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Viraj Narayanan Explains COTA Findings on EMR Research

Fragmentation in the US healthcare system hinders implementation of efficient workflows when it comes to real-world data, said Viraj Narayanan, MBA, vice president of Life Sciences at COTA Healthcare.

Fragmentation in the US healthcare system hinders implementation of efficient workflows when it comes to real-world data, said Viraj Narayanan, MBA, vice president of Life Sciences at COTA Healthcare.

Transcript:

COTA presented research at ASH on the challenges of abstracting data from disparate EHR systems. What was being looked at and what did COTA find?

This was a collaboration that COTA did with the Multiple Myeloma Research Foundation. Essentially what we were trying to do was go direct to providers, on a patient by patient basis, to obtain EMR records. What we found through this process was essentially the operational workflow of trying to go to individual provider site to individual provider site, and individual patient to individual patient was pretty cumbersome and time consuming. Essentially, there is a lot of administration lag, there is financial lag, to actually operationalizing that process of workflow, which speaks to a lot of the fragmentation that is the reality of the US healthcare system, at least today.

What are some of the ways the challenges of using data from disparate EHR systems can be overcome?

For better or worse, the structural underpinnings of the US healthcare system is very fragmented. You've got providers that are consolidating today as a trend, but they're still super fragmented. You've got payers, who are playing a big role in having relevant data. Then you've got an increasing number of new sources like Apple Watch, where patients are starting to hold data and becoming more empowered to hold data. But at the end of the day, unfortunately, most of the relevant clinical information is still with providers and with payers. That is going to be where partnerships have to be formed, at least in the status quo, to build consortiums of relevant data across multiple different sources.

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