Combining expert judgment by hierarchical modeling: an application to physician staffing

Article Abstract:

The decisions of individual experts can converted in a group decision through Bayesian hierarchical models. This technique is demonstrated in determining the number and kinds of doctors to be employed at medical centers managed by the Dept of Veteran Affairs (VA). The supra-Bayesian strategy is used for estimating the kind of uncertainty that is related to a panel's analysis of the number of doctors needed under certain situations. Hierarchical models are appropriate for these kinds of conditions because variability in the experts' decisions is partly affected by heterogeneity in their baseline experiences at various VA medical centers. Alternative hierarchical Bayes synthesis distributions are then calculated for the number of doctors needed for the daily workload in internal medicine at a particular VA center.

Administration of Veterans' Affairs, Veterans Hospitals & Medical Care, Decision-making, Decision making, Management, Usage, Medical centers, Bayesian statistical decision theory, Bayesian analysis, Military health services, United States. Department of Veterans Affairs

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Removing a Self-Inposed Restriction in Modelling Heirarchical Decision Processes

Article Abstract:

Models of decision-making in multi-level hierarchical systems are fairly common. However, the structures require that the system be pyramidal. This restriction is not necessary. A diagram of a pyramidal and non-pyramidal hierarchy is included.

Management science, Decision theory, Hierarchical Organization, Decision Models, Decision Making

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