HOPE VERSUS EFFICIENCY IN ORGAN ALLOCATION¹

Abstract

Previous ethical analyses of organ allocation policies have addressed the trade-off between giving organs to urgent versus non-urgent patients, overlooking the process by which patients become urgent in the first place. This article proposes three criteria for assessing the performance of organ allocation rules that take into account the dynamic nature of patient health. An equitable policy is one under which patients’ probability of receiving a transplant is equal at listing. Efficiency captures the goal of giving organs to patients when their benefit from transplantation is greatest. Hope implies that patients should believe that they have a reasonable chance of receiving an organ. The sickest first policy, which is currently used to prioritize patients, is hope-preserving, but may be inefficient. As demand grows relative to supply, patients will only receive an organ once they have reached the sickest status category.

The allocation system for lifesaving organs in the United States and elsewhere is based on the rule of rescue, which holds that life expectancy absent of treatment should be the primary determinant of who receives scarce medical resources. It was with this principle in mind that the Clinton administration proposed over 2 years ago to eliminate regional preferences in organ allocation and institute finer grading of patients’ medical status ⁽¹⁾. The proposals, particularly the former, have been the subject of intense controversy in the transplant community ever since.

Opponents of the administration have criticized national allocation on the grounds that it would direct more organs to sicker patients and hence lower aggregate success rates. For the most part, however, the debate has centered on parochial issues, and a much-needed reexamination of the rule of rescue as a basis for organ allocation has not taken place. This is unfortunate; given the continued growth of organ demand relative to supply, it is important to step back and consider whether current allocation policies, which were put into place under a very different environment and have only been modified slightly since their inception, continue to satisfy societal objectives.

Previous attempts to establish an overarching framework for rationing decisions have focused on the ethical principles of justice, fairness, and utility. This article defines three criteria—efficiency, equity, and hope—and argues that they provide a more constructive guide for structuring debates over allocation policy. Unlike the standard ethical criteria, they take into account the dynamic nature of patient health. The outcome of a given rationing policy depends not only on who gets treated but when they get treated as well ⁽²⁾. These principles, when applied to the problem of how to allocate livers, show that the current sickest-first policy performs well in terms of giving wait-listed patients hope, but that, by delaying transplantation, the sickest first policy may lead transplant recipients to have poorer outcomes than if they underwent transplantation immediately after listing.

PREVIOUS ANALYSES OF ALLOCATION RULES

Arguments in favor of the sickest-first rule are typically grounded in the ethical principle of justice. Burdick et al. ⁽³⁾ write, “Justice might also partially explain why we might give priority to a patient for whom death was imminent without transplant.” Likewise Ubel and Caplan ⁽⁴⁾ write, “Many theories of justice are based on the notion that the people in greatest need deserve special priority, even if they benefit less than other people.”

Ethicists and transplant surgeons are not dogmatic in their application of justice to organ allocation; some argue that retransplantation should be curtailed based on the principle of utility ⁽⁵⁾. Nevertheless, most agree that the principle of justice dictates that patients on the waiting list be prioritized by medical urgency.

The problem with standard motivations for the sickest-first rule is they begin by assuming that patients are either “urgent” or “non-urgent”; they do not account for how patients become urgent in the first place. Of adult, first-time liver recipients who underwent transplantation in 1997, 86% were placed on the waiting list in status 3 (the least urgent category). Only 49% underwent transplantation in status 3—well over a third were moved to more urgent categories. Table 1 shows that similar patterns hold for other measures of patient health. For example, half of all patients working at the time of listing stopped working by the time they received their transplant. The loss of health that patients experience on the waiting list is not an accident but rather a direct consequence of the sickest-first prioritization rule. In a dynamic setting, patient health and patient prioritization are jointly determined. A rule that assigns organs to sicker patients will cause more patients to become sick as they wait for a transplant.

