A decision support system to improve the efficiency of resource allocation in healthcare management

Limitations in healthcare funding require hospitals to find more effective ways to utilize resources. An effective patient management system is critically dependent on the accurate analysis of individual patient outcomes and resource utilization. In the current paper, a management-oriented decision support model is thus proposed to assist health system managers in improving the efficiency of their systems. In the first stage of the model, the key variables affecting system efficiency, as well as their causal relationships, are identified through causal maps. Efficiency is measured by the total time spent in the system. In the second stage, a Bayesian Belief Network (BBN) is employed to represent both the conditional dependencies and uncertainties of the key variables. In the third stage, a sensitivity analysis is performed using a BBN to determine the most critical variable(s) in terms of impact on the system. Finally, strategies to improve system efficiency are proposed. The suggested decision support system is applied to the tomography section in the radiology department of a private hospital in Turkey.