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A Healthy Dose of Simplification at CDC

Problem statement: The Centers for Disease Control and Prevention’s (CDC) ability to gather and gain insights from public health data was hindered by wide variability in how that data was being managed at the state and local levels.

Complicated data reporting was a well-known issue at CDC long before the COVID-19 pandemic developed. But the crisis gave the convoluted processes new — and not very positive — meaning and exasperated already frustrated physicians and laboratories required by law to report notifiable health conditions.

“We’ve got a very federated system. There’s the national level with CDC and some other partners, there’s state health departments, there’s local health departments, there’s sometimes city health departments,” said Dr. Daniel Jernigan, Deputy Director for Public Health Science and Surveillance at CDC. “There’s variation across that whole landscape, where one state may have counties as the predominant implementers of public health, others may have states. Some, like Texas, have health districts. It’s really variable as to how public health gets administered.”

On top of that is a distributed health care system, meaning no common system or data standards. As a result, when doctors diagnose hepatitis, for instance, they must report it to multiple places, such as a local and state health department. But the staff at those departments tend to be under-resourced, overworked and lacking data skills and technology. They often enter the information manually after receiving reports by fax, Jernigan said.

When the Coronavirus Aid, Relief and Economic Security Act required “every laboratory that performs or analyzes a test that is intended to detect SARS-CoV-2 or to diagnose a possible case of COVID-19” to report the results from each such test to the Secretary of the Department of Health and Human Services, that shed light on these silos.

Solution: Ease Information Sharing

In 2020, CDC launched the Data Modernization Initiative (DMI), a multiyear “effort to modernize core data and surveillance infrastructure across the federal and state public health landscape.” That includes commitments to strengthening public health data reporting, management and analytics across public health entities — and not just for COVID, but all health threats.

“Data modernization is looking at how to capture data automatically from the health care side — the laboratory or the doctor’s office — but also helping the state and local health departments to receive that electronic information and use it in ways that makes their lives easier,” Jernigan said. “Ultimately, we’re trying to get to faster, better data for decision-making at all levels of public health.”

To do this, CDC has established five priority areas, the first of which — building the right foundation — has had major impacts. For instance, an aspect of this is working with the Association of Public Health Laboratories’ APHL Informatics Messaging Services (AIMS), which is a cloud-based platform that serves as a central routing capability for cases nationwide, Jernigan said.

Using AIMS, physicians’ and labs’ electronic health records automatically send reportable illness information to health departments. “That is a transformation of how things have been done that shows a hugely efficient way of using cloud in order for that data to get to the right place in a much faster and robust way,” he said.

To ensure that the state or local health department has the cloud capabilities to receive that data, CDC is working with the U.S. Digital Service to come up with solutions, such as purchasing cloud services.

The data goes from the health departments into the National Notifiable Diseases Surveillance System database – a process that is also being updated, Jernigan said. “We previously did not have an agencywide cloud platform,” he said. “We do now have one that has been stood up on Microsoft Azure that we are using to, over the next three years, migrate multiple different systems at CDC into that environment. We have hundreds of systems at CDC.”

Additionally, CDC is working to use artificial intelligence (AI) to help foster predictive analytics and support the Center for Forecasting and Outbreak Analytics that the agency announced in April 2022.

Today, Jernigan can’t imagine CDC without cloud. “That’s like asking, ‘What would it be like without your smartphone?’ It would not be good,” he said. “The ability to know quickly what’s going on, the ability to share information, the ability to bring in data from multiple sources and use it to help with prevention, those things we’re years behind without cloud. It would not be possible.”

3 Takeaways

Focus on culture. “All the technology, all the cloud purchases, etc., doesn’t matter if the people that need to work in that environment aren’t ready for it or don’t understand it or feel threatened by it,” Jernigan said.

Don’t focus too much on cloud. The nontechnological policy issues must be addressed, too. “When you’re moving into the cloud and you’re starting to have shared resources and shared tools and shared standards and approaches, you have to have really robust governance to make sure that the needs of everyone that’s participating are being met and if there are problems, ways to troubleshoot that and to stop the development of silos,” he said.

Don’t underestimate the costs. “It takes a lot of money. It is expensive to move into the cloud. It’s helpful; there are things we couldn’t do before, but there are costs that were not there before as well,” he said.

This article appears in our guide, “Why Cloud Matters to You: A Reality Check.” To learn more about why cloud isn’t just the bailiwick of IT anymore, download the guide.

Photo by Artem Podrez via pexels.com

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