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Legacy Healthcare improves senior fall risk monitoring with Exer AI motion health platform

“Legacy Healthcare improves senior fall risk monitoring with Exer AI motion health platform” documents a Patient Safety & Fall Prevention deployment in Senior & Home Health at Legacy Healthcare. www.exer.ai reports weekly patient check-in rate: 90%+; this directory has not independently verified that result.

Maintained by Peter Korpak, Founder & Chief AnalystHow evidence is checked

Evidence at a glance

Evidence status:
Automated evidence gate passed
Deployment timeframe:
Not reported by source
Reported outcome metrics:
2 cited below
Directory entry published:
Source link checked:

The source-link check confirms reachability, not independent re-verification of every claim.

90%+Weekly Patient Check-in Rate
<10%Post-Treatment Soreness Rate

Source-reported figures — cited source: www.exer.ai

The Challenge

Senior living providers face persistent challenges with fall risk assessment and prevention. Traditional approaches lacked objective, continuous monitoring of residents' mobility and functional health, making it difficult to measure therapy effectiveness or maintain regular patient engagement outside of scheduled appointments.

The Solution

Legacy Healthcare deployed Exer AI's computer vision-based motion health platform to deliver hybrid care across multiple touchpoints — in-clinic assessments, SMS-based self-assessment surveys via text message, and in-room monitoring within residents' apartments. The sensor-free platform uses AI on standard mobile devices to objectively measure gait, kinematics, and functional tests.

Results

Over 90% of patients now check in at least weekly, dramatically increasing engagement frequency. The platform enabled measurable therapy impact tracking, with less than 10% of residents reporting soreness the day after treatment, indicating improved care protocol adherence and outcomes.

Key Takeaways

  • Hybrid care delivery (in-clinic + remote + in-room) significantly increases patient engagement frequency in senior populations.
  • Objective, sensor-free motion data enables providers to quantify therapy outcomes rather than relying on subjective reporting.
  • SMS-based check-ins are an effective modality for aging patients who may not engage with complex apps.

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Details

Company Size
MidMarket
Evidence status
Automated evidence gate passed
Deployment timeframe
Not reported by source
Directory entry published
Source link checked

Cited source

www.exer.ai

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