We propose to hone the tools of clinical decision analysis to make them applicable to complex management choices faced by clinicians at the bedside. The unique Clinical Decision Analysis Consultation Service constitutes a laboratory for the development of such tools and for the training of physicians because patients referred for detailed analysis provide an array of actual clinical choices that other physicians have found to be a conundrum. Our techniques already allow physicians at this institution to use logical, formal analyses in their practice. Among those tools are bedside algorithms for calculating decision thresholds, techniques to assist in the elicitation of patient values, simple techniques for the application of Bayes rule to interpret clinical data, and a microcomputer program which performs the full gamut of sensitivity analyses. These funded projects, as well as our Training Program in Clinical Decision Making, are now threatened by decreases in project budgets. This application seeks funding to continue these activities. We shall continue to operate our consultation laboratory and report its case material in a format useful to researchers and educators. We shall expand our microcomputer-based sensitivity analysis program to incorporate sensitivity analyses during Markov simulations and the concept of the threshold band of indifference, formally bringing sensitivity analysis to the concept of the "toss-up." We shall continue to enrich the tools of utility acquisition, making them more practical and avoiding well-known and recently elucidated cognitive biases. We shall implement certain bedside analytic tools on programmable calculators and shall examine factors which encourage and discourage their use by house staff. We shall also enhance our preliminary model for estimating life expectancy in patients facing competing risks of death. Finally, we shall collect, in a readily distributable form, a database of quantitative information relevant to modeling complex choices in individual patients. These investigations will increase the availabiltiy of logical tools for managing complex patients. By providing the clinician with techniques for integrating and evaluating the vast array of data and opinions which arise in such patients, this research will contribute to the twin goals of increasing the quality and trimming the cost of medical care.