The state of Oregon decided to cover all potentially eligible Medicaid citizens to 100% of poverty. Previously, Oregon had covered persons up to 67% of poverty. In order to keep overall program costs in check. Oregon decided to limit the number of services that its Medicaid program would cover. Oregon's normative choice was to contain program costs by covering all eligible persons up to 100% of poverty, while at the same time uniformly limiting access to certain services for everyone in the overall group of eligible persons. The state developed a prioritization list of medical services and priced the components on the list. The amount of money ultimately available for the Medicaid program was a political decision informed by data about the cost of different services and influenced by the priorities set through an independent process of priority-setting. Physicians were asked to determine what works medically, how well it works, and what benefits accrue to patients. Recognizing that physician perspectives on efficacy might vary from patients' perspectives on valuation of benefits, Oregon's planners developed a method for valuing medical outcomes that stemmed from particular medical interventions. This blend of medical fact and value to patients allowed for comparing valuations by introducing cost considerations. Condition-treatment (CT) pairs linked a medical condition with one or more courses of treatment. The goal was to determine the likely incremental medical benefit from a given treatment. In addition, Oregon developed a Quality-of-Well-Being scale to determine the net patient benefit from medical intervention and used a telephone survey to value that net benefit. A cost-benefit ratio was derived, and a prioritization of CT pairs was developed. The article analyzes and evaluates Oregon's use of cost-benefit calculations in the allocation of Medicaid funds, noting that Oregon itself backed away from many of the implications of its cost-benefit analysis and that the Americans with Disabilities Act has constrained use of quality-of-life judgments in Medicaid resource allocation decision-making.