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Dr Vinay Kini Discusses the Growing Influence of the EHR in the Transition to Value-Based Care

With the expansive growth of the electronic health record in the past decade, the extraction of meaningful use metrics is vital in the transition to value-based care, said Vinay Kini, MD, MS, cardiologist at the UCHealth Heart and Vascular Center–Anschutz Medical Campus.


With the expansive growth of the electronic health record in the past decade, the extraction of meaningful use metrics is vital in the transition to value-based care, said Vinay Kini, MD, MS, cardiologist at the UCHealth Heart and Vascular Center–Anschutz Medical Campus.

Transcript

Your argument in the session “Great Debates in Quality and Outcomes” at this year’s American Heart Association meeting focuses on the electronic health record [EHR]. Can you discuss its growing presence in the transition to value-based care?

EHR uptake over the last 10 years after the Affordable Care Act has been almost universal. I think something like 96% of hospitals now use electronic health records. In thinking about the transition to value-based care, what really, I think EHR is going to be the focus of, is some of these quality metrics or meaningful use–is kind of the term that’s been used over the last several years. These are things that are quality or process measures that really need to be extracted from the EHR because they’re not things that can be measured on kind of a more global scale by administrative data. So, to give you an example, right now a process measure that should be able to be extracted through the EHR would be something like when a patient is admitted for a heart attack, did they get the appropriate testing–the appropriate referrals afterward, the appropriate medications and treatments. Those things should be easily extractable through the electronic health record. Some of the bigger things like 30-day mortality or 30-day readmissions after hospitalization for a heart attack–those things will likely still stay in the realm of kind of the administrative data sets.

 
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