How to use AI to Improve Healthcare Data Quality With: Rajiv Haravu
In this in-depth interview, Rajiv Haravu, SVP of Product Management at IMO Health, explores the complexities of healthcare data normalization and its vital role in improving data quality across clinical systems. Haravu outlines the challenges of variability in documentation, from lab results to unstructured physician notes, and shares how IMO’s Precision Normalize and Precision Sets products address these issues. He discusses the interplay between structured and unstructured data, the role of terminology management, and the importance of adapting to evolving definitions. With insights on AI and natural language processing, Haravu reveals how IMO is integrating advanced tools while maintaining precision in clinical coding—empowering healthcare organizations to unlock the full potential of their data.
Episode Contents:
About the Guest
Rajiv Haravu is Senior Vice President of Product Management at IMO Health, leading products for data normalization, value set management, and clinical NLP. His background spans health information exchanges, research informatics, and medical device integration.
Key Takeaways
- Standardizing healthcare data is essential for accuracy
- AI enhances but doesn't replace clinical coding
- Surveillance is key to preventing AI model drift
Transcript Summary
Q: What is the main challenge in healthcare data normalization?
A: Variability in how medical concepts are documented, leading to data quality issues.
Q: How does IMO Health address this?
A: Through Precision Normalize and Precision Sets, standardizing terms and enabling accurate data analysis.
Q: What role does AI play?
A: AI supports but does not replace coding, improving efficiency and accuracy when paired with proprietary data assets.
More Topics
- AI in Patient Care
- AI in the Healthcare Industry
- AI and Medical Innovation
- Healthcare Ethics and Policy
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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.