From earlier disease detection to sharper diagnostic tools, AI and machine learning tools are helping providers deliver better care for patients living with chronic diseases.
Take one routine case: colonoscopies.
AI for Colonoscopy Screenings
Colonoscopies have become a cornerstone of preventive healthcare. Approximately 14-18 million procedures are performed every year in the United States. Current clinical guidelines recommend regular screenings from age 45 through 75. Patients should also receive follow-up colonoscopies every 10 years, if no polyps are found during the initial procedure.
Traditional colonoscopies face real challenges. Up to 25% of polyps can be missed during colonoscopy. That’s a significant gap in detection that could affect patient outcomes. Withdrawal time, bowel preparation quality, and the endoscopist’s skill level are all factors that impact the effectiveness of the screening.
AI tools have been used for years to improve colonoscopy screenings. These systems can spot cancerous polyps with remarkable precision during routine procedures. As far back as 2018 – a lifetime ago in AI technology – deep learning tools had a 96 percent success rate for identifying polyps.
Colonoscopies are just one example of how AI-tools are improving the quality of care. In radiology, algorithms rival or surpass human specialists, catching abnormalities early when treatment is most effective. For patients, this technology acts like a second pair of expert eyes and has the power to prevent mistakes. It’s not there to replace providers, but assist in their evaluation.
The Reimbursement Roadblock
Unfortunately, as with all things in health care, it comes back to money. Existing payment and reimbursement systems created before AI and machine learning don’t properly account for their value. Only a fraction of AI medical devices are reimbursed by the Centers for Medicare and Medicaid Services.
This creates a dilemma for providers: Adopt cutting-edge tools and risk no reimbursement from Medicare, or stick to traditional methods and deny patients better care.
Bipartisan Fix: The Health Tech Investment Act
A bipartisan group of lawmakers is working to address the problem related to Medicare reimbursement of AI and machine learning tools.
The Health Tech Investment Act (S.1399), introduced by Senators Martin Heinrich and Mike Rounds, creates a clear, predictable reimbursement pathway for FDA-regulated AI and machine learning devices within Medicare. By standardizing CMS payments, it removes financial uncertainty for providers considering these technologies.
The Act also ensures regular technology assessments, keeping policies aligned with AI advancements so patients never fall behind innovation.
Get Involved: Support Health Tech Investment Act
Early detection via AI screening can boost survival rates for cancer, heart disease, and neurological disorders. Accurate diagnoses reduce costs by eliminating unnecessary procedures and additional tests. For chronic illnesses, AI tools track subtle changes to ensure timely interventions.
Patients Rising is joining nearly two dozen patient advocacy groups, including the Alzheimer’s Association, Arthritis Foundation, and Prevent Cancer Foundation, to support S.1399.
You can join in our effort by adding your voice. Contact your U.S. Senator and member of Congress to urge their support for S.1399.