作者
Maxim Topaz, Kavita Radhakrishnan, Suzanne Blackley, Victor Lei, Kenneth Lai, Li Zhou
发表日期
2017/1
期刊
Western journal of nursing research
卷号
39
期号
1
页码范围
147-165
出版商
SAGE Publications
简介
This study developed an innovative natural language processing algorithm to automatically identify heart failure (HF) patients with ineffective self-management status (in the domains of diet, physical activity, medication adherence, and adherence to clinician appointments) from narrative discharge summary notes. We also analyzed the association between self-management status and preventable 30-day hospital readmissions. Our natural language system achieved relatively high accuracy (F-measure = 86.3%; precision = 95%; recall = 79.2%) on a testing sample of 300 notes annotated by two human reviewers. In a sample of 8,901 HF patients admitted to our healthcare system, 14.4% (n = 1,282) had documentation of ineffective HF self-management. Adjusted regression analyses indicated that presence of any skill-related self-management deficit (odds ratio [OR] = 1.3, 95% confidence interval [CI] = [1.1, 1.6 …
引用总数
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