Hospital-acquired conditions (HACs) harm patients and cost US hospitals $98 billion annually. Our mission is to eliminate the preventable patient harm HACs cause by revolutionizing risk assessment and monitoring.
The Kinometrix Difference
BIG DATA
Developed using real patient electronic health records (EHRs)
MACHINE LEARNING
Delivers superior precision and predictive accuracy
AUTOMATION
Integrates with existing EHRs to provide real-time decision support.
Platform Solutions
Kinometrix has developed a machine learning platform using EHR data to assess the risk for patient harm events in hospitals. Our first solution automates patient fall-risk assessment and provides accurate, real-time fall risk predictions with specific risk drivers directly to the frontline clinician.
The Kinometrix platform is a “headless” system. This means it can be integrated with any EHR and customized to meet specific hospital or health system needs.
Other tools integrated into EHRs require additional documentation or work to use. The Kinometrix platform solutions work within existing clinical workflows to reduce documentation requirements and provide an intuitive user experience.
Preventing Patient Falls
Fall prevention has been the subject of intensive research and quality improvement efforts for years, yet it remains a major challenge for healthcare organizations. Each year approximately 1 million patients fall in the hospital, with a third of these events resulting in injury.
One major challenge is accurately assessing a patient’s risk for falling. There is consensus that successful prevention begins with assessing individual patients’ risk for falls. However, despite years of effort, existing clinical prediction tools remain largely subjective and imprecise, and none has been shown to be significantly more accurate than others.
Kinometrix is changing this. The Kinometrix Fall Risk Assessment Solution (K-FRAS) uses existing EHR data to deliver accurate fall risk along with the drivers of individual patient’s risk directly to the clinician in real-time.
Seamless EHR Integration
Bi-directional API
