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COMPUTER IMPLEMENTED METHOD FOR CONGESTIVE HEART FAILURE RISK PATIENTS WITH STATISTICAL ANALYSIS PERFORMED TO GENERATE PREDICTION MODELS
COMPUTER IMPLEMENTED METHOD FOR CONGESTIVE HEART FAILURE RISK PATIENTS WITH STATISTICAL ANALYSIS PERFORMED TO GENERATE PREDICTION MODELS
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机译：进行统计分析以生成预测模型的同等心力衰竭风险患者的计算机实现方法
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摘要
A computer-implemented technique, including database processing, is used to identify at risk congestive heart failure patients where information about patients exists in a claims database. The technique includes processing the patient information in the claims database to find and extract claims information for a group of congestive heart failure patients. Next, using the extracted information, a set of events, relevant to congestive heart failure, is defined. Next, the extracted information and set of events are processed to create event level information which is organized with respect to events rather than claims. A time window is defined to provide a timeframe from which to judge whether events should be considered in subsequent processing; and, a set of variables is defined as being potential predictors of adverse health outcomes. Subsequently, the event level information, using the time window and the set of variables, is processed to generate an analysis file. Statistical analysis, such as logistic regression, is performed on the analysis file to generate a prediction model where the prediction model is a function of a subset of the set of variables. Finally, the prediction model is applied to the same or another claims database to identify and output at risk patients, diagnosed with congestive heart failure, likely to have adverse health outcomes.
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