Ai Angela C, Maloney Francine L, Hickman Thu-Trang, Wilcox Allison R, Ramelson Harley, Wright Adam
Adam Wright, PhD, Division of General Internal Medicine, Brigham and Women's Hospital, 75 Francis St., Boston, MA 02115, Phone: (617) 525-9811, Fax: (617) 732-7072, Email:
Appl Clin Inform. 2017 Jul 12;8(3):710-718. doi: 10.4338/ACI-2016-10-RA-0180.
To understand how clinicians utilize image uploading tools in a home grown electronic health records (EHR) system.
A content analysis of patient notes containing non-radiological images from the EHR was conducted. Images from 4,000 random notes from July 1, 2009 - June 30, 2010 were reviewed and manually coded. Codes were assigned to four properties of the image: (1) image type, (2) role of image uploader (e.g. MD, NP, PA, RN), (3) practice type (e.g. internal medicine, dermatology, ophthalmology), and (4) image subject.
3,815 images from image-containing notes stored in the EHR were reviewed and manually coded. Of those images, 32.8% were clinical and 66.2% were non-clinical. The most common types of the clinical images were photographs (38.0%), diagrams (19.1%), and scanned documents (14.4%). MDs uploaded 67.9% of clinical images, followed by RNs with 10.2%, and genetic counselors with 6.8%. Dermatology (34.9%), ophthalmology (16.1%), and general surgery (10.8%) uploaded the most clinical images. The content of clinical images referencing body parts varied, with 49.8% of those images focusing on the head and neck region, 15.3% focusing on the thorax, and 13.8% focusing on the lower extremities.
The diversity of image types, content, and uploaders within a home grown EHR system reflected the versatility and importance of the image uploading tool. Understanding how users utilize image uploading tools in a clinical setting highlights important considerations for designing better EHR tools and the importance of interoperability between EHR systems and other health technology.
了解临床医生如何在自主开发的电子健康记录（EHR）系统中使用图像上传工具。
对EHR中包含非放射图像的患者记录进行内容分析。回顾并手动编码了2009年7月1日至2010年6月30日期间4000份随机记录中的图像。为图像的四个属性分配代码：（1）图像类型，（2）图像上传者的角色（如医生、执业护士、助理医师、注册护士），（3）执业类型（如内科、皮肤科、眼科），以及（4）图像主题。
对EHR中存储的包含图像的记录中的3815张图像进行了回顾和手动编码。在这些图像中，32.8%为临床图像，66.2%为非临床图像。临床图像最常见的类型是照片（38.0%）、图表（19.1%）和扫描文档（14.4%）。医生上传了67.9%的临床图像，其次是注册护士，占10.2%，遗传咨询师占6.8%。皮肤科（34.9%）、眼科（16.1%）和普通外科（10.8%）上传的临床图像最多。提及身体部位的临床图像内容各不相同，其中49.8%的图像聚焦于头颈部区域，15.3%聚焦于胸部，13.8%聚焦于下肢。
自主开发的EHR系统中图像类型、内容和上传者的多样性反映了图像上传工具的多功能性和重要性。了解用户在临床环境中如何使用图像上传工具突出了设计更好的EHR工具的重要考虑因素以及EHR系统与其他健康技术之间互操作性的重要性。
