Simulation Modeling and Analysis
Simulation Modeling and Analysis
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In cost effectiveness studies variables associated with organization and available capacity may affect the overall results. The influence of the variation of these variables on the cost effectiveness can be evaluated by computer simulation following a carefully designed experimental design. This combination provides a means to examine a full range of possible scenarios. This was done to calculate the cost-effectiveness for the implementation of a new screening strategy for detecting developmental dysplasia of the hip (DDH). First current workflow and performance is analyzed. Then, important output factors are identified and alternative scenarios are determined with the use of experimental variables with according levels. For the determination of the levels literature and interviews among stakeholders are used. The 4 experimental variables are the location of the consult, integrated with regular consult or not, the number of US machines and the discipline of the screener. In total 72 possible scenarios are identified. 'Possible' means that they can be evaluated with the simulation model. In our model the experimental variables related to the number of US machines in combination with an extra consult is influencing the cost effectiveness the most. The combination of a simulation model and an experimental design greatly enhance cost effectiveness studies where organizational and capacity variables are important. Relevant information to determine the levels of experimental variables can be extracted from the literature and directly from experts. Using an experimental design a priori exploration of how variables affect the outcome is possible and as a result different strategies for implementation can be explored