AI for Interoperability in Health Care: Philips’s Carla Goulart Peron

2026-06-01 · Source: MIT Sloan Management Review · Field: Health & Wellbeing — Healthcare Systems & Policy, Medical Devices & Health Technology, Clinical Care & Medical Practice · Depth: Intermediate, extended

Summary

Dr. Carla Goulart Pegoraro, Chief Medical Officer at Philips, discusses the company's full shift to healthcare technology, encompassing imaging, patient monitoring, and AI-based clinical tools. Drawing from her experience as a physician in Brazil's resource-constrained public health system, she emphasizes AI's potential to bridge care gaps, improve access, and enhance diagnostic capabilities. A key example is Philips's FDA-cleared Smart Heart, an AI-driven one-click automation for cardiac MR planning, which reduces setup time from 15 minutes to 30 seconds, significantly boosting machine throughput and technician efficiency. Pegoraro highlights AI's additive role in healthcare, addressing the massive supply-demand imbalance and the importance of diverse data for equitable algorithms, citing the historical 5ml blood loss standard. She identifies global interoperability, supported by data standardization, evolving reimbursement, and adaptive regulation, as the most impactful AI capability for future healthcare.

Key takeaway

For healthcare executives and AI strategists evaluating new technologies, prioritize AI solutions that enhance interoperability and automate routine tasks. Implement tools like Philips's Smart Heart to drastically improve diagnostic throughput and technician efficiency, directly addressing the massive supply-demand gap. Ensure AI algorithms are trained on diverse patient data to build trust and avoid bias, particularly for underrepresented populations like women's cardiac health. Advocate for regulatory and reimbursement system evolution to support these transformative technologies.

Key insights

AI in healthcare augments clinical capabilities, improves access, and requires interoperability, diverse data, and adaptive regulation to address global care gaps.

Principles

• AI should add to, not replace, human clinicians.
• Diverse data is crucial for equitable AI algorithms.
• Interoperability is key for transformative healthcare.

Method

Smart Heart automates cardiac MR planning via one-click AI, reducing setup from 15 minutes to 30 seconds. This improves image quality, machine throughput, and reduces technician burden.

In practice

• Use AI to automate repetitive diagnostic tasks.
• Incorporate diverse patient data into AI training.
• Prioritize interoperability in health tech development.

Topics

• AI in Healthcare
• Healthcare Interoperability
• Medical Imaging AI
• Philips Smart Heart
• Health Equity
• Diagnostic Automation

Best for: AI Product Manager, Director of AI/ML, Consultant, Executive

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Editorial summary, takeaway, and curation by AIssential. Original article published by MIT Sloan Management Review.