Terry F Urbine1, Philip J Schneider2. 1. Associate Research Scientist and Instructor, Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy , Phoenix, Arizona . 2. Professor and Associate Dean, Department of Pharmacy Practice and Science, University of Arizona College of Pharmacy , Phoenix, Arizona .
Abstract
BACKGROUND: Preventing intravenous (IV) preparation errors will improve patient safety and reduce costs by an unknown amount. OBJECTIVE: To estimate the financial benefit of robotic preparation of sterile medication doses compared to traditional manual preparation techniques. METHODS: A probability pathway model based on published rates of errors in the preparation of sterile doses of medications was developed. Literature reports of adverse events were used to project the array of medical outcomes that might result from these errors. These parameters were used as inputs to a customized simulation model that generated a distribution of possible outcomes, their probability, and associated costs. RESULTS: By varying the important parameters across ranges found in published studies, the simulation model produced a range of outcomes for all likely possibilities. Thus it provided a reliable projection of the errors avoided and the cost savings of an automated sterile preparation technology. The average of 1,000 simulations resulted in the prevention of 5,420 medication errors and associated savings of $288,350 per year. The simulation results can be narrowed to specific scenarios by fixing model parameters that are known and allowing the unknown parameters to range across values found in previously published studies. CONCLUSIONS: The use of a robotic device can reduce health care costs by preventing errors that can cause adverse drug events.
BACKGROUND: Preventing intravenous (IV) preparation errors will improve patient safety and reduce costs by an unknown amount. OBJECTIVE: To estimate the financial benefit of robotic preparation of sterile medication doses compared to traditional manual preparation techniques. METHODS: A probability pathway model based on published rates of errors in the preparation of sterile doses of medications was developed. Literature reports of adverse events were used to project the array of medical outcomes that might result from these errors. These parameters were used as inputs to a customized simulation model that generated a distribution of possible outcomes, their probability, and associated costs. RESULTS: By varying the important parameters across ranges found in published studies, the simulation model produced a range of outcomes for all likely possibilities. Thus it provided a reliable projection of the errors avoided and the cost savings of an automated sterile preparation technology. The average of 1,000 simulations resulted in the prevention of 5,420 medication errors and associated savings of $288,350 per year. The simulation results can be narrowed to specific scenarios by fixing model parameters that are known and allowing the unknown parameters to range across values found in previously published studies. CONCLUSIONS: The use of a robotic device can reduce health care costs by preventing errors that can cause adverse drug events.
Entities:
Keywords:
drug contamination; medication errors; patient safety