Data contained in the EHR could predict which patients are more likely to experience an opioid overdose.
Researchers at Danville, Pa.-based Geisinger Health System analyzed the EHRs of more than 2,000 patients admitted to the hospital for overdoses between April 2005 and March 2015. The average patient admitted for an overdose was 52 years old, female, unmarried and unemployed.
Using EHR data, the researchers extracted trends predicting the best and worst patient outcomes. They found history of previous addiction, mental illness and comorbidities were associated with adverse overdose outcomes, including death. Patients who were married and had private health insurance tended to have more positive outcomes.
"Our study suggests opportunities for identifying patients at-risk for overdosing," said Joseph Boscarino, PhD, an addiction researcher at Geisinger and lead author of the study.
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