Quantification of oxycodone and morphine analytes in urine: Assessment of adherence

Michael E. M. Larson, PhD; Richard L. Berg, MS; Joyce Flanagan, PhD

doi:10.5055/jom.2015.0302

Authors

Michael E. M. Larson, PhD
Richard L. Berg, MS
Joyce Flanagan, PhD

DOI:

https://doi.org/10.5055/jom.2015.0302

Keywords:

chronic pain, creatinine, drug abuse, oxycodone, OxyContin, morphine, Kadian, urine specimen, urine drug testing

Abstract

Objective: To use urine drug testing (UDT) results and other covariates to develop a model for the assessment of opioid medication prescription adherence.

Design: Retrospective study.

Setting: The Pain Management Clinic at one center of a large, private, multispecialty healthcare system (consisting of 52 regional centers) in northcentral and western Wisconsin.

Participants: Seven hundred thirty-three Pain Management Clinic patients with an opioid prescription and UDT between June 1, 2007 and May 17, 2010. UDT results were available for 2,615 individual drug screens from 2,364 urine samples.

Intervention: Patient characteristics, drug dosage, quantitative urine creatinine and drug/analyte levels, and reported adherence/nonadherence were abstracted from the electronic medical record.

Main outcome measures: Adherence was categorized for all UDT results using an objective set of criteria. Drug adherence was modeled excluding samples for clinically observed adherence issues, detection of illicit substances, diagnosed addictive disorders, and/or metabolic reasons.

Results: Considerable variability was observed for primary urine analytes, even among those prescribed the same dose and believed to be adherent and free of confounding medical issues. For all medications evaluated, only urine creatinine contributed significantly (p < 0.0001) to predictive models of adherence based on dose alone. Simulated underuse and review of identified overuse and underuse suggest that this model could provide useful adherence information.

Conclusion: Predictive models based on urine analyte levels and clinical covariates, particularly urine creatinine, may be clinically useful for assessing opioid adherence. Future work should evaluate whether genetics or other factors can improve predictive accuracy of these models.

Author Biographies

Michael E. M. Larson, PhD

Clinical Psychologist, Department of Pain Management, Marshfield Clinic Health System - Minocqua Center, Minocqua, Wisconsin

Richard L. Berg, MS

Senior Biostatistician, Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin.

Joyce Flanagan, PhD

Clinical Chemist, Section Head, Chemistry and Toxicology, Marshfield Labs, Marshfield Clinic Health Systems Marshfield, Wisconsin

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