Table 1: Adult, first-time recipients who underwent transplantation in 1997

The loss of health that patients experience on the waiting list is a function of the scarcity of organs. In seeking universal principles of rationing, previous analyses often ignore the difference between situations of temporary treatment shortage and situations, such as the organ waiting list, where demand permanently exceeds supply. In the former, the sickest-first rule may be justified in terms of both justice and utility. When a treatment shortage is permanent, however, use of the sickest-first rule can have unintended consequences. As the waiting list grows relative to treatment supply, the percentage of patients receiving treatment in a non-urgent state will decline. Eventually, patients will receive treatment only after they have reached the sickest status category, at which point their ability to survive transplantation is diminished. Although the liver waiting list has not yet reached this point, it is approaching it. As shown in Figure 1 the number of people waiting for a liver transplant is growing exponentially, as an increasing number of patients are placed on the list every year and patients who have not received a transplant continue to wait. Parallels made in the national press between liver allocation and emergency room triage, where demand only temporarily exceeds supply, do not stand up to scrutiny ⁽⁶⁾. A better analogy would be the heart transplant waiting list, where 75% of heart recipients in 1998 were in the most urgent category at the time of transplantation, up from 55% in 1991 ⁽⁷⁾.

Figure 1: The gap between organ demand (represented by the top line) and organ supply (represented by the bottom) has grown over time. Patient wait list years equals the number of patients on the list at the beginning of the year plus one-half times the number of patients entering or exiting the list during the year. These data are taken from the 1997 Report of the Organ Procurement and Transplantation Network.

DYNAMIC EVALUATION CRITERIA

Allocation as a Two-Stage Process

Allocating organs should be viewed as a two-stage process ^(8,9). In the first stage rules screen out patients who are undeserving or are unlikely to receive a significant benefit from transplantation. Standard ethical approaches are ideal for addressing the questions raised in this stage, because the characteristics used to exclude patients (for example, advanced age) generally are unchanging over time. The second stage entails assigning the limited supply of organs to eligible patients. Obviously there is some connection between the first and second stages; the stringency of first-stage policies will determine the organ shortfall in the second ⁽¹⁰⁾. For reasons discussed above, however, the second stage is properly separated from the first because of the dynamic nature of patient health. Second-stage policies must not only choose between giving organs to urgent or non-urgent patients but must also try to prevent patients from reaching the most-urgent category in the first place. Below I propose three criteria that can be used to judge second-stage allocation policies. Like the standard ethical principles, they do not provide an unequivocal ranking of allocation rules. However, they are well suited for framing the trade-offs that must be faced by policymakers when choosing between alternative methods of prioritizing patients on transplant waiting lists.

Efficiency

All else being equal, allocation policies should provide organs to patients when their benefit from transplantation is greatest. To illustrate, consider Figure 2, which plots the net gain from transplantation as a function of waiting time. The point of greatest benefit is probably before a patient becomes sick but may be well after his physician detects the precursors to liver failure. [There is substantial disagreement on the optimal timing for liver transplantation in the literature ^(11–16)]. Hence the hypothetical benefit curve is not uniformly decreasing but rather increasing after diagnosis and then declining. A policy is efficient if patients undergo transplantation at time t*, the point at which the net benefit curve reaches its maximum.

Figure 2: Net benefit of transplantation as a function of waiting time.

Note that the principle of efficiency is different from the standard ethical principle of utility. If there is one organ and two patients need a transplant, the principle of utility dictates that it should be given to the younger, healthier patient. The principle of efficiency makes no such recommendation; it only requires that whoever receives the organ get it at a point when he derives the most benefit from it.

The underlying rationale for the efficiency criteria is that no allocation policy should entail a dead weight loss. In economic terms a dead weight loss is a loss of welfare by one person that does not accrue to another. Consider an organ recipient who undergoes transplantation after his point of maximum benefit. The patient would have been made better off and no one else worse off if instead the patient had undergone transplantation a week earlier (the patient would benefit from undergoing transplantation in a healthier state, and the net loss to other patients would be zero because the patient uses one and only one organ in either case). The decline in health experienced by the patient during the week is a dead weight loss and would be prevented under an efficient policy.

