Mayo Clinic, Bayesian Health Co-Develop AI Tool to Improve Palliative Care Access
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The solution is built on Bayesian Health’s clinical intelligence platform and integrates directly into hospital electronic health record systems, enabling care teams to access patient risk signals within existing workflows.
Mayo Clinic and Bayesian Health have co-developed an AI-powered clinical solution designed to identify hospitalized patients who may require palliative care earlier in their treatment journey, aiming to improve outcomes and reduce avoidable readmissions.
The solution is built on Bayesian Health’s clinical intelligence platform and integrates directly into hospital electronic health record systems, enabling care teams to access patient risk signals within existing workflows. It is designed to flag patients with serious illness who may have unmet palliative care needs, including pain management and caregiver support.
According to the organizations, nearly one-third of hospital readmissions involve patients with serious illness, yet fewer than half receive palliative care consultations. The AI tool seeks to close this gap by enabling earlier identification and intervention.
In a randomized clinical trial conducted at Mayo Clinic, the AI system was associated with a 44% increase in timely palliative care referrals. The study also reported a 25% reduction in 60-day readmissions and a 28% reduction in 90-day readmissions, along with improved patient quality of life outcomes.
The tool provides clinicians with real-time alerts and contextual patient information, allowing palliative care teams to identify eligible patients across the hospital and prioritize consultations. It also offers bedside clinicians actionable guidance within clinical workflows to support decision-making.
Mayo Clinic’s Department of Medicine led the clinical development and validation of the solution, while Bayesian Health handled integration into electronic health records and platform deployment. The system continuously learns from clinician feedback and patient data to improve accuracy over time.
The collaboration is part of Mayo Clinic’s Practice Transformation Ventures framework, which supports technology partnerships aimed at improving clinical care delivery. Data scientists from Mayo Clinic’s Kern Center for Health Care Delivery contributed to model development and evaluation.
According to the partners, this marks one of the first large-scale AI deployments at Mayo Clinic designed to support end-to-end clinical decision-making in hospital settings, with a focus on improving coordination between care teams while maintaining patient data confidentiality.
Suchi Saria, Ph.D., founder and CEO of Bayesian Health, said the platform is designed to help clinicians reach patients earlier in their care journey, when interventions can still change outcomes.
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