Kinometrix has developed a machine learning platform that utilizes electronic health records to provide real-time fall risk assessments for hospitalized patients, identifying specific risk factors directly to clinicians. This technology addresses the challenge of hospital-acquired conditions by delivering precise predictions that aim to reduce patient harm and associated costs.
Funding
$820K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
LLVIVVXFounders
Product
Problem
Hospital-acquired conditions, such as patient falls, cause significant harm to patients and incur substantial costs for hospitals annually. Existing methods for assessing patient fall risk are often subjective and lack the precision needed for effective prevention.
Solution
Kinometrix offers a machine learning platform that leverages electronic health record (EHR) data to provide real-time, accurate fall risk assessments for hospitalized patients. The Kinometrix Fall Risk Assessment Solution (K-FRAS) analyzes existing EHR data to deliver precise fall risk predictions, highlighting the specific factors contributing to an individual patient's risk. By integrating seamlessly into existing clinical workflows, the platform minimizes additional documentation requirements and provides an intuitive user experience for clinicians. The "headless" system design allows for integration with any EHR and customization to meet the specific needs of hospitals and health systems.
Target Audience
The primary target audience includes hospitals and health systems seeking to reduce patient harm from falls and associated costs, as well as clinicians needing accurate, real-time fall risk assessments.
Features
- Machine learning models developed using real patient EHR data for superior predictive accuracy.
- Real-time fall risk predictions delivered directly to clinicians within existing EHR workflows.
- Identification of specific risk factors driving individual patient's fall risk.
- Bi-directional API for seamless EHR integration.
- Customizable platform to meet specific hospital or health system needs.
- "Headless" system design allows integration with any EHR.