Aronow D B, Cooley J R, Soderland S
Center for Intelligent Information Retrieval, University of Massachusetts, Amherst, USA.
Proc Annu Symp Comput Appl Med Care. 1995:309-13.
Harvard Community Health Plan and the Center for Intelligent Information Retrieval are developing tools to support automated quality fo care measurement from clinical text data. A statistically based text classification system uses semantic features in computerized encounter notes to identify acute exacerbations of asthma. Individual encounter notes are sorted in bins of highly likely, highly unlikely and uncertain likelihood of documenting exacerbation, and then aggregated into episodes of exacerbation for frequency analysis. It is estimated that this approach could reduce the burden of manual chart review by 65%.
哈佛社区健康计划和智能信息检索中心正在开发工具，以支持从临床文本数据中自动进行医疗质量测量。一个基于统计的文本分类系统利用计算机化会诊记录中的语义特征来识别哮喘急性加重情况。将各个会诊记录按照记录加重情况的可能性高、可能性低和不确定进行分类，然后汇总成加重发作事件进行频率分析。据估计，这种方法可将人工病历审查的负担减轻65%。
