Ahltorp Magnus, Skeppstedt Maria, Dalianis Hercules, Kvist Maria
KTH Royal Institute of Technology, Stockholm, Sweden.
Stud Health Technol Inform. 2013;192:1149.
Text prediction has the potential for facilitating and speeding up the documentation work within health care, making it possible for health personnel to allocate less time to documentation and more time to patient care. It also offers a way to produce clinical text with fewer misspellings and abbreviations, increasing readability. We have explored how text prediction can be used for input of clinical text, and how the specific challenges of text prediction in this domain can be addressed. A text prediction prototype was constructed using data from a medical journal and from medical terminologies. This prototype achieved keystroke savings of 26% when evaluated on texts mimicking authentic clinical text. The results are encouraging, indicating that there are feasible methods for text prediction in the clinical domain.
文本预测有潜力促进并加快医疗保健领域的文档工作,使医护人员能够将更少的时间用于文档记录,而将更多时间用于患者护理。它还提供了一种减少拼写错误和缩写的方式来生成临床文本,从而提高可读性。我们探讨了如何将文本预测用于临床文本输入,以及如何应对该领域中文本预测的具体挑战。利用医学期刊和医学术语中的数据构建了一个文本预测原型。在模拟真实临床文本的文本上进行评估时,该原型实现了26%的击键节省。结果令人鼓舞,表明在临床领域存在可行的文本预测方法。