Linking electronic medical records to large-scale simulation models: Can we put rapid learning on turbo?

被引:12
作者
Eddy, David M. [1 ]
机构
[1] Archimedes Inc, San Francisco, CA USA
关键词
D O I
10.1377/hlthaff.26.2.w125
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
One method for rapid learning is to use data from electronic medical records (EMRs) to help build and validate large-scale, physiology-based simulation models. These models can than be used to help answer questions that cannot be addressed directly from the EMR data. Their potential uses include analyses of physiological pathways; simulation and design of clinical trials; and analyses of clinical management tools such as guidelines, performance measures, priority setting, and cost-effectiveness. Linking the models to EMR data also facilitates tailoring analyses to specific populations. The models' power and accuracy can be improved by linkage to comprehensive, person-specific, longitudinal data from EMRs.
引用
收藏
页码:W125 / W136
页数:12
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