Kaiser Permanente researchers have received a major grant from the National Institute on Drug Abuse to examine the role of opioid use in suicide risk and develop better tools to help clinicians identify patients who are at highest risk. The three-year, $1.4 million study will be led by Bobbi Jo Yarborough, Psy.D., an investigator at the Kaiser Permanente Center for Health Research in Portland, Oregon.
Both suicide deaths and opioid-related overdose deaths in the U.S. are on the rise. In 2015, the age-adjusted suicide rate was 13.3 per 100,000—a 27 percent jump from 1999, according to the National Center for Health Statistics. Over the same period, the rate of suicides with opioid poisoning as a contributing cause doubled, and the rate of opioid-related overdose deaths tripled.
“We’ve done preliminary work suggesting that 22 to 37 percent of opioid-related overdoses are, in fact, suicides or suicide attempts,” said Yarborough. “While health care settings are ideal places to intervene to prevent suicides, clinicians aren’t able to easily determine which of their patients are at elevated risk. Our ultimate goal is to develop the most accurate suicide risk prediction tools and put them into the hands of clinicians. If our study is successful, clinicians will have a powerful new resource in the fight against suicide.”
The new study will use the power of machine learning and predictive analytics, which allow researchers to find meaningful patterns in large datasets. The study will leverage Kaiser Permanente’s electronic health record system to create tools for clinicians to help prevent future suicides.
The existing suicide prediction models were developed under the auspices of the Mental Health Research Network, a group of 13 research sites embedded within U.S. health systems that serve a combined 12.5 million patients.
The models include a large number of variables that can predict the likelihood of a suicide attempt within 90 days of a mental health or primary care outpatient visit. These variables include medical, mental health and substance use disorder diagnoses; current and past prescriptions; and health care use patterns.
Under the new study, researchers will evaluate the following variables for their ability to improve prediction of suicide attempts or death: illicit or prescribed opioid use, opioid use disorder, discontinuation or substantial dose reduction of prescription opioids, and prior nonfatal opioid-related overdoses. Yarborough and her colleagues also will assess whether the strength of these risk predictors varies between men and women.
“We know that opioid use, opioid overdose, and suicide are related, but we need much more specific information to guide our efforts at prevention,” said Gregory Simon, M.D., M.S. in public health, principal investigator of the Mental Health Research Network, and a co-investigator on the new study. “The findings from this study will be a great asset to the public health community.”
The new study will include all seven of the Mental Health Research Network sites that collaborated in the development of the existing suicide risk prediction model: Health Partners in Minnesota; Henry Ford Health System in Michigan; and the Kaiser Permanente regional groups in Colorado, Hawaii, Southern California, Washington, and the Northwest (Oregon and Southwest Washington).
The researchers from those sites will be working with a dataset that includes approximately 24 million medical visits, 35,000 suicide attempts, and 2,600 suicide deaths, according to Kaiser Permanente.