Researchers use health data to predict who will use opioids after hospitalization

March 5, 2018 by Nathan Gill, CU Anschutz Medical Campus
Credit: CU Anschutz Medical Campus

Researchers at the University of Colorado Anschutz Medical Campus are working to develop statistical models to better predict which patients will be prescribed opioid medications long-term following discharge from a hospital stay. Opioids are commonly prescribed in the hospital but little is known about which patients will progress to chronic opioid therapy following discharge.

In the U.S. last year, more than 63,000 people died of a drug overdose, with opioids involved in 75 percent of those deaths. According to the 2015 National Survey of Drug Use and Health, over 2 million people in the US had a prescription use disorder.

"Doctors and are increasingly aware of the dangers associated with overprescribing of opioids," said Susan Calcaterra, a fellow in addiction medicine at theCU School of Medicine. "We can assist physicians in making informed decisions about opioid prescribing by identifying patient characteristics which put them at risk progressing to chronic opioid use."

The study was published online in the February issue of the Journal of General Internal Medicine.

Calcaterra, lead author, said, "Physicians are moving away from using prescription opioids as the primary treatment of chronic, nonmalignant pain. For the hospitalized patient, our ultimate goal is to provide adequate pain control by using a variety of pain management modalities, in addition to, or in place of, opioid medications. In doing so, we may be able to limit the number of patients who progress to long-term opioid use."

Researchers aimed to develop a prediction to identify hospitalized patients at highest risk of progressing to chronic opioid use following hospital discharge. To develop the prediction model, they accessed data available in the electronic health record from Denver Health Medical Center, an urban, safety net hospital. Researchers defined chronic opioid therapy (COT) as either receiving a 90-day or greater supply of oral opioids with less than a 30-day gap in supply over a 180-day period, or filling ten or more opioid prescriptions over one year.

By accessing electronic health record data, researchers identified patient-specific variables which were highly associated with the progression to COT. These variables included having a history of substance use disorder, past year receipt of a benzodiazepine, an opioid medication or a non-opioid analgesic, receipt of an opioid at hospital discharge and high opioid requirements during hospitalization. Having a surgical procedure during the hospitalization was not associated with progression to COT. The model correctly predicted chronic opioid therapy (COT) in 79% of the patients and no COT correctly in 78% of the patients.

According to the authors, no prediction model has been published to identify hospitalized patients at high-risk of future COT. There are useful prediction tools to assess the patient's risk of including the Screener and Opioid Assessment for Patients with Pain (SOAPP-R) and the Opioid Risk Tool (ORT). However, these tools have not been validated in the hospital setting and they can be too time-consuming to consistently administer in a busy clinical setting.

"This could be incorporated into the electronic health record and would activate when a physician orders . It would inform the physician of their patient's risk for developing COT and may impact their prescribing practices," Calcaterra said.

She continues: "All of the data required to assess risk are already available in the electronic health record, the physician would not need to input additional information. This tool would be inexpensive to implement and helpful in busy hospital settings where physicians make important health care decisions on patients they may have only met the day before. Researchers plan to validate this model in other health care systems to tests its ability to predict COT in other patient populations."

Similar techniques are already used in medicine to help make predictions using electronic data, including models that help predict development of diabetes, pancreatitis severity, heart failure readmissions and sepsis.

"Our goal is to manage pain in hospitalized patients, but also to better utilize effective non-opioid medications for pain control," Calcaterra said. "Ultimately, we hope to reduce the morbidity and mortality associated with long-term opioid use."

Explore further: Researchers find new risk posed by opioid pain medication

Related Stories

Researchers find new risk posed by opioid pain medication

November 17, 2015
Patients with no recent history of taking opioid pain medication had a 25 percent higher risk of chronically using the drugs if they received them when discharged from the hospital, according to researchers at the University ...

Long-term opioid use has dropped among US military veterans

January 30, 2018
A new study in the Journal of General Internal Medicine, published by Springer, shows that opioid prescribing has dropped after a peak in 2012. Lead author Katherine Hadlandsmyth of the Iowa City VA Healthcare System and ...

Prescribing of opioids adds to patient satisfaction with care

January 24, 2018
(HealthDay)—Patients with musculoskeletal conditions who are using prescribed opioids are more likely to be highly satisfied with their care, according to a study published in the January/February issue of the Annals of ...

Opioid cessation may be more successful when depression is treated

February 5, 2018
Opioid cessation in non-cancer pain may be more successful when depression is treated to remission, a Saint Louis University study shows.

Longer duration of post-op opioid use associated with misuse

January 19, 2018
(HealthDay)—Each refill and week of opioid prescription following surgery is associated with an increasing risk of opioid misuse among opioid naive patients, according to a study published online Jan. 17 in The BMJ.

Plastic surgeons get tips on managing opioid addiction risk

October 2, 2017
Opioid medications prescribed for pain management after plastic surgery may contribute to the ongoing opioid epidemic, according to a special topic paper in the October issue of Plastic and Reconstructive Surgery, the official ...

Recommended for you

Doctors prescribe opioids at high rates to those at increased overdose risk

April 24, 2018
The number of first-time prescriptions for opioid drugs has not risen since about 2010, according to UCLA researchers. However, patients taking a class of drug known to increase the risk for overdoses were likelier to receive ...

Study: Ibuprofen, acetaminophen more effective than opioids in treating dental pain

April 17, 2018
Opioids are not among the most effective—or longest lasting—options available for relief from acute dental pain, a new examination of the results from more than 460 published studies has found.

Text messaging tool may help fight opioid epidemic

April 17, 2018
A new automated text messaging service may curb opioid abuse and reduce the likelihood of relapse while also decreasing treatment costs, according to researchers at Washington University School of Medicine and Epharmix, a ...

Marijuana-based drug gets positive review from US agency

April 17, 2018
A closely watched medicine made from the marijuana plant reduces seizures in children with severe forms of epilepsy and warrants approval in the United States, health officials said Tuesday.

Post-surgical opioids can, paradoxically, lead to chronic pain

April 16, 2018
Giving opioids to animals to quell pain after surgery prolongs pain for more than three weeks and primes specialized immune cells in the spinal cord to be more reactive to pain, according to a new study by the University ...

Animal study suggests common diabetes drug may also help with nicotine withdrawal

April 5, 2018
In a mouse study, a drug that has helped millions of people around the world manage their diabetes might also help people ready to kick their nicotine habits.

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.