Characterization of drug-drug interactions in patients whose substance intake was objectively identified by detection in urine

ABSTRACT

Background: Identification of drug-drug interactions (DDIs) typically relies on patient medication lists which are prone to inaccuracies. This study describes use of a mass spectrometry test to detect recently ingested substances in urine with subsequent identification of DDIs.

Research design and methods: This was a retrospective analysis of the prevalence of DDIs identified in patients with chronic pain, addiction and/or behavioral health conditions in the U.S. Relationships between patient demographics, polypharmacy and the occurrence of DDIs were also described.

Results: Of 15,004 patients, 2964 (20%) had a DDI identified. There was a positive association between the number of substances detected in urine and the number of interactions identified (r = 0.5033, p-value = 0.0001). Of patients with polypharmacy, 15.6% had contraindicated or severe interactions identified compared to only 3.2% of those without polypharmacy. For polypharmacy patients, the youngest population studied had a much higher likelihood of having one or more DDIs identified compared to the other age groups (p-value = 0.0002).

Conclusions: By utilizing a mass spectrometry test to objectively detect recently ingested substances followed by identification of DDIs, healthcare providers may be able to better characterize the true incidence of DDIs. Study findings may not be generalizable to healthcare populations outside of pain management, addiction treatment, and behavioral health.

KEYWORDS:

• Addiction medicine
• drug interactions
• mass spectrometry
• medication reconciliation
• pain management

Author contributions

Josh Schrecker, Cheryl Hild, and Brandi Puet were involved in the conception and design of the manuscript. All authors approve this final version of the manuscript and agree to be accountable for all aspects of the work. Cheryl Hild provided data analysis and interpretation of the data and was a significant contributor to the methods and results section. In addition, she reviewed and provided edits to the entirety of the manuscript. David Schwope drafted the description of the analytical methods and additionally reviewed and edited the final version of the manuscript. Josh Schrecker and Brandi Puet were involved in the drafting of all other contents (introduction, portions of results and methods, discussion, and conclusion) and overall finalization of the manuscript.

Declaration of interest

All authors are employees of Aegis Sciences Corporation. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This paper was funded by Aegis® Sciences Corporation.