Benn DK, Kostewicz SH, Dankel DD, Segal R, Schmidt SO, Chardon Z
University of Florida, Gainsville, FL.
Proc AMIA Symp. 2000:1168.
Physician compliance with clinical guidelines varies between 30% and 50% despite knowledge of and acceptance of guidelines. In an attempt to improve the use of guidelines there is increasing interest in the development of clinical decision support systems. We are interested in designing a system that is intended for interdisciplinary use in primary, secondary, and tertiary level situations. Since 1995 we have been developing an electronic oral health record containing a decision support system for caries management. As the addition of different decision support modules was contemplated, the ability to scale up the environment became important. We decided to use Authorware (Macromedia, San Francisco, CA), which is a multi-media program generator capable of generating code for PCs, Macs, and streaming interactively across the internet. Authorware uses SQL calls to an open architecture database that is essential for easy access by multiple users. Our system has modules for demographics, medical-, dental-, social-histories, head and neck physical exam, vital signs, chief complaints, caries and periodontal disease recording graphics, automatic surveillance of input data to identify risk factors for caries with automatic classification of risk level into low, medium, or high. A suggested management strategy at the systemic and local lesion level is automatically generated for the clinician. The system is currently undergoing beta testing with Delta Dental Insurance (Boston, MA) and the Veterans' Administration (Gainesville, FL).
尽管医生了解并接受临床指南,但他们对指南的遵循率在30%至50%之间。为了提高指南的使用率,人们对临床决策支持系统的开发越来越感兴趣。我们有兴趣设计一个旨在在初级、二级和三级医疗环境中跨学科使用的系统。自1995年以来,我们一直在开发一种电子口腔健康记录,其中包含一个用于龋齿管理的决策支持系统。随着考虑添加不同的决策支持模块,扩大环境规模的能力变得很重要。我们决定使用Authorware(Macromedia,旧金山,加利福尼亚州),它是一个多媒体程序生成器,能够为个人电脑、苹果电脑生成代码,并通过互联网进行交互式流传输。Authorware使用SQL调用一个开放架构数据库,这对于多个用户轻松访问至关重要。我们的系统具有用于人口统计学、医学、牙科、社会史、头颈部体格检查、生命体征、主要症状、龋齿和牙周疾病记录图形、自动监测输入数据以识别龋齿风险因素并自动将风险水平分类为低、中或高的模块。会自动为临床医生生成在全身和局部病变水平上的建议管理策略。该系统目前正在与三角洲牙科保险(马萨诸塞州波士顿)和退伍军人管理局(佛罗里达州盖恩斯维尔)进行beta测试。