Resource allocation in the intensive care unit

Introduction

Two truisms of economics are that the supply of goods and services is finite and that supply is never sufficient to meet all demands. The tension between supply and demand for food, water, energy, education, and other goods and services creates economies. All societies must determine how goods and services will be allocated to individuals. Although the term rationing connotes a specific process of allocation during circumstances of severe resource limitation (for example, rationing coupons to allocate gasoline during World War II), rationing is just a synonym—an emotionally laden synonym—for resource allocation. In this chapter the terms are used interchangeably. Although rarely recognized as such, rationing decisions occur every day in all aspects of medicine. Critical care services are uniquely poised to raise difficult questions about allocation. First, this high-technology, labor-intensive area of health care is a major driver of rising healthcare costs. Second, the evidence for many intensive care services, including the evidence for admission to the intensive care unit (ICU) itself, is limited. Finally, the decision not to provide intensive care services compared with, for example, the decision not to get magnetic resonance imaging (MRI) for low back pain or not to provide antibiotics for an apparently viral respiratory infection is a rationing decision with an identifiable life in the balance.

Market-based economies allocate many resources on the basis of ability to pay, but other strategies exist ( Table 162.1 ). In developed nations, some goods and services—for example, health care and education—are treated differently than luxury goods and are allocated by society using criteria other than an individual’s purchasing ability. Because medical resources are finite, it is impossible to provide every effective treatment in every case where it might offer benefit and the patient desires the care. That does not mean that clinicians are aware on a daily basis of the burden of this reality. Sometimes the decisions are explicit with immediate repercussions—for example, the selection of one patient to receive a heart transplant when several might benefit from the sole available organ—or the decision to admit one patient to the last ICU bed when several patients are critically ill who would benefit from ICU admission. More frequently, the decisions are subtle and occur even when the supply of the therapy is not absolutely limited (e.g., the decisions to use cheaper antibiotics, sedative medication, imaging modalities, or nursing ratios) when more expensive options might be beneficial or, more frequently, the decision to use an ICU bed in cases of small benefit (e,g., observation of low-risk surgical patients for complications). Finally, allocation decisions can be completely implicit and almost hidden because they occur at a system level. For example, the decision to build an ambulatory care clinic instead of adding ICU beds is an allocation decision with profound implications for the delivery of critical care services that is nearly hidden to the individual clinician.

Although common and necessary, allocation decisions are stigmatized in medicine. Allocation decisions bring two major ethical principles into conflict. The principle of beneficence guides clinicians to act solely in their patient’s best interests, whereas the principle of justice directs clinicians to act fairly. This conflict may explain why euphemisms are frequently used to describe decisions that are essentially decisions to ration resources. For example, “triage,” “optimization,” “prioritization,” “cost-effective,” “waste,” and “basic health care” all indicate some form of allocation decision. The purpose of this chapter is to explore these decisions in their many guises as they occur in critical care and to offer some guidance to the clinician for constructing processes for allocating resources in their ICU.

Allocation versus evidence-based medicine

Decisions based solely on the evidence of efficacy of medical care are not rationing decisions. There is no medical obligation to provide and no societal obligation to pay for care that is harmful or ineffective. In fact, clinicians use special terms to describe interventions that fall into these categories, including “futile,” “not standard of care,” “medically inappropriate,” “wasteful,” or “experimental.” ^, For example, an intensivist who decides not to transfuse a critically ill patient with blood with a hemoglobin of 73 g/L is not rationing blood even though blood is an expensive and limited resource because there is evidence that this transfusion in many critically ill patients is of no benefit and may be harmful. The decision not to use human growth hormone, an expensive medication, in chronically critically ill patients is not a rationing decision because this treatment has not been shown to be effective and may be harmful.

