# Do Postoperative Orthopedic Patients Accurately Report Their Narcotic Medication Usage Using the Interventional Pain Assessment Drugs Scale?

## TL;DR

This study shows that patients can accurately report their opioid use after surgery using the IPA-D scale, which could help improve pain management and reduce misuse.

## Contribution

The study demonstrates the IPA-D scale's high accuracy in self-reported opioid use across different dosage categories.

## Key findings

- The IPA-D scale showed 100% accuracy for classes A and B with 0.0 MMEs.
- Class E (≥80 MMEs) had 94.4% accuracy with an average MME of 140.83.
- The IPA-D scale is a reliable tool for real-time opioid monitoring in clinical settings.

## Abstract

Introduction: Accurately assessing opioid consumption is critical for effective postoperative pain management and reducing misuse. While prescription monitoring tools like the Michigan Automated Prescription System (MAPS) provide objective data, they may not reflect actual patient behavior. This study evaluates the accuracy of self-reported opioid use using the Interventional Pain Assessment-Drugs (IPA-D) scale.

Methods: A prospective IRB-approved study enrolled 753 postoperative orthopedic patients at a Level I trauma center from June 2022 to June 2023. Participants completed the IPA-D survey to self-report opioid usage, which was stratified into five classes based on morphine milligram equivalents (MMEs). These reports were compared to MAPS prescription data to determine classification accuracy.

Results: The IPA-D scale demonstrated high accuracy. Classes A and B showed 100% accuracy with 0.0 MMEs. Class C (1-30 MMEs) had an accuracy of 99.3% with an average MME of 17.3. Class D (31-79 MMEs) reported 96.6% accuracy with an average MME of 42.81. Class E (≥80 MMEs) showed 94.4% accuracy and an average MME of 140.83.

Conclusion: The IPA-D scale enables reliable patient self-reporting of opioid use across most MME categories. It offers a practical, accurate tool for real-time opioid monitoring in clinical settings and may serve as a valuable complement to prescription databases like MAPS.