The language used by physicians and health professionals in prescription
directions includes medical jargon and implicit directives and causes much
confusion among patients. Human intervention to simplify the language at the
pharmacies may introduce additional errors that can lead to potentially severe
health outcomes. We propose a novel machine translation-based approach,
PharmMT, to automatically and reliably simplify prescription directions into
patient-friendly language, thereby significantly reducing pharmacist workload.
We evaluate the proposed approach over a dataset consisting of over 530K
prescriptions obtained from a large mail-order pharmacy. The end-to-end system
achieves a BLEU score of 60.27 against the reference directions generated by
pharmacists, a 39.6% relative improvement over the rule-based normalization.
Pharmacists judged 94.3% of the simplified directions as usable as-is or with
minimal changes. This work demonstrates the feasibility of a machine
translation-based tool for simplifying prescription directions in real-life.

提出了一个新的基于机器翻译的方法，PharmMT，用于将处方指示语言自动简化为患者友好的语言，从而显着减少药师的工作量。该系统对超过 530K 份处方进行了评估，达到了与药师生成的参考指示方向的 BLEU 得分为 60.27，相对于基于规则的归一化的 39.6％的相对改进。药剂师判断 94.3％的简化指示方向可以按原样或进行最小更改使用。这项工作展示了在现实生活中简化处方指示的机器翻译工具的可行性。