期刊
GERONTOLOGY AND GERIATRIC MEDICINE
卷 6, 期 -, 页码 -出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/2333721420959861
关键词
Alzheimer's disease; dementia; natural language processing; home health care; electronic health record
资金
- National Institute on Aging [R21AG065753]
Background: Little is known about symptom documentation related to Alzheimer's disease and related dementias (ADRD) by home healthcare (HHC) clinicians. Objective: This study: (1) developed a natural language processing (NLP) algorithm that identifies common neuropsychiatric symptoms of ADRD in HHC free-text clinical notes; (2) described symptom clusters and hospitalization or emergency department (ED) visit rates for patients with and without these symptoms. Method: We examined a corpus of -2.6 million free-text notes for 112,237 HHC episodes among 89,459 patients admitted to a non-profit HHC agency for post-acute care with any diagnosis. We used NLP software (NimbleMiner) to construct indicators of six neuropsychiatric symptoms. Structured HHC assessment data were used to identify known ADRD diagnoses and construct measures of hospitalization/ED use during HHC. Results: Neuropsychiatric symptoms were documented for 40% of episodes. Common clusters included impaired memory, anxiety and/or depressed mood. One in three episodes without an ADRD diagnosis had documented symptoms. Hospitalization/ED rates increased with one or more symptoms present. Conclusion: HHC providers should examine episodes with neuropsychiatric symptoms but no ADRD diagnoses to determine whether ADRD diagnosis was missed or to recommend ADRD evaluation. NLP-generated symptom indicators can help to identify high-risk patients for targeted interventions.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据