Abston K C, Pryor T A, Haug P J, Anderson J L
Department of Medical Informatics, University of Utah, Salt Lake City, USA.
Proc AMIA Annu Fall Symp. 1997:168-72.
Improving health care quality requires the elimination of unnecessary variation in the care process. Decision support applications already exist that can foster adherence to standards. The challenge resides in developing standards consistent with good medical practice. In this paper we present our efforts in determining where sufficient clinical data are captured electronically to automatically define a care process, and what analyses can be done to identify additional data that would allow a care process to be defined. Data routinely collected by a hospital information system have been examined. The analysis tools utilized include logistic regression, a neural network, a Bayesian network, and a rule induction program.
提高医疗质量需要消除医疗过程中不必要的差异。现有的决策支持应用程序可以促进对标准的遵守。挑战在于制定与良好医疗实践相一致的标准。在本文中,我们介绍了我们在确定何处以电子方式捕获了足够的临床数据以自动定义护理过程,以及可以进行哪些分析以识别允许定义护理过程的其他数据方面所做的努力。我们检查了医院信息系统常规收集的数据。所使用的分析工具包括逻辑回归、神经网络、贝叶斯网络和规则归纳程序。