NCQA Quality Matters-Episode 06 with Dr. Rebecca Jacobson

In this episode of Quality Matters, host Andy Reynolds sits down with Rebecca Jacobson, CEO of Astrata, to explore the challenges and opportunities in transitioning to digital quality measurement in health care.

“I’d want my billboard to say: “Digital quality, you can do it.”  Big things like this, big transformations that impact so much of the organization, they can be daunting, but we’ve seen plans make substantial progress that are clearly going to do very well. It can be done. Every quality team has it in them to guide this transformation and derive benefit. Just start now and have the confidence that you’re able to do it, that there are a lot of resources that help you.” Dr. Rebecca Jacobson

Rebecca offers an in-depth look at the sociotechnical shifts required for this evolution, sharing practical strategies to help organizations navigate this complex process. Discover how to overcome common obstacles, and learn about the real financial benefits that can convince even the most skeptical CFOs to invest in this transition. Rebecca also provides a candid assessment of the industry’s current state of readiness, emphasizing the importance of starting early for long-term success. She discusses why progress has been slower than expected and shares her updated timeline for widespread adoption.

In the podcast Brad Ryan, Chief Growth Officer of NCQA, adds some comments to the discussion by saying, “With regard to Rebecca’s comment about Natural Language Processing helping us through this transition, I would add this might be the best first clinical application for artificial intelligence. We have done a good job, as an industry, of digitizing clinical data. We have done a terrible job of standardizing what was collected and shared in that data. Artificial Intelligence and Natural Language Processing are an efficient, scalable way for us to take unstructured non-standard data into a standard format. That is the biggest lift. The real work is this data mapping to standard data. If we can get AI and NLP to be the front line workers for that data mapping, that takes us forward into the future tens to hundreds of times faster.”