Use AI to Detect Prediabetes Progression
The United States has a rapidly aging population and clinicians are struggling to keep up with a demand for care, while being asked to deliver more with less. Provider organizations, especially endocrinologists and primary care, broadly struggle to identify and prioritize patients who have, or will have, the greatest need for prediabetes intervention.
AI-Powered Prediabetes Detection
Lucem Health Reveal for Prediabetes identifies prediabetes patients who appear to be at a higher risk of progressing to type 2 diabetes within 12 months. By connecting your EHR data to a proven AI algorithm, Reveal for Prediabetes looks far beyond elevated glucose levels to identify patterns that humans cannot. This makes it a powerful tool for detecting potential risks earlier, treating patients more effectively, and lowering treatment costs.
Reveal for Prediabetes Progression Features
Presents a simple list of higher risk patients who should receive priority follow-ups
Does not require any active patient participation
Complements and enhances your existing clinical workflows
Proven data security with HIPAA compliance and SOC 2 certification
The Reveal Difference
Uses EHR data and a proven AI model to flag pre-diabetic patients who are at a higher risk of progressing to diabetes within 12 months
Enables provider organizations to target these patients for earlier detection and intervention, which leads to more successful treatment and better patient outcomes
Creates opportunities for increased diabetes screening revenues in fee-for-service (FFS) scenarios
Accelerates the identification of patient risks in value-based care (VBC) arrangements, which helps reduce the need for higher-cost treatments
How It Works
See how early detection and intervention can improve outcomes and quality of life for patients enabling treatment before a patient’s a condition may become more difficult and expensive to manage.
The Impact of Prediabetes
Today, a staggering 96 million adults in the United States are prediabetic—and 80% of them don’t even know it, because prediabetes doesn’t usually have any signs or symptoms.
Diabetes is considered one of the world’s top public health burdens. A condition featuring chronic elevated glucose in the bloodstream, diabetes affects approximately 11 percent of the U.S. adult population, and more than one-quarter of adults over 65. The prevalence of diabetes has been increasing in recent decades, in part due to the epidemic of obesity. Chronically elevated glucose levels in diabetes can weaken immunity, promote inflammation, harm blood vessels, raise the risk of heart attacks and strokes and can also cause retinopathy (eye disease), kidney disease, and damage to the nerves.
About 5% of prediabetics will progress to Type 2 Diabetes each year, adding 4.8 million new diabetic patients each year to the disease’s already high clinical and cost burden.
From Partners You Can Trust
Lucem Health partnered with Medial EarlySign to develop the Reveal for Prediabetes Progression solution.
About Medial EarlySign
Medial EarlySign’s clinical machine learning software solutions help healthcare stakeholders keep patients healthier longer. Healthcare clients derive actionable and personalized clinical insights from massive amounts of health data leading to potential improvements in quality care, outcomes, diagnostic efficiency, and to accelerate the latest advances in drug research and therapy. EarlySign’s AlgoMarkers and predictive solutions can help clients select enriched subpopulations and more accurately identify and prioritize patients for multiple conditions for interventions to halt or prevent the serious complications from the onset of disease or optimize clinical trials design and recruitment. The company’s purpose-built development environment enables fast, accurate, and explainable models supported by peer-reviewed research published by internationally recognized health organizations and hospitals.
Deliver More Proactive Prediabetes Care
Find out how you can harness the power of AI to reveal high-risk prediabetic patients earlier, focus your limited clinical resources, and improve patient outcomes—without extensive training, adapting your clinical workflows, or undergoing extensive data and systems integration.