Multi-objective design of risk-adjusted control chart in healthcare systems with economic and statistical considerations

Abstract

Using control charts to monitor healthcare systems has gained particular attention. In this paper, a risk-adjusted cumulative sum control chart is designed to monitor surgery outputs. Before undergoing surgery, the patients have some unique risk factors which influence the surgery outputs. Thus, risk-adjustment is carried out with the purpose of taking these risks into account using an accelerated failure time model. But the technical implementation of the chart requires determining the design parameters which should be selected in an optimal way putting the desired statistical and economic considerations into service. To this end, a multi-objective model, considering multiple assignable causes with different occurrence rates and effects, has been proposed and the model is solved with the help of a 5-stage algorithm based on the data envelopment analysis method. Then, to show the performance of the proposed procedure, a real case study has been conducted in the cardiac surgery center. Finally, sensitivity analysis on some cost parameters has been conducted. Furthermore, comparisons of the proposed multi-objective model with the pure economic and pure statistical design models have been made. The results reveal that the multi-objective design of the risk-adjusted cumulative sum chart shows acceptable performance in the presence of multiple assignable.