A Natural Language Processing Framework for Assessing Hospital Readmissions for Patients With COPD

作者：Agarwal Ankur^*; Baechle Christopher; Behara Ravi; Zhu Xingquan

来源：IEEE Journal of Biomedical and Health Informatics, 2018, 22(2): 588-596.

DOI：10.1109/JBHI.2017.2684121

• Data mining
• decision support systems
• feature extraction
• medical information systems
• natural language processing

With the passage of recent federal legislation, many medical institutions are now responsible for reaching target hospital readmission rates. Chronic diseases account for many hospital readmissions and chronic obstructive pulmonary disease has been recently added to the list of diseases for which the United States government penalizes hospitals incurring excessive readmissions. Though there have been efforts to statistically predict those most in danger of readmission, a few have focused primarily on unstructured clinical notes. We have proposed a framework, which uses natural language processing to analyze clinical notes and predict readmission. Many algorithms within the field of data mining and machine learning exist, so a framework for component selection is created to select the best components. Naive Bayes using Chi-Squared feature selection offers an AUC of 0.690 while maintaining fast computational times.

• 出版日期2018-3