7th Global Gastroenterology and Artificial Intelligence Summit (Live)

9 -Shen
Pdf Summary
This document, authored by Dr. Lin Shen, Chief Medical Information Officer at Mass General Brigham and Harvard Medical School, provides a practical health system perspective on implementing AI in clinical practice within the complex and financially pressured U.S. healthcare landscape.<br /><br />Mass General Brigham, a large nonprofit integrated health system with multiple hospitals, ambulatory services, and a major research program, illustrates the challenges facing healthcare: rising costs outpacing GDP growth, surging employment expenses without improved outcomes, and physician shortages exacerbated by burnout and practice consolidations. Traditional financial “exit ramps” such as government borrowing and cost-shifting to employers and insurers are no longer sustainable.<br /><br />Several paths forward are identified: private-equity cost-cutting, crisis-driven disruption, and AI transformation. AI holds promise to automate administrative tasks, enhance diagnostics and chronic care management, reduce medical errors, and ultimately lower costs by diminishing unnecessary care.<br /><br />Healthcare executives must navigate these solutions amid competing local priorities and complex organizational structures. Effective AI implementation requires alignment between enterprise priorities—integrating viewpoints from medical officers, operations, finance, and other stakeholders—and robust governance frameworks. A tiered governance model is recommended, comprising an AI Governance Committee for overall strategy, an Implementation Oversight Group for use case evaluation, and project teams responsible for deployment and impact monitoring focused on safety, bias, privacy, and ROI.<br /><br />Integration challenges include aligning platforms, ensuring cybersecurity, managing vendor relationships, and scaling operational support with specialized ML operations capabilities. Engagement strategies emphasize building credibility, understanding decision-maker concerns, and fostering long-term relationships over transactional sales.<br /><br />Success stories at Mass General Brigham include ambient clinical documentation tools decreasing clinician burnout by over 20%, AI-assisted workflow optimization, and embedded large language model tools in EHRs. The document stresses AI as a horizontal, integrated infrastructure rather than siloed tech.<br /><br />In summary, healthcare organizations must align AI initiatives with business drivers, enforce transparent governance, anticipate scrutiny, and prioritize collaborative relationships to sustainably realize AI’s potential in clinical care.
Keywords
AI implementation
healthcare system
Mass General Brigham
clinical practice
physician burnout
healthcare costs
AI governance
machine learning operations
electronic health records
healthcare innovation