Key result
NLP identifies HF patients with poor self-management from home healthcare notes with ~86% precision.
Why the study?
The study was conducted to identify patients in home healthcare with heart failure symptoms and poor self-management using unstructured electronic health record data.
Can natural language processing algorithms accurately identify heart failure symptoms and poor self-management in home healthcare clinical notes?
Can natural language processing algorithms accurately identify heart failure symptoms and poor self-management in home healthcare clinical notes?
NLP algorithms can feasibly and accurately identify heart failure symptoms and poor self-management from unstructured home healthcare clinical notes, facilitating individualized symptom management.
May support targeted HF symptom management in home care; leaves open prospective validation and outcome impact.
The goal of this natural language processing (NLP) study was to identify patients in home healthcare with heart failure symptoms and poor self-management (SM). The preliminary lists of symptoms and poor SM status were identified, NLP algorithms were used to refine the lists, and NLP performance was evaluated using 2.3 million home healthcare clinical notes. The overall precision to identify patients with heart failure symptoms and poor SM status was 0.86. The feasibility of methods was demonstrated to identify patients with heart failure symptoms and poor SM documented in home healthcare notes. This study facilitates utilizing key symptom information and patients' SM status from unstructured data in electronic health records. The results of this study can be applied to better individualize symptom management to support heart failure patients' quality-of-life.
No takes yet. Share an insight, caveat, or question.
Chae et al. (2021) studied Heart failure. Natural language processing (NLP) algorithms was evaluated on Precision to identify patients with heart failure symptoms and poor self-management status. Natural language processing algorithms identified patients with heart failure symptoms and poor self-management from home healthcare clinical notes with an overall precision of 0.86.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: