To get around this criticism, some might propose building into summary population measures “moral weights” that reflect our preferences or values when we take a stand on these distributive problems. Their goal, perhaps, might be to develop an ethically sensitive tool or decision procedure. Planners could then use it with fewer moral qualms in different resource allocation contexts, perhaps substituting “objective” calculation for “subjective” moral deliberation.

I believe that the unsolved nature of these morally contested rationing problems poses a serious obstacle to this strategy. For reasons I develop, we must view these measures and the methodologies that use them—or even highly improved versions of them—as inputs into a fair and deliberative decision making process. Our goal must be better informed and ethically sensitive deliberators making decisions, not methodologies that substitute for them.

To that end I urge a two-pronged research program. One prong explores social attitudes toward the distributive problems that must be addressed in making these resource allocation decisions. For example, Eric Nord’s (1994) “person trade-off” approach explicitly asks people how many health outcomes of one kind (e.g., moving patients from one health state to another) they consider equal in social value to outcomes of a different kind. This approach avoids inferring an answer to this question from the very different question people are asked in standard summary measures, where they assign a personal utility to them of being in one state rather than the other. If developed further in directions Nord suggested, the person trade-off approach could help us learn more about how our society, or subgroups in it, reason about these issues. Serious obstacles confront this approach, however. Nord himself recognized some, and I note others. Still, properly pursued, it might provide an important body of information that could assist decision makers who must allocate resources.

The second component of the research program explores the requirements of a fair decision making process in the different contexts in which resource allocation decisions must be made. I make some preliminary suggestions about some elements of such a process, but much more work needs to be done. Decision makers constrained by such a fair process could then use information from summary health measures, CEA, and information about the attitudes and reasoning people use to think about these distributive issues to arrive at decisions others should view as legitimate and fair.

This argument has a brief history. Five years ago, at an international bioethics conference in Amsterdam, I claimed that the absence of principled solutions to these rationing problems means that we need to develop an account of fair procedures for resolving them (Daniels, 1993). Nord, speaking in the same session, replied that his person trade-off method can tell us how the public solves these problems and gives us a way to produce an instrument that incorporates the values underlying these solutions (Nord, 1993, 1994). I objected then that his method—which Brock and I believe asks the right questions—could not substitute for moral deliberation for various reasons. I continue that line of reply here, but I embrace the effort he makes to find out more about our beliefs about these distributive issues.

Early in 1993, the Public Health Service Panel on Cost-Effectiveness Analysis in Health and Medicine began its deliberations about the role and limits of CEA, and the argument I offer here was one of the considerations that led it to recommend that CEA should be viewed as an input to decision making and not a decision making procedure (Gold, Siegel, et al., 1996; Russell, Gold, et al., 1996). Unfortunately, simply making that recommendation without providing more assistance in helping us make these controversial, distributive decisions risks letting people give too much weight to the distributive implications of CEA. Even imperfect or distributively



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement