Hear from Lisa Morella, Senior VP of Data Governance & Analytics at CodaMetrix—and one of The Healthcare Technology Report’s Top 50 Women Leaders in Healthcare Technology of 2024—as she shares her journey and insights on the role of AI, data quality, and innovation in transforming patient care.
As the healthcare industry evolves, so does the way we utilize technology to improve patient care, optimize workflows, and make smarter decisions. Artificial Intelligence (AI) plays a crucial role in this transformation. But for me, the spark to pursue a career in AI began much earlier, rooted in a deep curiosity about data and patterns.
My passion for AI began with a fascination for patterns. Whether in math, science, or everyday life, I've always been drawn to the stories data can tell. Early on, I realized that AI, in essence, is about recognizing patterns at scale. As I delved deeper into AI, I saw it as an opportunity to uncover hidden structures within data, using those insights to solve real-world problems.
A strong AI platform should stand out through its data strategy—integrating various data types to deliver real-time, meaningful insights for health systems. Traditional analytics rely on siloed data, but by capturing full clinical context and applying advanced machine learning tactics, platforms can surface actionable trends. This enables healthcare leaders to make data-driven decisions that reduce costs and improve patient outcomes.
At CodaMetrix, AI-driven automation and advanced analytics have empowered my team to manage vast amounts of healthcare data efficiently. AI-powered tools like data governance and anomaly detection have improved our own data integrity, reduced errors, and ensured compliance. Additionally, AI-enhanced dashboards and natural language processing (NLP) tools have streamlined reporting, making complex data more accessible to stakeholders. These innovations not only accelerate our workflows but also allow us to provide more valuable insights, drive customer satisfaction, and improve healthcare outcomes.
One of the proudest moments of my career was bringing CMX Insights to market. It was an experience that combined my passion for data with real-world business impact. Leading the team to develop and launch these products, I saw firsthand how data could be transformed into actionable intelligence. By defining the right data models and ensuring smooth user adoption, we empowered customers to make data-driven decisions, guiding them on where to begin their automation journey.
AI’s impact in healthcare is undeniable, but success hinges on data quality and strategy. In Part 2, we’ll explore how AI serves as an augmentation tool rather than a replacement for healthcare professionals, emphasizing the balance between innovation and human oversight.
