From Paper to Population Health: A Q&A with Sanjeev Mehta, MD, MPH, Joslin Diabetes Center’s Chief Medical Information Officer and Director of Quality

-Trisha Gura/GluTrisha

A pediatric endocrinologist by training and “IT guy” at heart, Dr. Sanjeev Mehta joined the T1D Exchange Quality Improvement Collaborative to help design and implement its novel IT platform. Here, he looks out at the landscape of big data in medicine and offers insights into how it might best be captured to enhance care for individuals living with type 1 diabetes.

As a pediatric endocrinologist, what drew you to medical information technology?

 I have a longstanding interest in health services research starting back when I was in college. I always liked this notion of how we can leverage large data sets to better understand care delivery and outcomes. As I progressed in my medical career, it was natural to focus these efforts on my clinical passion: diabetes.

From your college days until now, what changes have you seen when it comes to health data?

 We went from lack of readily available data in paper-based medical records, to a paucity of key clinical information in electronic health records (EHRs). That’s because the EHRs were set up for billing, not for clinical documentation, especially for the nuanced care required for understanding diabetes.

For me at Joslin, the evolution has been about how I can get access to discrete, systematically captured data where you have extremely strict criteria for what can and cannot be entered. Basically, we are trying to get to the point where our EHR is viewed with that level of sophistication, yet deployed in a manner that isn’t burdensome for providers during their routine clinical encounters.

Are we now better able to collect standardized data outside of a controlled laboratory or clinical trial?

It depends. This whole movement to get people access to regulated EHRs has allowed us to conduct some high-level evaluations, such as diabetes prevalence, medication-based treatments, and general health outcomes. But to get to more nuanced questions, such as understanding what are the aspects of care that seem to work for the management of type 1 diabetes, we still have a long way to go.

What needs to happen for us to get there?

 Everyone is in support of standardization of diabetes-specific data, such as use of technologies and broader glycemic metrics. Our effort here in the T1D Exchange Quality Improvement Collaborative is to say, “Hey, how much standardization can we achieve at these 10 sites and use that experience to scale the solution to other sites?” And after that, the next step is creating clinical standards that can be used and supported by these organizations and institutions.

How will the Collaborative help make an impact on these and other challenges in type 1 diabetes care?

 Members are all engaged in the Collaborative, not just because they are smart and believe in it but because they can drive meaningful quality improvement at their organizations. When people start to see the T1D Exchange Quality Improvement portal and realize how they can use the data more to work with populations in their clinics, the whole effort will be quite compelling.

To learn more about the T1D Exchange Quality Improvement Collaborative, click here.




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