Hospital information systems (HIS) have become an essential part of healthcare institutions and now incorporate prescribing support software. Prescription support software allows for structured information capture, which improves the safety, appropriateness and efficiency of prescriptions and reduces the number of adverse drug events (ADEs). However, such a system increases the amount of time physicians spend at a computer entering information instead of providing medical care. In addition, any new visiting clinician must learn to manage complex interfaces since each HIS has its own interfaces. In this paper, we present a natural language interface for e-prescribing software in the form of a spoken dialogue system accessible on a smartphone. This system allows prescribers to record their prescriptions verbally, a form of interaction closer to their usual practice. The system extracts the formal representation of the prescription ready to be checked by the prescribing software and uses the dialogue to request mandatory information, correct errors or warn of particular situations. Since, to the best of our knowledge, there is no existing voice-based prescription dialogue system, we present the system developed in a low-resource environment, focusing on dialogue modeling, semantic extraction and data augmentation. The system was evaluated in the wild with 55 participants. This evaluation showed that our system has an average prescription time of 66.15 seconds for physicians and 35.64 seconds for other experts, and a task success rate of 76\% for physicians and 72\% for other experts. All evaluation data were recorded and annotated to form PxCorpus, the first spoken drug prescription corpus that has been made fully available to the community (\url{https://doi.org/10.5281/zenodo.6524162}).

翻译：医院信息系统（HIS）已成为医疗机构的重要组成部分，目前集成了处方支持软件。处方支持软件能够实现结构化信息采集，从而提高处方的安全性、合理性和效率，并减少药物不良事件（ADE）的发生。然而，这类系统增加了医生在电脑前输入信息而非提供医疗服务的时间。此外，由于各HIS拥有独立的界面，任何新入职的临床医生都必须学习操作复杂的界面。本文提出了一种面向电子处方软件的自然语言接口，以智能手机可访问的口语对话系统形式呈现。该系统使处方开具者能够通过语音记录处方，这种方式更贴近其日常实践。系统提取处方的正式表示形式供处方软件校验，并利用对话请求必填信息、纠正错误或警示特殊情况。鉴于目前尚无基于语音的处方对话系统（据我们所知），我们介绍了在低资源环境下开发的系统，重点涵盖对话建模、语义提取和数据增强。该系统在真实场景中由55名参与者进行了评估。评估结果显示，医生使用本系统的平均处方时间为66.15秒，其他专家为35.64秒；医生的任务成功率为76%，其他专家为72%。所有评估数据均被记录并标注，形成了PxCorpus——这是首个完全向社区开放的口语药物处方语料库（网址：\url{https://doi.org/10.5281/zenodo.6524162}）。