Abstract
Obtaining patient medication histories during emergency department (ED) admissions is an important step towards identifying potential errors that could otherwise remain in the patient's active medication list. This is a descriptive report of a standardized, electronic data collection tool created to document potential medication errors in patients receiving high-risk medications during ED admissions. Trained pharmacy technicians completed a survey following medication history collection using a secure web platform called REDCap®. Data collected included patient-specific information, the number and type of high-risk medications, and potential medication errors identified in the collection process. During a pilot period of April 2019 to October 2020, 191 patient records were completed using the survey tool. Out of a total of 1088 medications recorded, 41% were considered high-risk medications. 42% of potential medication errors were classified as high-risk medication errors. Results from this survey tool demonstrated that 58% of high-risk medication orders could potentially result in a medication error that can be carried through patient admission and discharge. Accurate medication history and transitions of care can significantly impact patient quality of life. The cost of addressing a medication related-adverse event is also substantial. Based on published reports, annual gross savings to a hospital is estimated to be $4532 per harmful error in 2020, after adjusting for inflation. This equated to approximately $1,182,852 in estimated savings for Ascension Texas in 18 months. Nationwide, preventing potential medication errors in an outpatient setting can save on average $3.5 billion per year. This web-based survey tool has improved the quality and efficiency of potential error identification during medication history collection by pharmacy technicians. This information can be easily retrieved and aid in discussions regarding medication reconciliation at the leadership level and impact patient treatment outcomes by developing virtual processes that may result in fewer medication related events.
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