[The construction and evaluation of the preventing method for the input mischoice in a prescription order entry system--usefulness of a three-character input and a warning screen display system]
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Updated: Sep 28, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Megumi Watanabe1, Munetoshi Sugiura, Toshikazu Seino
1Department of Pharmacy, University of Tokyo Hospital, Faculty of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.
Abstract:
In the computerized prescription order entry system, it has been pointed out that a physician's input mischoice for medicine is one of the causes of medication errors. We therefore investigated the input mischoices by physicians at the time of writing prescriptions. Subsequently, the number of input characters in a prescription order was changed to three characters from two characters. Furthermore, 105 items of high-alert medications, which are likely to result in injury if errors occur, were established. A warning screen display system that requests reconfirmation of the effect, name, usage, and dosage of those medicines was also built. It was found that 70% of input mistakes were caused by choosing the medicine displayed immediately above or below the desired drug. By changing the number of input characters of a prescription order to three characters from two characters, the rate of specification of a trademark improved sharply from 36% to 85%. Consequently, the rate of choice of a drug with another trademark decreased significantly from 0.028% to 0.0047%. In 5% of cases when the warning screen was displayed for a high-alert medicine, the prescription was stopped, and 25% were changed to other medicines. The above results show that the system that requires the input of three or more characters for the physician order entry and displays a warning screen for high-alert medicines is useful in preventing mischoices at the time of prescription input.
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