Login / Signup

Opioid use and COVID-19: a secondary analysis of the impact of relaxation of methadone take-home dosing guidelines on use of illicit opioids.

Victoria PanwalaEmily ThornSolmaz AmiriM Eugenia SociasRobert LutzOfer Amram
Published in: The American journal of drug and alcohol abuse (2023)
Background: An exemption to existing U.S. regulation of methadone maintenance therapy after the onset of the COVID-19 pandemic permitted increased take-home doses beginning March 2020. Objectives: We assessed the impact of this exemption on opioid use. Methods: A pre/post study of 187 clients recruited from an OTP who completed a survey and consented to share their urine drug testing (UDT) data. Use of fentanyl, morphine, hydromorphone, codeine, and heroin was assessed via UDT. Receipt of take-home methadone doses was assessed from clinic records for 142 working days pre- and post-COVID exemption. Analysis was conducted using a linear regression model to assess the association between increased take-home doses and use of illicit opioids. Results: In the pre- vs. post-COVID-19 SAMHSA exemption periods, 26.2% vs. 36.3% of UDTs were positive for 6-acetylmorphine respectively, 32.6% vs. 40.6% positive for codeine, 34.2% vs 44.2% positive for hydromorphone, 39.5% vs. 48.1% positive for morphine, 8.0% vs. 14.4% positive for fentanyl ( p -value < .001). However, in the unadjusted descriptive data, when grouped by change in substance use, those clients who experienced a decrease in the use of morphine, codeine, and heroin post-COVID-19 were given significantly more take-home doses than the groups that had no change or an increase in the use of these substances. In the adjusted model, there was no significant relationship between change in opioid use and increased receipt of take-home methadone doses. Conclusions: Although take-home doses post-COVID-19 nearly doubled, this increase was not associated with a significant change in use of illicit opioids.
Keyphrases
  • coronavirus disease
  • sars cov
  • healthcare
  • chronic pain
  • primary care
  • pain management
  • emergency department
  • electronic health record
  • cross sectional
  • machine learning
  • hepatitis c virus
  • single molecule
  • data analysis