The Real Costs of Poor Data Interoperability in Healthcare With: Jordan Johnson, MSHA
In this illuminating interview, Jordan Johnson, MSHA, Founder and Principal of Bridge Oncology, unpacks the complexities behind healthcare data interoperability. Speaking with Dr. Sanjay Juneja, Johnson offers a deep dive into how interoperability—often oversimplified—functions in clinical, administrative, and technological workflows. Drawing from his experience as a legal and operational expert, Johnson discusses the downstream consequences of data misalignment and lack of standardization, especially in oncology and radiotherapy. With a strong stance on the need for regulatory frameworks and AI-powered infrastructure, Johnson highlights how true interoperability could reduce healthcare disparities, boost clinical efficiencies, and drive value-based care transformation. For any healthcare professional working with EHRs, payer systems, or health data, this conversation is essential.
Episode Contents:
About the Guest
Jordan Johnson is the Founder and Principal of Bridge Oncology, where he leads data-driven solutions to sustain oncology practices and expand patient access. He is a national thought leader in price transparency, healthcare policy, and operational innovation. https://www.linkedin.com/in/jordan-johnson-msha-m-jurr-mls-7bb49441/
Key Takeaways
- Data misalignment leads to billions in waste and disparities
- AI and structured data can accelerate real-time decisions
- Interoperability underpins successful value-based care models
Transcript Summary
What does interoperability mean in healthcare?
Jordan Johnson explains that interoperability is more than system connectivity; it's about whether technology, staff, and data can coexist in a way that improves outcomes, speed, and accuracy.
How does poor interoperability impact care delivery and cost?
He discusses how lack of data standardization leads to disparities, billing errors, and unnecessary loss. Real-time access and AI structuring can dramatically reduce this friction.
What are the legal and ethical risks of poor data sharing?
Jordan notes emerging litigation and liability concerns tied to unregulated AI tools and data sharing. Updated business associate agreements and federal standards are needed to avoid misuse.
Can AI help fix interoperability issues?
Absolutely. Johnson outlines how AI can automate redundant tasks, synthesize clinical data, and even operate remote imaging workflows, especially in underserved areas.
Will payers support AI-driven interoperability?
He believes they will, particularly because real-time, predictive analytics could reduce costs and improve outcomes, aligning perfectly with value-based care goals.
More Topics
- AI and Medical Innovation
- Healthcare Ethics and Policy
- AI in Patient Care
- AI in the Healthcare Industry
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About the Series
AI and Healthcare—with Mika Newton and Dr. Sanjay Juneja is an engaging interview series featuring world-renowned leaders shaping the intersection of artificial intelligence and medicine.
Dr. Sanjay Juneja, a hematologist and medical oncologist widely recognized as “TheOncDoc,” is a trailblazer in healthcare innovation and a rising authority on the transformative role of AI in medicine.
Mika Newton is an expert in healthcare data management, with a focus on data completeness and universality. Mika is on the editorial board of AI in Precision Oncology and is no stranger to bringing transformative technologies to market and fostering innovation.