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

Area of Science:

• Pharmacovigilance
• Health Informatics
• Drug Safety

Background:

• Gabapentin misuse and abuse potential necessitates effective detection methods in claims data.
• Existing algorithms for identifying gabapentin misuse/abuse in administrative claims are limited.
• This study addresses the need for a robust algorithm to detect gabapentin misuse and/or abuse.

Purpose of the Study:

• To develop and validate an algorithm for identifying gabapentin misuse and/or abuse in administrative claims data.
• To characterize patients exhibiting potential gabapentin misuse and/or abuse.
• To identify factors associated with gabapentin misuse and/or abuse.

Main Methods:

• An algorithm was developed with input from 21 clinical experts over a 12-month period.
• The algorithm was applied to 334,128 patients with gabapentin prescriptions in the IBM® MarketScan® Research Databases (Dec 2017-Dec 2018).
• Logistic regression was used to assess factors associated with potential gabapentin misuse and/or abuse.

Main Results:

• The algorithm identified potential gabapentin misuse and/or abuse in 17.6% of patients.
• Associated factors included male sex (aOR: 1.08), drug and alcohol dependence (aOR: 1.31), bipolar disorder (aOR: 1.34), and concurrent use of opioids (aOR: 1.23), muscle relaxants (aOR: 1.24), or SNRIs (aOR: 1.33).
• These findings indicate significant prevalence and identify key risk factors for gabapentin misuse.

Conclusions:

• Approximately one in six patients using gabapentin showed potential misuse/abuse in a large commercial claims database.
• Comorbidities and concurrent drug use are significantly associated with gabapentin misuse and/or abuse.
• Enhanced monitoring and individualized safety protocols are recommended for high-risk patients.