Reducing Variability of Care with Bayesian’s AI Platform

o3/05/23 –Reducing Variability of Care with Bayesian’s AI Platform

Inconsistent and variable care delivery can lead to negative consequences for hospitals, patients, and payers. Bayesian’s AI platform is designed to help reduce variability in care, improve clinical outcomes, and enhance overall patient satisfaction.

Defining Variability

Variability of care refers to the differences in the way patients are treated and the outcomes they receive based on a wide array of factors such as demography, what hospital they have access to and the care practices employed in their treatment. There are many factors contributing to variability, including lack of evidence-based protocols and fragmented care delivery systems.

The Impact of Variable Care Practices

Variability of care can lead to unequal access to care, inconsistent quality of care, and higher costs for patients, hospitals and payers. These can affect patient satisfaction and create a lack of trust in the healthcare system. Payers also face financial consequences from variability in care, as they may have to cover the cost of additional treatments, longer hospital stays, or readmissions.

How Bayesian’s AI Platform Addresses Variability

Bayesian’s AI platform is designed to address variability in care by providing clinicians with real-time insights and personalized treatment recommendations. The platform uses an adaptive, modular framework that considers a patient’s unique physiology, clinical protocol, provider workflow, and hospital operations. This approach helps clinicians make more informed decisions and reduces the likelihood of variability in care delivery for a wide range of critical condition areas such as sepsis, all-cause deterioration, pressure injuries, and transitions of care, just to name a few.

Practical Uses of Bayesian’s Clinical AI to Standardize Care Practices:

• Bayesian’s AI platform can be tailored to different clinical settings and hospital needs, providing a personalized approach to care.
• The multi-modal platform identifies patterns and trends in patient data that traditional practices/methods may miss.
• Bayesian provides access to evidence-based guidelines and best practices, leading to better treatment decisions and outcomes.
• By automating certain tasks, the platform reduces the time it takes to provide care, improving patient outcomes and reducing costs associated with unnecessary procedures and extended hospital stays.

Our Unique Approach

Unlike previously studied models, Bayesian’s approach is clinically grounded, thinking like a clinician. Clinicians use the platform as an extra set of eyes and ears, making it an effective tool in improving the overall quality of care. The platform uses Bayesian statistical models to analyze patient data, such as medical history, lab results, and vital signs. These models allow clinicians to identify potential risks and predict patient outcomes based on data from similar patients. The platform also provides real-time feedback to clinicians on their treatment plans, alerting them to any potential issues or opportunities for improvement.

Benefits of Reducing Variability

Variability in care can have negative consequences for hospitals, patients, and payers. However, with Bayesian’s AI platform, clinicians can have access to real-time insights and personalized treatment recommendations that can help reduce variability in care delivery. By using Bayesian’s AI platform, hospitals can improve clinical outcomes, enhance patient satisfaction, and reduce costs associated with longer hospital stays or readmissions.