| ABSTRACT
Health care costs in the United States are on the rise, propelled in part by the high costs of pharmaceuticals used by the aging national population. Attempts to control these spiraling costs have led to increasingly restrictive reimbursement policies, which has clear consequences for pharmaceutical companies' revenues Here we discuss existing strategies in decision-making models, ideas for improving pharmaceutical company decision-making models, and specifically the benefits of taking into account the changing nature of reimbursements in deciding which medical products and services to develop, produce, and offer. Future research directions are also discussed.
Keywords
Health care costs, economic analysis, pharmaceutical industry, rationing
1 INTRODUCTION Health care costs in the United States are on the rise to the extent that they are spiraling out of control. While in 2003 the United States spent 15.3% of its GDP on health care, that share rose to 18% in 2010 and will reach 26% of GDP by 2030. In the long run, this rate of growth is patently unsustainable. Consequently, the United States must contain these rising costs, which requires all components of its health care system become efficient and cost effective; pharmaceutical companies are by no means an exception. Since the US population is aging at an unprecedented rate, and older individuals consume far more drugs than younger persons, pharmaceutical companies are particularly vulnerable to efforts to contain costs. Pharmaceutical companies' pre-market drug testing efforts have historically focused on human safety and drug effectiveness. Changes in reimbursement policies on the part of insurance companies and governmental organizations suggests that this testing paradigm that precedes the release of drugs should evolve to include the utilization of marginal analysis of new drug developments that takes into consideration cost minimizing efforts, while utilizing marginal cost and marginal benefits of drug development, and to take these factors into account at an earlier stage in the decision-making model. While the calculation of marginal cost should take into consideration the additional costs of various resources used in the development of each new drug, benefits of those medications should be calculated in terms of qualify-adjusted life-years measurement - essentially a standardized means of determining life-extension and overall health benefit in a combined metric. This type of marginal analysis, typically used by economists, that also considers cost minimization efforts, would rule out new but expensive drugs that cannot provide much value to the users of these new drugs, who, for the most part, will consist of the elderly. Organizations that actually make and implement reimbursement decisions could benefit from a similar decision model (Wirtz et al., 2005). 2 DRUG DECISION-MAKING MODELS In nations outside of the United States, especially those with nationalized health care systems, a common means of determining whether to reimburse new drugs by means of cost effectiveness analysis. This analysis helps determine whether paying for a new drug is worth additional cost, in terms of life extension and quality-of-life enhancement, as compared with similar drugs on the market, and is expressed in terms of a quality-adjusted life years measurement ranging from 0 (the least healthy) to 1 (the most healthy) scale that enables of the comparison of benefits across different age and disease groups. To illustrate the utilization of this metric, decision-makers reimburse conditions with higher cost per quality-adjusted life years score (for example, treatment of AIDS would have a higher score than treatment for asthma). An accompanying component to economic decision-making for reimbursing organizations is a willingness-to-pay threshold. In other words, below a certain ratio of cost to life years/quality benefit, organizations will deem intervention not worth reimbursing, and recommend alternative courses of treatment (Shiroiwa et al., 2010). Within the United States, a widespread call to reduce health care spending along with more limited reimbursements by Medicare, Medicaid, and other organizations to be created by recent healthcare reform legislation places additional demands on pharmaceutical companies to introduce medicines with increased effectiveness and for seriously impairing diseases with few competitor drugs, but also to prepare to receive less reimbursement-based compensations for what they bring to market. Even outside the United States, governments are beginning to require, or introducing more restrictive standards on companies, to show empirical evidence that drugs are not only therapeutically effective, but cost-effective. Many governments utilize an incremental cost effectiveness ratio-driven decision model, based on the ratio of the increased cost of a particular therapy as compared to existing medicinal therapies, to the change in quality adjusted life-years. 3 CHANGING PRODUCTION DECISION MODELS Across the pharmaceutical industry, companies generally involves obtaining a drug license, at which point phase III trials are completed and drug outcomes can be analyzed effectively, and then analyzing reimbursements. It is proposed that pharmaceutical companies can benefit from instead determining cost-effectiveness during Phases I and II of clinical trials before drug licensing is obtained, by projecting cost and effectiveness using data on effectiveness of similar chemical compounds and similar interventions and studies on the disease (Hall et al, 2010). It is hypothesized that the projected cost-benefit analysis can in fact guide the conducting of Phase III trials, in terms of decisions regarding how to allocate funding as a function of revenue expectations based on projected reimbursements. Of course, this model would have to take into account exceptional cases such as when interventions that would be considered cost-ineffective by normal standards treats a debilitating disease that cannot be treated otherwise, or in the cases of drugs that are perceived as "vanity" treatments, or treat diseases afflicting a non-priority subset of patients, or simply a too-small subset of patients. Thus, other factors besides simple cost-effectiveness must be incorporated into the ideal decision-making model, including therapeutic value, the size of the population that could potentially benefit from the drug, strong outcomes (above existing averages) in clinical trials, and how burdensome the disease is to society as a whole as well as the individually-stricken patient. Yet another factor is encapsulated by the Pareto principle, which states that a socially optimal therapy is one that does no harm to anyone, and leaves one or more subsets of the population better off. 4 CURRENT AND FUTURE RESEARCH Given the fevered pitch at which lawmakers and those in the health care industry are clamoring for reform, the development and testing of decision-making models is particularly ripe for empirical research. One particularly attractive direction is a detailed computational analysis of how changing reimbursement practices introduced by Obama's recently-passed Health Care Reform bill will affect the optimal decision model described above for pharmaceutical companies, as well as the existing decision-making model. Besides the aforementioned complex factors beyond simple cost-effectiveness that should be taken into account in an ideal decision-making model, of particular interest to the author is the effects of age-based health care rationing - i.e., disproportionately weighting interventions that help young people versus treating people above a certain age (even beyond any such weighting that is implicit in the quality-adjusted life years metric), to bolster arguments in ethical debates about health care rationing proposed solutions in the United States and beyond. REFERENCES Hall, P.S. et al. 2010. Health Economics in Drug Development: Efficient Research to Inform Healthcare Funding Decisions. European Journal of Cancer. Shiroiwa, T. et al. 2010. International survey on willingness-to-pay (WTP) for one additional QALY gained: what is the threshold of cost effectiveness? Health Economics. Wirtz, V. et al. 2005. Reimbursement decisions in health policy - extending our understanding of the elements of decision-making. Health Policy. . |
Updated 03/19/2014