A Predictive Algorithm to Detect Opioid Use Disorder: What Is the Utility in a Primary Care Setting?

Area of Science:

• Precision Medicine
• Primary Care
• Clinical Decision Support

Background:

• Opioid use disorder poses a significant challenge in primary care.
• Effective risk stratification tools are needed to guide clinical decision-making.

Purpose of the Study:

• To evaluate the clinical utility of an algorithm-based decision tool for assessing opioid use risk in primary care.
• To determine the impact of this tool on physician decision-making and patient outcomes.

Main Methods:

• A prospective, longitudinal study involving 1822 patients across 18 primary care clinics.
• Patients were risk-stratified into low, moderate, and high categories using a precision medicine profile.
• Physicians documented their actions and perceptions regarding the tool's utility.

Main Results:

• 47% of physicians used the tool to guide clinical decisions, rating its benefit at 3.6/5.
• 88% of clinicians perceived some benefit for patient care.
• Tool utilization led to changes in opioid prescriptions and a 2.7-point average reduction in patient pain scores.

Conclusions:

• The algorithm-based tool is a valuable resource for primary care physicians to manage opioid use disorder risk.
• Physicians reported enhanced clinical improvement for minority patients.
• Guidance from the tool significantly reduced patient-reported pain.