Levin James E, Raman Sivakumaran
Clinical Informatics, Information Technology Services, Children's Hospitals and Clinics of Minnesota, Minneapolis/Saint Paul, Minnesota, USA.
AMIA Annu Symp Proc. 2005;2005:445-9.
Using data from over 450,000 pediatric encounters three data sources were evaluated for their ability to support early detection of a yearly outbreak of rotavirus disease: 1) Laboratory studies ordered, 2) Diagnosis codes, and 3) Free text "reason for visit" strings categorized as Gastrointestinal syndrome by a support vector machine software classifier. We found that in this setting the categorized free text analyzed through simple control charts detected each outbreak within 10 days of their beginning as determined by laboratory detection of rotavirus antigen (the gold standard). Outbreak detection by laboratory studies was delayed an average of 14 days and by diagnosis codes by an average of 20 days. We conclude that categorized text may provide a valuable basis for real-time detection of disease outbreaks.
利用来自超过45万次儿科诊疗的数据，对三个数据源支持轮状病毒病年度疫情早期检测的能力进行了评估：1）所开具的实验室检查；2）诊断编码；3）由支持向量机软件分类器归类为胃肠综合征的“就诊原因”自由文本字符串。我们发现，在这种情况下，通过简单控制图分析的归类自由文本在轮状病毒抗原实验室检测（金标准）确定的每次疫情开始后的10天内检测到了疫情。实验室检查发现疫情平均延迟14天，诊断编码发现疫情平均延迟20天。我们得出结论，归类文本可为疾病疫情的实时检测提供有价值的依据。
