Evaluation of a Prescription Outlier Detection System in Hospital’s Pharmacy Services

Prescription review is a complex task performed by clinical pharmacists in a hospital environment. In this paper, we present the development and hospital’s pharmacy evaluation of an open-source decision support system for clinical pharmacy called NoHarm.ai. The system relies on an unsupervised algorithm based on graph structure that ranks outliers prescriptions. We deployed the decision support system for clinical pharmacy in a 1,200-bed hospital. NoHarm.ai can correctly classify, with an average of 84% of F-measure, the dose and frequency (posology) of several medications in the real-scenario application improving the work of the hospital’s pharmacists.