About
OK2StandUP is the first AI-powered fall mitigation solution built specifically for healthcare caregivers across hospitals, rehabilitation centers, memory care facilities, and skilled nursing communities. The system uses discreet wearable technology to continuously monitor high-risk patients and deliver predictive alerts within 6 seconds of a patient's intent to sit up — allowing staff to respond proactively before a fall occurs. In clinical trials spanning 4,500 hours of monitoring across 5 skilled nursing communities with 44 high fall-risk patients, OK2StandUP achieved zero fall incidents and demonstrated 95% accurate intent detection with an average of just 0.1 false alerts per bed per day. This dramatically reduces alarm fatigue while keeping care teams meaningfully informed. Unlike legacy bed alarm systems or camera-based monitoring, OK2StandUP protects patient privacy and dignity without requiring line-of-sight surveillance or dedicated sitters. It integrates seamlessly into existing rounding, fall risk, and mobility monitoring workflows without disrupting clinical protocols. OK2StandUP is purpose-built for clinical care teams — directors of nursing, patient safety officers, and hospital administrators — who are looking to reduce fall-related adverse events, reclaim clinical staff time, and lower the operational costs associated with fall injuries. The platform also includes OK2Predict, a predictive analytics module, and an ROI calculator to help facilities quantify the financial and operational benefits of adoption.
Key Features
- Predictive Sit-Up Intent Detection: Wearable AI sensors detect a patient's intention to sit up and alert care teams within 6 seconds, enabling proactive intervention before a fall occurs.
- Ultra-Low False Alert Rate: Averages just 0.1 false alerts per bed per day, dramatically reducing alarm fatigue compared to traditional bed alarm systems.
- Camera-Free, Privacy-Respecting Monitoring: Continuous monitoring without cameras or dedicated one-on-one sitters, preserving patient privacy and dignity while keeping staff informed.
- Seamless Workflow Integration: Designed to integrate easily into existing rounding, fall risk, and mobility monitoring protocols without disrupting established clinical workflows.
- OK2Predict Analytics Module: Predictive analytics tools and an ROI calculator help facilities assess fall risk trends and quantify the operational and financial value of the system.
Use Cases
- Monitoring high fall-risk patients in skilled nursing facilities to prevent fall incidents and reduce injury-related costs.
- Reducing dependence on one-on-one patient sitters in hospital settings by providing AI-driven, real-time sit-up intent alerts.
- Supporting memory care units where patients may not communicate their intent to move, enabling proactive staff response.
- Streamlining rehabilitation center workflows by integrating fall risk monitoring into existing rounding and mobility protocols.
- Helping hospital administrators quantify fall prevention ROI and justify investment in AI-powered patient safety technology.
Pros
- Clinically Validated Results: Achieved zero fall incidents across 5 product trials with 44 high fall-risk patients over 4,500 hours of monitoring — a compelling evidence base for adoption.
- Reduces Staff Burden: Eliminates the need for constant room checks and one-on-one sitters, freeing up clinical FTE capacity for higher-value care tasks.
- Minimal Alarm Fatigue: With only 0.1 false alerts per bed per day, care teams can trust alerts and respond with urgency rather than tuning them out.
- Privacy-Safe Design: No cameras or video surveillance means patient dignity is protected, easing adoption concerns among patients and families.
Cons
- Enterprise-Only Pricing: Designed for healthcare facilities rather than individual consumers or small practices; pricing is not publicly listed and likely requires a sales engagement.
- Requires Clinical Protocol Integration: The system is intended to supplement — not replace — established clinical fall prevention protocols, meaning staff training and workflow adaptation are required.
- Limited to Sit-Up Intent Detection: The current system is focused on detecting intent to sit up; it does not cover other types of patient movement or fall scenarios beyond this specific behavior.
Frequently Asked Questions
How quickly does OK2StandUP alert care staff?
The system delivers alerts to care teams within 6 seconds of detecting a patient's intention to sit up, giving staff time to respond before a fall occurs.
Does OK2StandUP use cameras to monitor patients?
No. OK2StandUP uses discreet wearable technology rather than cameras, protecting patient privacy and dignity while providing continuous monitoring.
How accurate is the system, and how many false alarms does it generate?
The system achieves 95% accuracy in detecting sit-up intent and averages just 0.1 false alerts per bed per day, significantly reducing alarm fatigue for care teams.
What types of facilities is OK2StandUP designed for?
OK2StandUP is built for hospitals, rehabilitation centers, skilled nursing facilities, and memory care communities — anywhere high fall-risk patients require continuous monitoring.
Does OK2StandUP replace existing fall prevention protocols?
No. OK2StandUP is designed to augment and support established clinical fall prevention protocols, not replace them. Alerts serve as a supplementary tool for care teams.
