Beginning October 1, 2026, hospitals using Bayesian’s continuous sepsis monitor can receive additional Medicare reimbursement for eligible inpatient cases, the first reimbursement pathway of its kind for presuspicion sepsis monitoring.

NEW YORK, Sept. 2, 2026 /PRNewswire/ — Bayesian Health today announced that its FDA-cleared sepsis flagging device has been approved for a New Technology Add-on Payment (NTAP) under the Centers for Medicare and Medicaid Services’ FY 2027 Inpatient Prospective Payment System Final Rule. Beginning October 1, 2026, hospitals using the technology can receive additional Medicare reimbursement for eligible inpatient cases.

The approval builds on Bayesian’s Breakthrough Technology Designation and FDA clearance in April 2026, and makes Bayesian the first continuous sepsis monitoring technology with both FDA clearance and a dedicated Medicare reimbursement pathway.

“Early detection should be standard infrastructure in every hospital,” said Suchi Saria, PhD, Founder and CEO of Bayesian Health. “Reimbursement is not what makes clinical AI valuable. It’s signal quality clinicians can trust and the end-to-end infrastructure to operationalize those signals into everyday care. What this approval does is remove friction, so proven technology reaches more clinicians and patients faster.”

How the payment works

Standard hospital payment rates are set on historical claims, so a hospital adopting a newly approved technology absorbs its cost inside a rate that predates it. NTAP closes that gap: it provides a temporary add-on payment, on top of the standard MS-DRG payment, for cases where a qualifying technology was used and costs exceed what the bundled payment covers.

Beginning October 1, 2026, hospitals using Bayesian’s sepsis solution will have a way to bill for eligible use of the technology across adult Medicare fee-for-service inpatient admissions monitored by Bayesian, spanning an estimated 739 MS-DRGs. Eligible discharges qualify for an add-on payment of up to $61.84 per case. The pathway remains in place for up to three years.

For more information on payment guidelines visit https://www.bayesianhealth.com/insights/ntap-reimbursement-guide.

The value for health systems

Sepsis takes 270,000 lives in US hospitals every year¹ and drives more than $50 billion in annual hospital costs². Every hour of delayed treatment reduces survival by as much as 7.6 percent³. Health systems know this, but growing patient volumes, workforce shortages, and sustained margin pressure can slow adoption even when the clinical need is clear.

NTAP changes that equation, aligning Medicare payment with the clinical case for early detection so health systems can adopt proven monitoring technology while reimbursement helps carry the cost.

“Hospitals should not have to choose between financial discipline and getting ahead of the deadliest condition facing their patients,” said Martin Doerfler, MD, Chief Medical Officer at Bayesian Health. “Clinical teams already know what early detection is worth. They have seen what happens when sepsis is caught hours sooner. This approval aligns the payment model with the clinical reality, and it gives health system leaders one less reason to wait.”

Health systems’ biggest challenges is operationalizing clinical AI beyond the pilot stage: integrating into the EHR without burdening IT, training clinical staff, tuning alerts so they get answered instead of dismissed, and knowing who is accountable for checking that the system still performs on an ongoing basis. Bayesian’s platform is built to carry that work, with EHR-native workflow integration, documentation and reporting, and FDA-grade monitoring that tracks performance continuously. With NTAP, that support now includes CMS payment support .

Evidence that earned the pathway

Bayesian’s sepsis flagging device was validated in a landmark prospective study published in Nature Medicine, one of the largest evaluations of AI in clinical care ever conducted. Patients whose clinicians engaged with its alerts showed an 18.2 percent reduction in mortality and received antibiotics a median of 1.85 hours sooner. Those results have since been matched or exceeded across a diverse set of health systems, with consistently high (80%+)  clinician adoption, faster antibiotic delivery, lower utilization and lower sepsis mortality. Sustained adoption at that level is not an accident; it reflects continuous performance monitoring and tuning that keeps the system accurate as patient populations and clinical practice evolve.

Momentum

NTAP approval marks Bayesian’s second major regulatory and policy milestone of 2026, following FDA clearance in April. The milestones cap a year of momentum for the company, which recently expanded its physician leadership team and partnered with Mayo Clinic to bring its platform to palliative care, demonstrating how the same real-time intelligence built for sepsis becomes a repeatable playbook across service lines.

Clinical AI has moved from pilot to strategy, and Medicare’s decision reflects that shift: health systems now have the evidence, the clinical leadership, and the reimbursement pathway to move from adoption to transformation.

About Bayesian Health

Bayesian Health is the real-time clinical intelligence platform that helps health systems deliver proactive, highly-reliable care. By continuously reading the full patient record to establish each patient’s baseline and detect meaningful change over time, Bayesian applies complex clinical reasoning to identify the patients who truly need attention and surface clear next steps. Built to work within leading EHR systems and backed by FDA-grade monitoring and governance, the platform enhances existing clinical workflows by adding a continuous intelligence layer that helps teams intervene earlier and more effectively. Bayesian has partnered with leading health systems to make the long-promised shift from reactive to proactive care across key drivers of mortality, readmissions, and length of stay, hardwiring quality as a durable strategy rather than a series of disconnected initiatives.

Learn more at https://www.bayesianhealth.com.

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SOURCE Bayesian Health