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Marlee Ravid

3 Things Experts Want to Share About AI Integration

Adoption, Outcomes, System Integration, Workflow
Table of Contents

Integrating AI in healthcare is transforming patient care, but is not without its challenges. Its success hinges largely on a thoughtful and strategic approach. Drawing from insights shared by industry leaders, here are three key takeaways for health systems looking to effectively leverage AI and integrate.

1. Think Enterprise-Wide: AI Needs to Be a Scalable, Platform Solution

AI integration is most effective when approached as an enterprise-wide initiative rather than a collection of siloed tools. Debbi Cancilla, EVP and CIO at Temple University Health System, emphasized the importance of scalability across the healthcare system. AI solutions should be viewed as platforms that can evolve and expand to meet the diverse needs of different departments and facilities. A strong AI partner can provide a platform that allows seamless communication and coordination across the entire health system, ensuring that the technology can scale as the organization grows.

Key Insight: Approach AI as a scalable, enterprise-wide platform that fosters communication and coordination across your health system, ensuring long-term adaptability and growth.

2. Successful AI Integration Requires Strong Change Management

AI projects are far more than IT initiatives–they require comprehensive change management across the organization. Jeffrey Sturman, SVP and CDO at Memorial Healthcare System, stressed that AI efforts must involve operations, clinical workflows and business processes. Successful AI integration demands executive sponsorship and a governance structure that brings together stakeholders from different areas of the organization. Treating AI as a holistic initiative ensures that it aligns with broader organizational goals and drives meaningful improvements.

Key Insight: Ensure that AI integration is supported by robust change management, involving leadership and stakeholders from across the organization to align AI initiatives with clinical and operational goals.

3. Focus on Value: AI Should Improve Care Quality, Patient Experience and Cost Efficiency

At the heart of AI integration should be the goal of enhancing patient care. Sarah Kramer, MD, reminded us of the triple aim: improving care quality, enhancing patient care and reducing costs. AI should deliver on these promises by providing better care more efficiently. If an AI solution doesn’t support these core objectives, it may not be worth pursuing.

Key Insight: Ensure that your AI initiatives are aligned with the Triple Aim – delivering high-quality care, improving patient experience and reducing costs. 

If you’re interested in diving deeper into the world of clinical AI, explore our library of Lessons From the Inside videos. Here, AI trailblazers from leading institutions share their real-world experiences and insights on successfully integrating AI into healthcare.

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Marlee Ravid

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