Equity

A policy is equitable if, at the time of listing, the probability of eventually receiving a transplant is equal across patients. An inequitable policy is one under which a patient placed on the waiting list in a relatively sick state has a much lower probability of receiving a transplant than a patient placed on the waiting list in a healthy state. This is not to say that the probability of receiving a transplant must be equal across patients after listing. Some patients will remain in their initial health status or even improve, while others will deteriorate. As long as these events are essentially random and unrelated to patients’ health status at listing, however, the equity criterion is not violated.

The equity principle as defined above is based on the belief that once patients are deemed sufficiently healthy to be considered for treatment, policy should not favor one class of patients at the expense of another ⁽¹⁷⁾. To the extent that regional allocation results in differential access to transplantation, it is inequitable. In the case of patient health, patients should not be penalized for being diagnosed late in the course of their disease relative to patients diagnosed earlier. At the same time, patients’ status will change for reasons that are unpredictable, and it is beyond the scope of allocation policy to try to compensate for these changes, given that organs are an indivisible good.

Hope

Hope is formally defined as deriving pleasure or utility from a delay in the resolution of uncertainty. Practically this means that a wait-listed patient will be happier knowing that he has a chance of receiving a transplant than if he is told immediately that he will or will not get an organ. This also applies to a patient’s family and society at large; we seem to place a high value on avoiding situations where an otherwise healthy individual knows with certainty that he will experience an untimely death, especially when the means exist to prevent that death. A recent survey of public preferences for liver allocation policies found that responders were willing to allocate a portion of organs to older and sicker recipients even when they felt that, overall, the allocation system should direct organs to patients with the greatest potential to benefit ⁽¹⁸⁾. The value of hope is one possible explanation for this apparent contradiction. Likewise, researchers have documented preferences for hope in studies where participants were asked to choose between immediate versus future disclosure of the results of a monetary lottery ⁽¹⁹⁾.

Obviously there are limits to how far the concept of hope can be applied to an allocation scheme. Some patients may prefer early resolution of uncertainty to delay, especially if knowing the outcome of the allocation process changes their time horizon with respect to financial decisions. Wait-listed patients who develop conditions that render them poor candidates for transplantation should be removed from the waiting list, even if this means that they lose hope. Likewise elderly patients may be denied access to the waiting list, even if they are healthy compared to their peers.

A wait-listed patient will lose hope if his probability of receiving a transplant in the future falls below some critical level. Together equity and hope imply that all patients should start out with an equal probability of receiving an organ, regardless of initial health, and that, although the likelihood of eventually receiving a transplant may vary with patients’ health levels over time, it should always be high enough to preserve hope.

Other Principles

Efficiency, equity, and hope are not the only criteria that an allocation system should satisfy. Two others are legitimacy and honesty. Legitimacy holds that the public, on whose generosity the transplant system depends, should accept and understand the allocation system. Legitimacy may explain why first-come first-served queues are so often used to allocate resources ⁽²⁰⁾, even when other mechanisms would be more efficient. Honesty implies that an allocation system should not encourage physicians to distort medical decisions or misreport information to the allocator. The current system has been criticized on both these grounds ⁽¹⁾. Because hospitalized patients have a higher priority, physicians may base their site-of-care decisions on nonmedical factors. Also, physicians may overexaggerate the severity of patients’ liver disease so that they can be placed on the waiting list to accumulate waiting time. Monitoring and stricter standards can help to limit gaming, but generally it is preferable to have a system that induces rather than coerces honesty.

