Data Analytics

The Widespread Benefits of Federal Predictive Data Analytics

Health and welfare agencies at the state and local level gain information from national resources.

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Gienna Shaw is an independent journalist with more than 25 years of experience as a writer and editor. She specializes in business, technology and healthcare.

As the federal government makes headway with predictive data analytics at the federal level — using automation and better data management to try and put itself in a proactive position — agencies are also using those resources to support state and local entities.

The Department of Health and Human Services, for example, is working to improve child welfare outcomes using predictive models to estimate future risk of maltreatment, serious injury or fatality; forecast the likelihood of repeated maltreatment; or evaluate a neighborhood’s risk level for abuse, for example.

Predictive analytics can also improve agency operations by evaluating caseworker turnover or identifying trends in the quantity of incoming cases, letting local- or state-level employees focus on current caseloads rather than trying to tease out future trends but giving them the information they need to prevent those trends if they’re unwelcome ones.

In addition, the Centers for Disease Control and Prevention is using predictive analytics to forecast future probabilities of disease patterns, health behaviors and other variables, using population and other data to influence health decision-making.

Federal Data Serves as a ‘Public Utility’ for States

In North Carolina, the Digital Health Institute for Transformation, a nonprofit education and research organization based in Chapel Hill, N.C., and its local partners are using funds from the federal COVID-19 relief effort to build a predictive model to guide businesses, community organizations and others in making reopening decisions.

The decision support tool is powered by a variety of national and regional information, including health, labor, economic and occupational data.

DHIT president Michael Levy says the federal government has a role to play in helping state and local governments use predictive analytics to create similar programs and improve public health and the economy, just as it created greater mobility and boosted commerce by building highways across the U.S.

“What we’re seeing is a new public utility emerging that’s no different than water and energy,” he says.

Full collaboration on predictive analytics between the federal government and the rest of the U.S. may still be a work in progress.

“We’re still at the very beginning of the maturity curve,” Levy says, “but you have to start building the infrastructure one brick at a time.”

LEARN MORE: How do gencies use predictive analytics to gain efficiencies and save taxpayer dollars?

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