Overview
Prospective cohort study in which Sentinel's fall-risk assessment outperformed traditional screening tools at predicting fall events within the studied population.
This prospective cohort study followed 500 older adults in skilled nursing facilities over 12 months, comparing Sentinel's smartphone-based fall-risk assessment against established clinical tools.
In this cohort, Sentinel's algorithm achieved an AUC of 0.89 for identifying elevated fall risk within 30 days, higher than the Morse Fall Scale (AUC 0.72) and STRATIFY (AUC 0.69) as observed in the study.
The study reported that regular smartphone-based gait assessment surfaced fall-risk changes earlier than periodic manual assessments, supporting preventive intervention workflows led by qualified care teams.
These findings support smartphone-based gait analysis as a promising complement to established fall-risk stratification tools in clinical settings, within the scope of the studied population.
Key Takeaways
- AUC of 0.89 for 30-day fall-risk identification in this cohort
- Higher AUC than Morse Fall Scale and STRATIFY in the study
- Supports earlier intervention before mobility decline progresses
- Studied in real-world skilled nursing facility settings