 To calculate the effectiveness of care resource utilization at the population level requires both resource costs and quality of life benefits to be aggregated in terms of the expected number of uses of each resource. A low-cost and low-benefit, but widely used resource will tend to rank as more efficient than a high-cost and high-benefit, but rarely used resource. This can lead to counter-intuitive results. For example, when the Oregon government tried to put into place a plan to lower Medicaid costs using CEA and QALY they began by identifying treatment/condition pairs—that is, types of treatments provided to patients with different kinds of health conditions—and from these created a rationing priority list in terms of expected QALY benefits from treatment. One of the consequences of the plan was that the treatment of capping teeth was far higher on the priority list than appendectomy, even though no one would die from uncapped teeth while untreated appendicitis could be lethal. The reason was obvious: you could pay for many hundred instances of teeth capping for the price of a single appendectomy, and adding up all of the small but non-zero QALY benefits from the capping would trump the QALY benefits of the appendectomy. This result was widely viewed as profoundly counterintuitive (although some argued that our intuitions are not always as clearly opposed to favoring aggregated benefits [Kamm 1993; Nord 1999]).