As the U.S. continues to suffer from an opioid addiction epidemic, electronic health record data have the potential to help clinicians better predict who is most likely to die or experience other serious complications from abuse of the drug class.
Researchers at Geisinger Health System in Danville, Penn., analyzed the EHRs of more than 2,000 patients admitted to the hospital for overdoses between April 2005 and March 2015. Among their findings: 9.4 percent of patients died within a year, and those taking higher doses of prescription opioids combined with psychotropic medicines need closer monitoring.
Results of Geisinger’s 10-year retrospective analysis were presented June 5 at the International Conference on Opioids in Boston. Researchers focused on the problem of opioid overdoses, which according to the Centers for Disease Control and Prevention have increased dramatically in the U.S. over the past decade and a half, rising from 8,407 deaths in 2000 to 28,647 deaths in 2014.
“I didn’t know the extent of the problem until we did this study,” says Joseph Boscarino, an addiction researcher and senior epidemiologist at Geisinger, one of the country’s largest healthcare organizations, serving more than 3 million residents in central, south central and northeast Pennsylvania.
As Boscarino points out, opioid dependence is a complex health condition with social, psychological and biological contributing factors. Geisinger’s EHR research, funded by Indivior, a Richmond, Va.-based opioid addiction treatment drug company, found that marital status, mental health and employment status were all important predictors of negative patient outcomes that include death, repeated overdoses, frequent healthcare service use and higher related costs.
According to the EHR data, patients had an average age of 52, were more often female (54 percent), not married (64 percent) and unemployed (78 percent). In addition, they had concurrent chronic disease, including cardiovascular disease (22 percent), diabetes (14 percent), cancer (13 percent) and the presence of one or more mental health disorders (35 percent), such as anxiety, depression and schizophrenia.
Coverage by public health insurance, such as Medicaid, or no insurance coverage was also a big predictor of complications, observes Boscarino.
Having concurrent chronic diseases, mental disorders and use of psychotropic medications such as anti-depressants resulted in higher prescription opioid use. And while patients who were married and had private health insurance were more immune to complications from drug abuse, those patients with a history of previous addiction, mental illness and other chronic diseases were all found to be conditions associated with adverse overdose outcomes.
“The predictors were pretty obvious ones,” says Boscarino. “If they had any psychiatric disorder or if they used other psychoactive medications, they were at higher risk. And, the more opioids they had in the past, the more likely they were to overdose.”
EHRs can be a powerful tool in reducing the risks associated with opioid overdoses by providing alerts to providers about potential red flags, Boscarino contends.
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