Home Healthcare Clinical Notes Predict Patient Hospitalization and Emergency Department Visits.
Maxim Topaz, Kyungmi Woo, Miriam Ryvicker and 2 others
PMID 32852359WHAT IT FOUND
Early home health visit notes could predict later hospitalization or emergency department visits.
The best model performed well, but no intervention was tested. Clear documentation of symptoms, care coordination, and social risks may help flag risk.
Key findings
01In 112,237 home health episodes from 89,459 unique patients, 19,301 episodes (17.2%) ended in hospitalization or an ED visit.
02Using the first 70% of notes per episode (727,676 notes), a random forest model predicted hospitalization or ED visits with F-measure .83 and AUC .76.
03388 words and expressions were associated with hospitalization or ED visits; clinical factors (28%) and coordination/communication (23%) were most prevalent.
STILL TO COME
How it was doneWhat they foundWhat it means for RNs
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What it does not show
The data came from one nonprofit home health agency in New York, so the model may not work as well in other agencies. Some hospitalization or emergency department visit outcomes may have been missed because clinicians could not always follow up after discharge. The study used only narrative notes, not structured medication or disease data, so risk factors documented elsewhere may have been missed. The machine learning models were used with default settings and were not tuned specifically for these home health notes. The study did not test whether acting on the model warnings reduced hospitalizations or emergency department visits.
Declared interests
The authors reported no conflicts of interest. The article is tagged as supported by NIH extramural and U.S. Public Health Service research support.
The easy way to misread this
Do not read this as proof that early warning systems reduce hospitalizations or emergency department visits. The study only tested whether notes could predict these events, and it did not deliver or evaluate an intervention.