New York-based United We Care is using artificial intelligence (AI) to help clinicians reclaim up to 40% of their weekly workload.

The Stella Clinical Copilot uses graph neural networks to analyse medical data, uncovering complex relationships between symptoms, diagnoses and treatments. This provides clinicians with real-time, personalised insights for better decision-making and improved patient outcomes.

Overwhelmed by administrative tasks, clinicians often have limited time for quality patient interactions. Stella tackles this by automating processes and streamlining workflows.

Clinical Copilot is built on four pillars:

• Data-driven accuracy: Stella leverages 150 years of research, more than 220 million relationships and 16 million biomedical insights to support clinical decisions with data.
• Efficacy: Leveraging best practices and real-time insights, Stella empowers clinicians to deliver effective care, improving patient outcomes.
• Efficiency: Effortless notes, smart automation and smooth EHR integration free up time for patient care.
• Measurable RoI: Improved documentation, reduced administrative burdens and increased patient satisfaction lead to increased RoI.

Stella generates accurate and concise clinical notes. It can dictate patient interactions, automatically capturing key details and generating summaries.

Grounded in extensive research, it transcends traditional reliance on only population-level data. Now, Stella delivers individualised insights, enhancing and supporting precision in clinical decision-making. Users can leverage Stella’s knowledge base to provide tailored recommendations for each patient.

“Stella Clinical Copilot is set to revolutionise clinical note-taking and streamline administrative tasks for healthcare professionals,” said Ritu Mehrotra, CEO at United We Care (www.unitedwecare.com). “It offers advanced patient data management, automated note generation and seamless integration capabilities, significantly reducing the administrative burden on clinicians and enhancing overall healthcare efficiency.”