Unfortunately, the assessments of benefit and harm are not as straightforward as the terms would suggest, and the line between effective, ineffective, and experimental often lies in the eyes of the individual clinician. Decision science has taught us that medical decision making is a complex process that frequently obscures the true rationale of the choice. In fact, judgments allegedly based solely on objective evidence of safety and benefit often incorporate a variety of subjective values and biases. These may include the value the clinician assigns to being wrong; the value assigned to trying to “rescue” a patient in imminent danger of death; the clinician’s tolerance for uncertainty; the impact of the decision on the clinician’s finances; biases about the patient’s race, gender, functional status, or age; and the cost or availability of the resource. These transitions from statements that summarize the evidence of benefit to recommendations that incorporate cost and other values are often very subtle. This is particularly problematic for many treatments in critical care where there is an absence of evidence of efficacy, no clear harm, and, for individual clinicians, strong beliefs about efficacy. For example, the authors of a recent systematic review of colloid resuscitation in critical care conclude that “there is no evidence from randomized controlled trials that resuscitation with colloids reduces the risk of death compared with crystalloids in patients with trauma, burns and following surgery.” This is a statement of their summary of evidence of efficacy. Like many treatments in critical care, the evidence neither supports nor completely refutes the use of colloids as resuscitation fluids in the critically ill. However, the authors conclude, “As colloids are not associated with an improvement in survival, and as they are more expensive than crystalloids, it is hard to see how their continued use in these patient types can be justified outside the context of randomized controlled trials.” Although the first statement may be a fair summary of the evidence, the recommendation against using colloids in the second sentence is fundamentally a rationing or allocation assessment based on cost-effectiveness. It incorporates an implicit strategy that only recommends treatments that have demonstrated benefit related to their cost. One might conclude from the authors’ review that colloid resuscitation is experimental or that its benefit is likely to be small; however, the reasoning for recommending against its use is based on the cost of the treatment. Presumably, if colloid fluids were the same price as crystalloids, the authors might reach different conclusions even though the cost does not change the evidence of efficacy.

The preceding example shows how assessments of cost can creep into evidence-based recommendations for therapy even without formally discussing allocation. Because clinicians and payers may be reluctant to admit that they are incorporating cost or availability into the rationale for a decision, they may find decisions of futility or appropriateness less ethically problematic than rationing. In fact, these judgments may implicitly contain assessments of cost by incorporating cost into the definition. Because scientific studies can never statistically prove a therapy is ineffective, when is there sufficient evidence to move a treatment or diagnostic device from experimental care to standard care? Does this distinction matter if the person is paying for their own care or if it is paid for by a third party? Given the statistical challenges of proving inefficacy, when is there sufficient evidence, in the absence of demonstrated harm, that a treatment is ineffective as opposed to not yet of proven efficacy? These decisions are frequently made by consensus bodies using subjective or poorly characterized criteria but usually avoiding an explicit assessment of cost. In 1989 the Oregon Health Plan attempted to extend healthcare benefits to more people by creating a prioritized list of health benefits—essentially rationing care. To develop this list, the Oregon Health Services Commission was convened. It ranked treatments by their effectiveness from therapy for acute head injury with loss of consciousness (#1), anal fissure (#579), and hepatorenal syndrome (#743, near the bottom) and funded them in order based on available resources. Interestingly, although treatments were selected based on funding and the overall process was essentially a rationing plan based on cost-effectiveness, the rank list itself was not particularly correlated with formal cost-effectiveness assessment, indicating that other, potentially subjective, factors took precedence.

At the bedside, clinicians also tend to subtly incorporate cost into their assessment of evidence-based recommendations. The amount of evidence required to convince clinicians to adopt treatments that are risky or expensive will always be more than treatments that are safe and cheap. For example, consider the decision to elevate the head of the bed of mechanically ventilated patients to prevent ventilator-associated pneumonia. Although the evidence supporting its effect on reducing mortality or ICU length of stay is limited, it is inexpensive and safe and has become part of routine ICU care. Conversely, kinetic beds, topical prophylactic antibiotics, and special endotracheal tubes, which are more expensive and may raise safety issues, have had considerably less uptake despite evidence supporting their use.

Judgments about the evidence-based efficacy of treatments that are supposed to be independent of cost are further complicated by the motivation of the decision maker. It would be difficult for an insurance company that is assessing whether a specific therapy is experimental or standard of care to be unbiased when its decisions affect its profits. Alternatively, surgeons who developed a procedure may be committed to its benefits in a way that compromises an objective evaluation. The complexity of the assessment of efficacy and costs points to the importance of making allocation decisions as objective, explicit, and public as possible.

