-evident efficiency rationale for CE is that resources should be spent where they have the highest health impact. This has led to perhaps the largest field in health economics which attempts to provide better estimates of value through CE analysis. However, the costs invariably used in CE analysis are prices set by producers rather than resources used to produce treatments. Therefore, observed CE levels are endogenous because the pricing of new technologies is chosen to maximize profits. This is important because optimal prices, and hence observed CE levels, are affected by demand factors such as patient/doctor demand and payer adoption policies. This implies that traditional measures of "costs" reflect these demand-determined mark-ups rather than resource costs and moreover, CE-based reimbursement policies affect the endogenous CE levels payers observe. Reimbursement based on endogenous CE may therefore bear little relationship with efficient use of scarce medical resources. Using data from technology appraisals by the National Institute for Health and Clinical Excellence (NICE), we test for conditions under which adoption based on standard CE analysis may lead to adoption of more inefficient technologies in terms of resource use.
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New medical technologies are often argued to be a leading force behind the growth in health care spending. In order to manage the costs imposed by such technologies and to prioritize health care dollars, both public and private payers have increasingly relied on combined measures of the benefits and costs of new technologies. These measures include cost-effectiveness, cost-utility, or cost-benefit analysis, hereafter referred to collectively as CE analysis.
It is self-evident that payers should attempt to maximize the returns in health they obtain from the limited resources available for health spending. Thus, CE analysis offers an important means to allocate scarce health care budgets, whether privately or publicly funded.
CE thresholds, which dictate that a given technology will be reimbursed only if the incremental costs per quality-adjusted life year (QALY) they provide are below a given threshold, is one way in which CE-based adoption is implemented in practice. The most prominent examples are the UK's National Institute for Clinical Excellence (NICE) and Australia's Pharmaceutical Benefits Advisory Committee. As a consequence of the extensive use of CE analysis by payers, an enormous health economics literature has developed and shown the conditions under which CE analysis, when applied under a fixed budget constraint, can lead to gains in static efficiency. Indeed, the amount of work done on the CE of medical technologies may perhaps be the largest field within health economics, particularly in European countries where such analysis guides a large share of public spending.
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Tomas J. Philipson is a visiting scholar at AEI.
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