现实临床环境中的现代光学字符识别系统：一些准确性和可行性观察结果。
A modern optical character recognition system in a real world clinical setting: some accuracy and feasibility observations.
作者信息
Biondich Paul G, Overhage J Marc, Dexter Paul R, Downs Stephen M, Lemmon Larry, McDonald Clement J
机构信息
Regenstrief Institute for Health Care and Indiana University School of Medicine, Indianapolis, IN, USA.
出版信息
Proc AMIA Symp. 2002:56-60.
Advances in optical character recognition (OCR) software and computer hardware have stimulated a reevaluation of the technology and its ability to capture structured clinical data from preexisting paper forms. In our pilot evaluation, we measured the accuracy and feasibility of capturing vitals data from a pediatric encounter form that has been in use for over twenty years. We found that the software had a digit recognition rate of 92.4% (95% confidence interval: 91.6 to 93.2) overall. More importantly, this system was approximately three times as fast as our existing method of data entry. These preliminary results suggest that with further refinements in the approach and additional development, we may be able to incorporate OCR as another method for capturing structured clinical data.
光学字符识别（OCR）软件和计算机硬件的进步激发了对该技术及其从现有纸质表格中获取结构化临床数据能力的重新评估。在我们的试点评估中，我们测量了从一份已使用二十多年的儿科问诊表格中获取生命体征数据的准确性和可行性。我们发现，该软件的数字识别率总体为92.4%（95%置信区间：91.6至93.2）。更重要的是，该系统的速度大约是我们现有数据录入方法的三倍。这些初步结果表明，随着方法的进一步改进和更多开发，我们或许能够将OCR纳入另一种获取结构化临床数据的方法。
Zotero 插件