LIVER ALLOCATION AS A CASE STUDY

Applying the principles listed above to several benchmark rationing rules for liver allocation can illustrate their usefulness and limitations. Consider an allocation system in which every patient receives a single lottery ticket upon listing and organs available on a certain day are assigned by some random mechanism to the patients who turned in their lottery ticket the day before. Assuming that individuals place a high value on life expectancy, they would redeem their lottery tickets when transplantation would do them the greatest good. This is at point t* in Figure 2. Hence, the lottery system described above, where the choice of when to enter the lottery is determined by the patient and his physician, is efficient. Also it is equitable; every patient receives one ticket. Sick patients can choose to enter the lottery as soon as they are listed, while healthy patients may prefer to wait.

The problem with a lottery system like that described above is that it is not hope-preserving. A patient who enters the lottery and loses has zero probability of receiving an organ in the future. Of course patients who value hope highly can always choose to wait to redeem their ticket right before they die, but few are likely to pursue such a strategy. Under the lottery system, the probability is constant until the patient uses the ticket at time t*. It is zero afterwards for patients who do not receive an organ at t*.

The sickest-first policy represents another extreme. Once the waiting list increases beyond a critical point, patients will receive a transplant only after they have reached the sickest health level. Hence one can think of the sickest-first policy as analogous to a lottery where patients are entered in the lottery once they become “sickest” rather than at the time of their choosing. Because the probability of receiving a transplant is always above zero, even on the last day of a patient’s life, the sickest-first policy is hope-preserving. It is equitable for the same reason.

The literature on the optimal timing of transplantation does not provide a definitive answer to the question of whether the sickest-first policy is efficient. However, if faced with an unlimited supply of organs it is difficult to imagine a surgeon waiting until a patient is in an intensive care unit to perform transplantation (indeed this was not the practice in the early days of transplantation when organs were plentiful). Given the significantly lower graft success rates of patients who undergo transplantation in status 1 or 2A instead of status 3, it seems fair to conclude that optimal time for transplantation is before patients reach the sickest category (as shown in Fig. 2) and that the sickest-first policy is inefficient. In choosing between the sickest-first policy and a lottery in this case, society faces a trade-off between hope and efficiency.

CONCLUSIONS

Although not all countries use as detailed an urgency classification system as the United States, all employ some variant of the sickest-first rule to allocate livers and other lifesaving organs. Outside of transplantation, the sickest-first rule is used to prioritize patients in crowded emergency rooms, disaster-relief shelters, and countries with nationalized health systems. [Although the popular press often writes of “waiting lines” in Canada and Britain, it is usually the case that patients in dire need of treatment are moved to the head of the queue ⁽²¹⁾]. Lotteries and other mechanisms have been used to ration treatment at various times ⁽²²⁾, but the sickest-first rule seems to predominate.

That the sickest-first rule is so widely used suggests its intuitive appeal and, possibly, the value of hope in societal preferences. Can we then assume that the sickest-first rule is the right one to use for allocating organs? Not necessarily. The current organ waiting list, with its large and growing gap between organ demand and organ supply, is different from other clinical situations and from the organ waiting list a decade ago, when the sickest-first rule was first put into place. Under conditions of severe shortage, the sickest-first rule may be very inefficient, resulting in organ wastage and excessive morbidity.

Ultimately policymakers may decide that, despite its efficiency losses, the sickest-first policy is preferred over a lottery, waiting line, or any other feasible prioritization rule. If this is the case, the policy should be defended not on the grounds that it is just but rather because it preserves the hope of patients on the waiting list. It is natural to wonder, however, if there is any way to bridge the hope-efficiency trade-off. One possibility is to allow patients to choose at the time of listing between the present system and one in which they would receive a lottery ticket for an organ that could be turned in at the time of their choosing. Patients who value hope could choose the old system, while patients who value efficiency could choose the lottery. As long as organs are apportioned across systems so that the probability of eventually receiving a transplant does not depend on which scheme is chosen, this dual-system approach would be equitable while permitting greater expression of patient preferences.

Acknowledgments: I thank Joseph Newhouse, Katherine Swartz, Richard Frank, and Karen Donelan for helpful comments and advice.