Bayesian directs the attention of the clinician to patients at high risk. Clinicians are encouraged to interact with Bayesian and do not feel pressure to agree with the care signals. Bayesian’s AI thinks like a clinician by considering multiple data points in concert rather than individually. Clinicians use the platform as an extra set of eyes and ears.
To illustrate this concept, think of a provider or nurse weighing all the available data (labs and vitals from the last 48h, patient medical history etc.) and making a decision about a patient’s risk status. Bayesian is a silent colleague continuously reviewing all the data and calling attention to what matters most.
Recent, large outcome study showed 89% physician and care team adoption, leading to 1.85h earlier treatment for sepsis*.
Patient-specific, targeted
Signals arrive with clinically meaningful lead time*
Rigorously tested, proven
Structured to reduce bias and false signals
Context accompanies every signal for transparency
Read about how Bayesian achieved improved clinical and financial outcomes for one health system, driven by high adoption and continued engagement of the platform.
Decades of published research has validated our machine learning strategies, and over two years at academic and community hospitals has validated our adoption, engagement, and outcomes.
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