Kinometrix

Kinometrix provides a precision patient-safety platform powered by machine learning that analyzes EHR data to assess risks for patient harm events, with a specific fall-risk solution called K-FRAS. K-FRAS automates fall-risk assessment and reports individual risk drivers so clinicians can target interventions. The platform delivers real-time, objective risk predictions that include nurses’ expert assessments and aims to reduce nursing workload while improving accuracy versus existing tools. The team spent five years building the platform and positions it for deployment in hospitals to prevent patient harm. Kinometrix is based in Fort Belvoir, Virginia. The company has received investment from VIPC’s Virginia Venture Partners and funding from VIPC’s Commonwealth Commercialization Fund to support its initial go-to-market with early customers. Kinometrix is a developer of a risk assessment system designed to monitor patient fall risk status and produce actionable reports for nursing staff. The company is building a patient safety analytics platform intended to enable more targeted fall-prevention care and to empower clinical teams to practice at the top of their licenses. Kinometrix will use the awarded grant to analyze additional proprietary inpatient records to enhance its model robustness and to complete platform development. The company has previously received funding from Virginia Venture Partners. Kinometrix is based in Fort Belvoir, Virginia. The work focuses on improving health and safety outcomes within the hospital environment through scalable analytics. Kinometrix develops a fall-risk notification system that combines machine learning applied to electronic health record (EHR) data with wearable balance sensor data to alert hospital staff when a patient moves into a high-risk category. The product fuses motion sensors and a patient’s medical history to produce patient-specific risk assessments intended to reduce nurse workload and prevent patients from "falling through the cracks." The company plans to build a first release of its PatientSteady platform and validate components of its algorithm using the investment from CIT GAP Funds, which it says will lead to its first round of sales. Kinometrix positions its solution against current bedside assessment tools that it describes as subjective, inaccurate, and cumbersome. The company cites the scale of the problem—about one million inpatient falls in U.S. hospitals per year, averaging $6,694 per fall (roughly $6 billion annually)—as driving demand for its technology. Kinometrix aims to deploy its solution across the over 6,000 U.S. hospitals referenced by its CEO. KinometriX’s core product, the KX1 platform, uses a single inertial measurement unit (IMU) sensor integrated into therapists’ workflows to measure strength, range of motion, speed, and neuromuscular control. The system moves beyond patient self-reporting by providing empirical movement data that therapists can use to document healing progress and make objective treatment decisions. Research cited in the article indicates IMUs provide more precise indicators of rehabilitation progress than patient surveys. Inova Personalized Health Accelerator (IPHA) provided the company’s first institutional investment and is partnering to refine and validate algorithms. Inova Loudoun is conducting a pilot with its diverse patient population and collecting clinician feedback to shape the platform. KinometriX’s stated goal is to measure and then predict treatment progress to maximize patient adherence and accelerate clinical adoption.