An algorithm to identify gabapentin misuse and/or abuse in administrative claims data

Abstract

Background: Despite gabapentin's misuse and abuse potential and associated adverse events, few algorithms are available to detect gabapentin misuse and/or abuse in claims data. This study aims to develop an algorithm to identify gabapentin misuse and/or abuse in administrative claims data.

Methods: We developed an algorithm to identify gabapentin misuse and/or abuse over a 12-month period based on input from 21 clinical experts. We implemented the algorithm among 334,128 patients with at least one dispensed prescription of gabapentin between December 1, 2017 and December 1, 2018 in the IBM® MarketScan® Research Databases. We described the characteristics of patients who potentially misused and/or abused gabapentin and assessed factors associated with misuse and/or abuse using logistic regression.

Results: The algorithm identified 17.6% of patients with gabapentin use who potentially misused and/or abused gabapentin. Factors associated with potential gabapentin misuse and/or abuse included men (adjusted odds ratio (aOR): 1.08; 95% confidence interval (CI): 1.06-1.10), comorbid conditions (e.g., drug and alcohol dependence (aOR: 1.31; 95% CI: 1.24-1.39); bipolar disorder (aOR: 1.34; 95% CI: 1.27-1.41)), and medication use (e.g., opioids (aOR: 1.23; 95% CI: 1.20-1.26), muscle relaxants (aOR: 1.24; 95% CI: 1.21-1.27), or serotonin-norepinephrine reuptake inhibitors (aOR: 1.33; 95% CI: 1.29-1.36)).

Conclusions: Approximately one in six patients with gabapentin use potentially misused and/or abused gabapentin in a large commercial claims database. Multiple comorbidities and drug use were associated with gabapentin misuse and/or abuse. Monitoring requirements and individualized safety measures should be put in place for patients at elevated risks of gabapentin misuse and/or abuse.

Keywords: Abuse; Administrative claims data; Algorithm; Gabapentin; Misuse.