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.     

Analysis of the Expected Resources of Copper Scrap

In this article, the expected resources of copper scrap in the Russian Federation have been analyzed, and their amounts and use through 2035 have been estimated. The conclusion on reducing the supply of copper scrap resources in the country in the mid-term prospects as a result of the change in based on the scrap generation and notable decline in the copper consumption in the country since the 1990s has been explained. In addition, the possible presence of uncollected scrap reserves, which may ultimately affect the operations of producers of copper and copper-containing products and lead to increased competition over the raw materials on the market, has been assessed and analyzed.