Extracting Daily Dosage from Medication Instructions in EHRs: An Automated Approach and Lessons Learned
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Understanding a patient's medication history is essential for physicians to provide appropriate treatment recommendations. A medication's prescribed daily dosage is a key element of the medication history; however, it is generally not provided as a discrete quantity and needs to be derived from free text medication instructions (Sigs) in the structured electronic health record (EHR). Existing works in daily dosage extraction are narrow in scope, dealing with dosage extraction for a single drug from clinical notes. Here, we present an automated approach to calculate daily dosage for all medications in EHR structured data. We describe and characterize the variable language used in Sigs, and present our hybrid system for calculating daily dosage combining deep learning-based named entity extractor with lexicon dictionaries and regular expressions. Our system achieves 0.98 precision and 0.95 recall on an expert-generated dataset of 1000 Sigs, demonstrating its effectiveness on the general purpose daily dosage calculation task.
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