Dr Harlan Krumholz on Using New Technologies, Data Generation to Prevent or Address Epidemics

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If we’ve got data moving, and if we’re analyzing it in smart ways in real time, we should be able to detect problems within our healthcare system much more rapidly than we have been able to in the past, explained Harlan Krumholz, MD, SM, the Harold H. Hines Jr professor, Medicine and Epidemiology and Public Health, Yale School of Medicine, and director, Center for Outcomes Research and Evaluation, Yale-New Haven Hospital.

Transcript

How can new technologies or better data generation prevent or address epidemics, like the current opioid epidemic?

It we’ve got data moving, and if we’re analyzing it in smart ways in real time, we should be able to detect problems within our healthcare system much more rapidly than we have been able to in the past. Things like the opioid epidemic shouldn’t have been by chance. Enough evidence accumulates, and all of a sudden it becomes a national priority. We should be able to understand this early; we should be able to see what costs are being accrued, what suffering is associated with it, how people are being burdened by it, and how prescriptions are going up. We should have a dashboard and dashboards that help us understand what’s moving and what’s not, and that’s true in noncommunicable disease problems, behavioral problems, and infectious problems. We should be tracking this all the time.

An example of this is readmissions. We implement a policy, but the truth is we can only really track readmissions about a year later, so we can’t be agile, we can’t tweak the policies, and we can’t understand where we’re going wrong, because we’re not getting data back fast enough. We need to be able to have a picture of the entire healthcare system. It needs to be streaming in ways that inform us, and help us be able to target interventions, and then, honestly, within the healthcare systems, we need to be doing A/B testing just like software developers do. We need to try different things, get results, understand what they do, and be able to continue to iterate them over time, so that we can improve. Without that, we’re stuck in a situation where we may make change, a year later we find out what that change did, and it may take us another year to make another change. We’re moving way too slow, and we’ll never learn that way. So, we both have to be able to detect problems, address them, understand what our interventions are doing, and be able to rapidly iterate if we want to be a true learning healthcare system.