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In general, most human physiological organs systems, which are constructed by collecting more than one part to perform either single or multiple functions. In addition, the successive times between failures are not necessarily identically distributed. More generally, they can become smaller (an indication of deterioration). However, if any organic deterioration is detected, then the decision of when to take the intervention, given the costs of diagnosis and therapeutics, is of fundamental importance. At the time of the decision, the degree of future human organic deterioration, which is likely to be uncertain, is of primary interest for the decision maker (for example, determining the prevalence of disease, doing a population survey, or measuring the level of a toxin). This paper develops a possible structural design of decision support systems by considering the sensitivity analysis as well as the optimal prior and posterior decisions. The proposed design of Bayesian decision support systems facilitates the effective use of the computing capability of computers and provides a systematic way to integrate the expert’s opinions and the sampling information which will furnish decision makers with valuable support for quality decision-making.