부산대학교 도서관

Objectives: Since the 1970s, a plethora of tools have been introduced to support the medication use process. However, automation initiatives to assist pharmacists in prospectively reviewing medication orders are lacking. The review of many medications may be protocolized and implemented in an algorithmic fashion utilizing discrete data from the electronic health record (EHR). This research serves as a proof of concept to evaluate the capability and effectiveness of an electronic prospective medication order review (EPMOR) system compared to pharmacists' review. Materials and methods: A subset of the most frequently verified medication orders were identified for inclusion. A team of clinical pharmacist experts developed best-practice EPMOR criteria. The established criteria were incorporated into conditional logic built within the EHR. Verification outcomes from the pharmacist (human) and EPMOR (automation) were compared. Results: Overall, 13 404 medication orders were included. Of those orders, 13 133 passed pharmacist review, 7388 of which passed EPMOR. A total of 271 medication orders failed pharmacist review due to order modification or discontinuation, 105 of which passed EPMOR. Of the 105 orders, 19 were duplicate orders correctly caught by both EPMOR and pharmacists, but the opposite duplicate order was rejected, 51 orders failed due to scheduling changes. Discussion: This simulation was capable of effectively discriminating and triaging orders. Protocolization and automation of the prospective medication order review process in the EHR appear possible using clinically driven algorithms. Conclusion: Further research is necessary to refine such algorithms to maximize value, improve efficiency, and minimize safety risks in preparation for the implementation of fully automated systems. Lay Summary Pharmacists prospectively evaluate most medication orders placed in the hospital. While this review serves an important function, the current system gives equal significance to all orders. This system creates opportunity costs where the pharmacist reviews routine medication orders instead of performing other more valuable clinical activities that may produce greater patient benefits and outcomes. It may be possible for the review of routine medication orders to be protocolized and performed consistently and efficiently by an electronic system. This investigation aimed to evaluate the opportunity to develop a protocol for medication order review and implement an electronic system to mimic this activity. A team of clinical pharmacists and informaticists created a best-practice framework of what should be checked when reviewing medication orders. They then designed an electronic prospective medication order review (EPMOR) system to run in the background of the electronic health record (EHR). A comparative review of the EPMOR system versus the human- driven order verification process was performed. During a 5-day period, 13 404 medication orders were studied. Of the 13 133 orders reviewed by a pharmacist, 7388 passed the EPMOR. Further research is necessary to evaluate the safety and use of enhanced automation including artificial intelligence for verifying medication orders. Key words: informatics; pharmacists; automation; electronic prospective medication order review; prospective medication order review.
Background and significance Pharmacist prospective medication order review (PMOR) is performed for nearly all medications in a hospital-based setting. PMOR occurs following a prescriber's signed order but prior to dispensing [...]