Anesthesia and Pain Management Drug Cost Reduction while Maintaining Adequate Patient Care
MetadataShow full item record
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.
autoregressive moving average