The race is on to develop better ways to predict if patients will develop diabetes, heart disease or other critical conditions.

Spurred by employers and insurers that want health-care providers to prevent illness—and not merely treat it—doctors and hospitals are creating ever more complex algorithms to forecast their patients’ medical future. And they’re searching for new kinds of data to make those predictions as accurate as possible, mining behavioral, consumer and financial data for potential clues.

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Some hospitals are collecting new information from patients directly, while others have sought data from companies that sell consumer and financial information, or federal agencies that provide statistics on poverty, housing density and unemployment.

Knowing more about how people live—from their interests to their income—could prove useful as doctors look for clues to poor health and tailor interventions to address patients’ needs, potentially preventing illness and saving money, proponents of this approach say.

“So much of what determines a person’s health and well-being is independent of medical care,” says Rishi Sikka, senior vice president of clinical operations for 12-hospital Advocate Health Care in Downers Grove, Ill.

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