Children’s Health Services Research, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Pediatrics. 2012 May;129(5):e1275-81. doi: 10.1542/peds.2011-2875. Epub 2012 Apr 16.
Implementing US Preventive Services Task Force and American Academy of Pediatrics preventive service guidelines within the short duration of a visit is difficult because identifying which of a large number of guidelines apply to a particular patient is impractical. Clinical decision support system integrated with electronic medical records offer a good strategy for implementing screening in waiting rooms. Our objective was to determine rates of positive risk screens during typical well-care visits among children and adolescents in a primary care setting.
Child Health Improvement through Computer Automation (CHICA) is a pediatric clinical decision support system developed by our research group. CHICA encodes clinical guidelines as medical logic modules to generate scanable paper forms: the patient screening form to collect structured data from patient families in the waiting room and the physician worksheet to provide physician assessments at each visit. By using visit as a unit of analysis from CHICA's database, we have determined positive risk screen rates in our population.
From a cohort of 16 963 patients, 408 601 questions were asked in 31 843 visits. Of the questions asked, 362 363 (89%) had a response. Of those, 39 176 (11%) identified positive risk screens in both the younger children and the adolescent age groups.
By automating the process of screening and alerting the physician to those who screened positive, we have significantly decreased the burden of identifying relevant guidelines and screening of patient families in our clinics.
在美国预防服务工作组和美国儿科学会的预防服务指南的指导下,在短时间内完成一次就诊,这是非常困难的,因为要确定大量指南中哪些适用于特定患者是不切实际的。与电子病历集成的临床决策支持系统为在候诊室实施筛查提供了一个很好的策略。我们的目的是确定在初级保健环境中,典型的儿童保健就诊中,阳性风险筛查的发生率。
儿童健康改善通过计算机自动化(CHICA)是由我们的研究小组开发的一种儿科临床决策支持系统。CHICA 将临床指南编码为医疗逻辑模块,以生成可扫描的纸质表格:患者筛查表,用于从候诊室的患者家庭中收集结构化数据;医生工作表,用于在每次就诊时提供医生评估。通过将就诊作为 CHICA 数据库的分析单位,我们确定了我们人群中的阳性风险筛查率。
从 16963 名患者的队列中,31843 次就诊中提出了 408601 个问题。在所提出的问题中,362363 个(89%)有响应。其中,39176 个(11%)在年幼儿童和青少年年龄组中都发现了阳性风险筛查。
通过自动化筛查过程并提醒医生注意那些筛查阳性的患者,我们大大减轻了我们诊所中识别相关指南和筛查患者家庭的负担。