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Abstract
The treatment of human shock states, for example following major heart surgery, illustrates an important class of decision problems involving the timing of risky interventions on a critical system. A probabilistic model is outlined for use in deciding on the intervention time, t̂, which maximizes the probability of recovery. A closed-form expression for t̂ is obtained in an important special case where the probability functions of the model decline exponentially with time. The behavior of t̂ is analyzed in some detail and compared with that of simple suboptimal strategies. A number of extensions are considered, including more general utility structures. The discussion of unknown probability structures leads to a brief comparison with sequential decision procedures.
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