Allocation strategies

Given that an intervention is effective, clinicians will face decisions to allocate resources at the bedside. These decisions are usually separated into macro-allocation decisions (involving groups of people and usually made at a managerial or health policy level) and micro-allocation decisions (made at the bedside and involving identifiable specific cases). A hospital’s decision not to hire additional ICU nurses is a macro-allocation decision. A nurse manager’s decision to allocate a specific patient to share a nurse in the ICU rather than to receive 1:1 nursing is a micro-allocation decision. This chapter is primarily concerned with bedside allocation, or micro-allocation decisions, which clinicians make on a routine basis. There is an important interaction between micro- and macro-allocation decisions because macro-allocation decisions ultimately affect individuals, and macro-allocation regulations are an effective strategy for implementing allocation ( Table 162.2 ).

There are a number of approaches to allocating resources (see Table 162.1 ). Although these are all feasible, they are not all equally ethical. The principles of equality, fairness, justice, and due process make some strategies less acceptable. The principle of utilitarianism directs resource allocation to maximize the “utility,” or benefit, of the most people for any given amount of resources. To the extent that “utility” can be measured by measuring patient outcomes like health-related quality of life and to the extent that we can estimate the effects of medical treatments on utilities, we can theoretically calculate exactly which set of medical treatments to pay for to maximize the benefit to the population. These studies are called cost-effectiveness analyses and are the quantitative realization of the philosophic theory of utilitarianism. Allocating medical resources through cost-effectiveness analyses has important limitations. First, medical cost-effectiveness analyses cannot tell how much money to allocate to medical as opposed to other goods and services, just how to maximize health outcomes for any selected outlay of resources. Second, cost-effectiveness analyses may not fully account for some factors that society values. For example, cost-effectiveness analysis routinely treats all human lives as equally valuable; however, society often places a very high value on identifiable lives in imminent danger of death and may not value additional years of life in the elderly as much as years of life in the young. Cost-effectiveness and other utility-based allocation strategies fail to account for the value society places on rescuing lives in imminent peril—a not uncommon occurrence in the ICU. Standard economic analyses may not value equal distribution as much as optimal distribution and, to this end, may discriminate in settings that society finds unacceptable. Finally, cost-effectiveness analysis is a mathematical technique that generates comparative outcomes for populations of patients rather than an evaluation in single cases. It is worth pointing out that the term cost-effective is frequently misused both in informal clinical conversation and in the literature. It is incorrect to speak of a treatment as being “cost-effective” without a comparator. Cost-effective does not necessarily, and actually rarely, means cost saving. Cost-effective does not necessarily mean the least expensive or the most effective of treatment options.

Cost-effectiveness analysis is a methodology that provides a ranking of treatments, which provides someone who has the authority to make decisions with the information to compare various strategies. For example, one can compare the cost-effectiveness of captopril versus no captopril in survivors of myocardial infarction with using fluoxetine versus imipramine for major depression to decide whether to use captopril, fluoxetine, both, or neither. Cost-effectiveness analyses provide a ruler, a shared metric, usually in terms of dollars per life-year or dollars per quality-adjusted life year (QALY) that allows treatments to be compared with allocation (rationing) decisions on which treatments to provide when all effective treatments cannot be paid for. Valid cost-effectiveness ratios require an estimate of a numerator (the cost of one therapy compared with another) and a denominator (the effect of the therapy on survival or quality of life). Without evidence of effectiveness from randomized trials, estimates of cost-effectiveness are problematic and must be modeled on other data. Although we have data in critical care on strategies to reduce gastrointestinal bleeding, duration of mechanical ventilation, and ICU-acquired infections, the number of treatments that can demonstrate an improvement in QALYs is very limited. Therefore the denominator for cost-effectiveness analyses in critical care can frequently only be expressed as dollars per event: for example, dollars per gastrointestinal bleed or ventilator-associated pneumonia prevented. These ratios, sometimes referred to as cost-benefit analysis, cannot be used to compare a treatment to prevent gastrointestinal bleeding with a treatment to prevent catheter-related infections or with a treatment to improve weaning because they are all expressed with different denominators. Cost-effectiveness analyses with non-QALY denominators can be helpful in bedside rationing decisions when the intervention is known to be safe and equally or more effective and reduces cost. For example, special beds in the ICU have been shown both to prevent decubitus ulcers and to reduce the overall costs of care even when the cost of the bed is factored in. Therefore the cost-effectiveness ratio, expressed in dollars per decubitus ulcer prevented, is a negative number.