What if the early signs of patient harm never went unnoticed?

Proactive care, powered by real-time clinical intelligence

Partnering with leading health systems to raise the standard of patient care

Partnering with leading health systems to raise the standard of patient care

REAL-TIME CLINICAL INTELLIGENCE PLATFORM

Stop asking clinicians to do the impossible.

Bayesian monitors every patient continuously, surfaces only those who need attention, and gives clinicians the guidance to act, consistently, at scale.

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Our outcomes are proven in research.
Validated in the real world.

Our outcomes are proven in research.
Validated in the real world.

.

Adoption

Absolute Mortality

Length of Stay

Real-World Data Across Bayesian Customers

81%

↓ 5.5%

↓ 1.9 days

5-Site Study Published in Nature Medicine

89%

↓ 3.3%

↓ 0.5 days

See the Peer-Reviewed Data

Our outcomes are proven in research. Validated in the real world.

Real-World Data Across Bayesian Customers

Adoption

81%

Absolute Mortality

↓ 5.5%

Length of Stay

↓ 1.9 days

5-Site Study Published in Nature Medicine

Adoption

89%

Absolute Mortality

↓ 3.3%

Length of Stay

↓ 0.5 days

See The Peer-Reviewed Data

Learn More

“We tried multiple tools, all with less than 1% adoption. At that rate, you can't improve anything, no matter how good the model is. Bayesian fires 3 hours earlier and 20 times less often on patients who are actually getting sick. That's the difference between a tool that gets ignored and one that gets used.”

Daniel Vaughn

Daniel Vaughn

Conrad Gleber MD MBA FAMIA

Associate Chief Medical Information Officer

“We tried multiple tools, all with less than 1% adoption. At that rate, you can't improve anything, no matter how good the model is. Bayesian fires 3 hours earlier and 20 times less often on patients who are actually getting sick. That's the difference between a tool that gets ignored and one that gets used.”

Daniel Vaughn

Daniel Vaughn

Conrad Gleber MD MBA FAMIA

Associate Chief Medical Information Officer

“We tried multiple tools, all with less than 1% adoption. At that rate, you can't improve anything, no matter how good the model is. Bayesian fires 3 hours earlier and 20 times less often on patients who are actually getting sick. That's the difference between a tool that gets ignored and one that gets used.”

Daniel Vaughn

Daniel Vaughn

Conrad Gleber MD MBA FAMIA

Associate Chief Medical Information Officer

Feature Image

Signals clinicians trust, not tune out

Signals clinicians trust, not tune out

Most clinical AI forces a choice between catching more risks and avoiding false alarms. Bayesian breaks that tradeoff by thinking like a clinician, reading the full chart and tuning risk to each patient’s baseline.

More lead time, less noise

compared to EHR

3+

hour earlier

lead time

20x

lower flag
volume

Learn More

Learn More

Source: Data from Bayesian customer using Epic sepsis algorithm

Targeting top drivers of mortality and hospital utilization

Sepsis

Likelihood of sepsis mortality increases by 8% with every hour of delay¹

Readmissions

14% of Medicaid patients are readmitted within 30 days²

Deterioration

40% to 80% of unplanned ICU admissions are preceded by deterioration signs³

Palliative Care

Only ~50% of patients who would benefit from palliative care actually receive it⁴

Transitions of Care

1 in 5 discharges from the acute hospital are delayed due to non-medical reasons, including failure to plan for PAC⁵

Heart Failure

Only 2% of HFrEF patients are discharged on appropriate therapy⁶

HAPI

HAPIs are associated with a 57% longer LOS⁷

Malnutrition

Hospital malnutrition affects 20-50% of patients but is diagnosed in <10%⁸

Now, when we say,

“we are doing

everything we can”

It is not a hope.
It is a truth.

Now, when we say,

“we are doing

everything we can”

It is not a hope.
It is a truth.

Now, when we say,

“we are doing

everything we can”

It is not a hope.
It is a truth.

Now, when we say,

“we are doing

everything we can”

It is not a hope.
It is a truth.