Insight by IQVIA

No perfect solution: How to embrace ‘fit-for-use’ in data modernization

The possibility of what they don’t know can paralyze public health agencies when making decisions. Instead, they should focus on actionable, timely data.

This content is provided by IQVIA Government Solutions.

Federal agencies have been working for years to meet a mandate to put their data to use in making evidence-based decisions. It can take years to conduct a study, analyze the data and arrive at a conclusion. Although that conclusion might be excellent, it’s also often too late.

“If you’re looking for a perfect solution, you’ll never get there,” said Nandini Selvam, president of IQVIA Government Solutions. “There is a combination of functional, strategic, structural aspects to what’s making data modernization really difficult. And the way it’s being laid out, it’s literally boiling the ocean in a way that I don’t know if any one of these agencies is even going to be successful.”
One of the lessons that came out of the pandemic is that government has a desperate need for data modernization. Public health agencies especially have various strings of data that they can’t pull together in a dashboard fashion, meaning they can’t use it or can’t operationalize it in a near real-time format.

And that’s a serious problem for public health agencies because their job is to get out ahead of the patient environment and the community at large. And they can do that better with more data at their fingertips. But they’ll never have perfect data, and that’s what their long-term data modernization plans don’t take into account. They’re paralyzed by the fact that they’ll never know what they don’t know.

Focus on ‘fit-for-use’

That’s why Selvam advocates for breaking out public health data modernization into manageable pieces. The first piece is existing data: baseline surveillance data on the population and its existing issues. That alone will never be perfect, but it allows for near-term predictions. That’s what they should modernize around, with a focus not on perfect data but what Selvam calls “fit-for-use” data.
“Start with the end in mind,” Selvam said. “You could have a thousand streams of data, but if you’re not actually using it for something, why are we collecting it? Start with understanding what it is you’re hoping to accomplish and then working your way back towards what are the fields of data that help you meet those objectives.”

And that’s where “fit-for-use” data comes in. Selvam said it’s important to allow leeway for less-than-perfect data. But in a field like public health, it doesn’t have to point to the exact answer. It has to point in a definitive direction.

“If your goal is to affect human care or human health, then this has to be much more timely. So I think this notion of balancing the right type of data with the right timing around it is what makes it fit for use,” Selvam said.

For example, in military health domain, it’s about having the right data within a common platform with standardized ontology in order to make the best possible decision for patient care as quickly as possible. It needs to be accessible, digestible and actionable. On the civilian side, in the case of the Department of Health and Human Services or the Centers for Disease Control and Prevention, the data is oriented more towards public health policy.

“We just helped CDC, for instance, more recently evaluate the uptake of the RSV vaccine, along with the renewals on the COVID vaccines, et cetera,” Selvam said. “So we were able to do weekly polls and that helped influence CDC communication strategy. It went back to the manufacturers to say, maybe you need to be having more conversations about this. It looks like we were able to show geographic tracking. So this kind of information is data-driven decision-making, data-driven policymaking.”

Importance of communication

And as for the nay-sayers, the amateur epidemiologists who think they know better than the CDC, and for that matter, the black swan events like COVID that are impossible to predict? Even the best data can’t help with that, so don’t obsess over it. Instead, that comes down to better communication, Selvam said. Public health officials need to be comfortable admitting what they don’t know, rather than waiting for definitive answers to communicate at all.

COVID illustrated this perfectly, she said. The public had so many questions: What is the effectiveness of masks, and when do they need to be used? Can it be transmitted through surface contact, or is it airborne? Sometimes officials said nothing because they weren’t sure yet, and that created distrust down the road when answers changed.

“And really, the answer should have been ‘we don’t know a lot of things. We’re going to do the very best we can while we do it. And sometimes that messaging is going to change.’ And I think that’s the HHS mindset. That’s fit-for-use,” Selvam said. “What I mean with this is you bring the public along where they see that you’re skinning your knees along the way. But they feel vested. Because the absence of that information is not really that helpful either.”

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