AI Opioid Risk Screening Tools Wrong 92 Percent of the Time

AI opioid risk screening tools

The advanced AI screening tools doctors and pharmacies rely on to identify patients at risk of opioid addiction may be doing more harm than good. AI has flagged the wrong people while missing thousands who genuinely need help.

A landmark new study found that AI-powered opioid risk scoring systems produce false positives at an alarming rate. The report raises urgent questions for patients, providers and anyone affected by the opioid epidemic.

Opioid Addiction Risk Tools are Failing Patients

Artificial intelligence tools like NarxCare and Epic scan electronic health records and prescription drug databases to generate Opioid Risk Scores (ORS) for patients. The AI shares these results with healthcare providers so that they can flag those considered at risk of opioid misuse or overdose. Patients flagged as high risk may be denied opioid prescriptions or dropped from care entirely. 

But this new study suggests that using opioid risk scores to predict patient behavior has major flaws. The study indicated that the system produced unacceptably high rates of false positives.

For the millions of Americans living with opioid addiction or managing chronic pain with prescription opioids, that’s not an abstract research finding. It can mean being cut off from legitimate medication, labeled a drug-seeker, or pushed out of the healthcare system entirely. All these scenarios can paradoxically increase overdose risk.

The Opioid Crisis

The study examined Epic’s opioid risk scores for 700,000+ American patients treated by primary care providers. Epic scored 99.6% as low risk, with only 0.4% flagged as high risk.

The accuracy gap between those two groups is stark. Of the 2,665 patients classified as high risk, only 185 received an overdose or opioid use disorder diagnosis. This indicates that Epic’s scoring system was accurate only 7% of the time. Conversely, it produced a false positive rate of 92.2%.

Lead researcher Dr. Stephanie Hooker of the HealthPartners Institute wrote that the tool’s misclassification rate “could undermine its external validity, leading to misallocated resources and missed interventions.”

The low-risk category isn’t clean either. Of the 2,362 patients who ultimately experienced an overdose or opioid use disorder diagnosis, Epic’s system had flagged only 185 as high risk. The numbers suggest more than 2,000 patients were incorrectly labeled as low risk.

The Problem’s Core

The tools aren’t just inaccurate. They might measure the wrong things entirely. Pain management expert Dr. Lynn Webster is a Senior Fellow at the Center for U.S. Policy and explains it’s a mistake to count diagnoses and overdoses in the same predictive model because they’re distinct events. Someone can overdose without having a diagnosis and vice versa.

“Opioid risk tools will always struggle to predict overdose death risk because overdoses can occur in patients who have no opioid use disorder and no aberrant drug-related behavior,” Webster relayed. “Some patients overdose even when they take their medications exactly as prescribed.”

The stakes are high because these systems are everywhere. Epic’s MyChart software has already collected data on 190 million patients. Major pharmacies like CVS and WalMart use NarxCare for their customers.

Flawed Scoring Deepens the Opioid Epidemic

Inaccurate risk tools may actively worsen the opioid epidemic by pushing people toward unregulated street drugs like heroin. When patients with legitimate opioid addiction or pain conditions are denied prescriptions or abandoned by their doctors, some turn to the illicit market, where new synthetic drugs like orphines have made overdose deaths much more likely.

Webster warns that both NarxCare and Epic scores “can be harmful if used punitively.” The overestimated risk can lead to forced tapering, patient abandonment that “paradoxically increase overdose risk.” Once a risk label enters a patient’s chart, “it can take on a false authority that changes how patients are treated.” 

For families navigating the opioid crisis, this means a loved one with a narcotic addiction could be quietly flagged, stigmatized, and shut out of care, with no way to appeal an algorithm’s judgment.

Opioid Use Disorder and Overdose Risk

Opioid use disorder is a chronic condition characterized by compulsive opioid use despite harmful consequences. It encompasses addiction to prescription opioids and illicit fentanyl, the latter is responsible for the majority of U.S. overdose deaths. 

Naloxone (Narcan) can reverse an opioid overdose when administered quickly and is available without a prescription in most states. Still, experts warn that naloxone might not be enough to reverse overdoses caused by polysubstance abuse, which consists of two or more opioids mixed together.

Harm Reduction & Treatment Options

Knowing the difference between physical dependence, addiction, and overdose risk is critical But AI tools appear to blur all three.

Even if AI has a long way to go, that doesn’t mean you should sit on the sidelines. Whether or not a risk tool has flagged you, effective opioid addiction treatment is available. Evidence-based options include:

  • Naloxone/Narcan: Anyone at risk of opioid overdose should have naloxone on hand. Many pharmacies now carry it without a prescription, and many health departments distribute it for free.
  • Fentanyl test strips: Because fentanyl contamination in the illicit drug supply is widespread, fentanyl test strips are a critical harm reduction tool. Check with your local health department for free distribution programs.

Peer support remains one of the most powerful tools in opioid addiction recovery. Narcotics Anonymous (NA) meetings are free, widely available, and welcoming to anyone struggling with narcotic addiction.

AI is new and can assist clinicians, but fellowship with peers is tangible, real, and lasts a lifetime. Call 800-934-1582(Sponsored) or browse our directory to find NA chapters anywhere in the U.S.

the Take-Away

The advanced AI screening tools doctors and pharmacies rely on to identify patients at risk of opioid addiction may be doing more harm than good. AI has flagged the wrong people while missing thousands who genuinely need help. A landmark new study found that AI-powered opioid risk scoring systems produce false positives at an alarming …