Why Some Health Policies Don't Make Sense at the Bedside

When cost-effectiveness analysis, decision analysis, and other forms of health policy analysis were first introduced as tools for clinical decision making, some physicians complained that the quantification the analyses required was artificial, simplistic, and dehumanizing [1-4]. Perhaps some of these concerns have been overcome, because these analyses are becoming more common in the medical literature and are increasingly influential in the development of health policy and clinical guidelines. Nevertheless, many clinicians find these analyses difficult to apply during individual encounters with patients. Concerns about these analyses take many forms. One common concern stems from the recognition that patients can vary widely in their preferences, and, thus, that analyses using an average set of goals may not represent the interests of all patients. Another concern is that analyses that include monetary inputs, such as cost-effectiveness analyses, are difficult to apply to individual patients, who usually face a personal cost that differs from the cost used for the analysis. A third concern is that the interests of society are often distinct from those of individual patients and, thus, that some policies developed to further societal goals can seem ill-suited to some patients' interests. These limitations of policy analysis are, in general, well understood. In this paper, however, we discuss a fourth, more subtle, interpretation of clinicians' concerns. Medical decisions appear to be less risky from the perspective taken in a policy analysis than they do from the perspective taken by physicians, patients, and other decision makers who must apply policy at an individual level. Even if all patients have similar values and preferences, the individual effect of costs can be adequately measured, and the goals of society are aligned with those of individual persons, policy analyses can inadequately reflect the risks faced by individual patients. This is because policy analyses focus on the outcomes of groups rather than on the outcomes of individual persons. Because clinicians treat patients one at a time, this difference in perspective can make the results of policy analyses difficult to apply and may explain the gap sometimes seen between health policy and clinical practice. We believe that this problem helps to explain the intuitive concern that many physicians have about policy analyses, and that it calls into question the value of these analyses in shaping clinical practice. Although there has been some discussion in the medical literature of differences between individual and group perspectives, much of this discussion has focused on the ways in which outcomes are framed or the manner in which information is presented [5]. Deber and Goel [6] have discussed some of the failings caused by presenting only central tendenciesa common practice when outcomes are presented from the population perspectivebut the implications of these concerns for clinical policy analysis are not generally well understood. Managing Risk in Financial Settings Every medical decision entails the chance that something will go wrong or that a different choice would have been better. Similarly, when an investor buys stock, there is always the chance that the price will fall or that a different investment would have done better. Investment risks provide a model for understanding the risks faced by physicians and patients in medical settings. Consider a person with $10 000 and a choice between investing in a stock or a bond. Both investments are likely to provide some return, but both have some risk, as shown in Figure 1 (top). The stock has an expected return of $700 $600; the bond has an expected return of $600 $100. Despite the higher return expected from the stock, individual investors might prefer the bond because it has lower variance. Figure 1. Distribution of potential dollar returns for investments in stocks or bonds assumed to be normally distributed. Top. Middle. Bottom. An investor can reduce financial risk by creating a portfolio of investments. Because each stock or bond is unlikely to move in lockstep with other stocks or bonds in the market, variations in investment performance will tend to offset each other. The benefits of diversification are illustrated in Figure 1 (middle); the fund represented is assumed to have 100 investors, each contributing $10 000. Assuming that there are no administrative costs, a 100-stock fund would yield an expected return of $70 000; a 100-bond fund would yield an expected return of $60 000. The risk faced by the fund as a whole depends on the correlation in performance among the stocks and among the bonds. When investments are not perfectly correlated, the risk faced by the fund is reduced. Figure 1 (middle) shows the outcome for the hypothetical case of independent returns. The distribution of potential returns is much narrower and less risky because the stocks and bonds move independently, and so poor performance of some stocks or bonds is offset by the better performance of others. A fund investing in 100 stocks can attract individual investors who dislike risk and would therefore not invest in only 1 stock. Individual investors can enjoy these benefits because they share in the risk reduction achieved by the portfolio. The distribution of returns back to individual investors is shown in Figure 1 (bottom), which is identical to that shown in Figure 1 (middle) except in scale. Managing Risk in Health Care Settings The principles discussed above are basic to financial markets and represent well-understood mechanisms for managing risk in investment settings. The practices of some large-animal veterinarians use the same kind of risk reduction in a health care setting. For example, a dairy farmer might consider attempting to increase the aggregate milk production of a herd of cattle by altering the herd's feed or by using hormonal manipulation. The interventions carry some risk because each cow might or might not respond with a greater return of milk. An intervention with a higher potential return but higher variance might be rejected for a single cow but accepted for a large herd. As long as the outcomes of the individual cows in the herd are not perfectly correlated, decreases in the dairy outputs of some cows might be offset by increases in the outputs of others, and so the intervention might be less risky than it would be if applied to a single cow. Just as an investor reduces risk by purchasing several stocks that react differently to market forces, a dairy farmer can reduce risk by considering the herd to be a diversified portfolio of cows that may react differently to any given health intervention. Do Health Policy Analysts Treat People Like Cows? The principles underlying portfolio theory are appropriate for investors or dairy farmers but may not be appropriate for decisions about human health. In particular, the assumption that outcomes faced by individual persons can offset each other effaces the moral distinction between these persons [7]. We argue that conventional approaches to policy analysis often make this error: They take a societal perspective and inadvertently assume a redistribution of outcomes to individual persons that cannot be achieved. Suppose you are invited to play a game in which a fair coin is tossed. If it lands heads up, you receive $100. If it lands tails up, you must pay $50. How much would you be willing to pay to play such a game once? The expected value of the game is $25 (a 50% chance of gaining $100 and a 50% chance of losing $50). Because of the chance of losing $50, however, some might pay less than $25perhaps $10for the opportunity to play this game once. They pay a price lower than the expected value to compensate for the chance of losing. How much would you be willing to pay to play the game 100 times? The expected value of playing the game 100 times is $2500 (100 x $25), but those willing to pay only $10 to play the game once might be willing to pay much more than $1000 to play the game 100 times. Although each flip of the coin is just as risky, the group of 100 independent coin flips is much less risky. (Under certain conditions, rejecting the opportunity to play once for anything more than $10 would imply that one must reject the opportunity to play 100 times for anything more than $1000 [8, 9]. Nevertheless, playing once seems riskier, and perceptions may be as important as reality.) To the extent that people like to be compensated for assuming risk, they should pay different amounts per game if they are playing the game once or 100 times [10]. Many health policy analyses treat risky interventions like coin flips. In costbenefit and cost-effectiveness analyses, for example, the expected benefits and burdens of a medical strategy are assumed to be distributed uniformly over the population [11]. The risk to each person, however, is greater than the risk perceived from an aggregate perspective because each person is unlikely to bear the average burden and receive the average benefit [12]. When you flip a coin 100 times, you care not about the outcome of each flip but about the average outcome. When you recommend a medical intervention 100 times, however, you ought to care about the outcome in each case. In neglecting the distribution of outcomes across individual persons, health policy analysts implicitly treat human populations in the same way that veterinarians treat herds of cattle, which is to say that they see them as an opportunity to diversify. Financial Risk and Health Risk In investment settings, financial returns are easy to redistribute equitably among investors. In health settings, however, redistributions of clinical outcomes are unattainable. Makers of health policy may be able to put individual patients into a common financial risk pool, but they usually cannot put them into a common health risk pool. The inability to offset risks between