Can EHR Analytics Predict Opioid Overdoses?

Yes, to some degree.

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Opioid addiction has become a national epidemic recently. In 2014, over 47,000 people died of a drug overdose in the U.S. Over 28,000 of those deaths were the result of prescription opioids.

In the U.S. since 1999, fatal prescription opioid overdoses have quadrupled. Each day, emergency rooms treat over 1,000 people for the misuse of prescription opioids.

So how can EHR analytics predict opioid overdoses?

Geisinger Health System has analyzed electronic health record (EHR) information for patients admitted with overdoses for over a ten-year period.

The data factors in mental health, marital status, employment status, and other factors to determine which patients have the highest risk of dying from overdoses or experiencing other complications.

What did they find?

They were able to help predict which patients had the largest risk for overdoses and complications.

Who has the largest risk?

Patients that have an average age of 52, were more often female, unmarried and unemployed had the highest risk.

Patients with a history of addiction, other mental illnesses, or chronic diseases had the worst outcomes. Patients with higher opioid doses and psychotropic medicines need close monitoring.

Married patients with private health insurance had the least likelihood of fatal overdoses and other complications.

The study shows opportunities to identify the most at-risk patients.

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