Anesthesia and Pain Management Drug Cost Reduction while Maintaining Adequate Patient Care

Methods to potentially reduce pain management and anesthesia drug costs were analyzed in this study. A non-linear programming model was developed to accept intravenous, transdermal patch, and oral pain medications as inputs to generate a cost-minimized dosing recommendation. The non-linear programming model was constrained by the maximum non-lethal dose for each drug and a popular pharmacodynamic equation to determine the probability of no response. An autoregressive moving average (ARMA) technique was used to develop a forecasting model for one patient's historical bispectral index data. The ARMA technique fits the bispectral index data well and generated accurate forecasts of patient sedation five minutes ahead; however, it requires a significant amount of data collection. A moving average technique is proposed to generate forecasts while the autoregressive technique collects sufficient historical data points. The non-linear programming model successfully identified local cost-minimized dosing recommendations assuming a set of hypothetical medication properties. Further blood-work analysis must be conducted to ascertain true drug property values for drugs used in pain management and to permit implementation.