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Cleveland Clinic, a nonprofit academic medical center, is implementing Artificial Intelligence as an enterprise priority. This article explores two key AI applications: ambient AI documentation for clinicians to reduce paperwork, and AI-driven sepsis detection to improve early diagnosis and patient outcomes, highlighting their partnerships and rollout strategies.
Cleveland Clinic addressed clinician burnout and excessive administrative tasks by deploying ambient AI for documentation. After a thorough head-to-head evaluation of five vendors, Ambience Healthcare was selected for its superior documentation quality and responsive engineering support. This AI tool captures patient-clinician conversations via a phone app and automatically drafts structured clinical notes directly into Epic, Cleveland Clinic’s EHR system. The phased rollout strategy, prioritizing standardized primary care workflows, led to widespread adoption by over 4,800 clinicians across more than 3.5 million encounters. Results indicate significant improvements, including a nearly 50% reduction in after-hours documentation time, increased patient face time, and a notable decrease in cognitive burden for clinicians.
To improve outcomes for sepsis, a leading cause of death in U.S. hospitals, Cleveland Clinic implemented Bayesian Health's AI platform for real-time detection. This system continuously analyzes electronic medical record data like lab tests, vital signs, and clinical notes to identify sepsis risk earlier than traditional rule-based methods. A pilot study at Cleveland Clinic Fairview Hospital involving over 3,330 patients showed a tenfold decrease in false alerts and a 46% increase in identified sepsis cases, with a sevenfold rise in cases flagged before antibiotic administration. This enhanced signal quality boosts clinician trust and enables earlier intervention, leading to plans for expansion across 13 hospitals in Ohio and Florida, and future co-development of AI modules for other critical conditions.