Dynamic changes in methadone utilisation for opioid use disorder treatment: a retrospective observational study during the COVID-19 pandemic.

OBJECTIVES: Opioid use disorder (OUD) is a major public health concern in the USA, resulting in high rates of overdose and other negative outcomes. Methadone, an OUD treatment, has been shown to be effective in reducing the risk of overdose and improving overall health and quality of life. This study analysed the distribution of methadone for the treatment of OUD across the USA over the past decade and through the COVID-19 pandemic. DESIGN: Retrospective observational study using secondary data analysis of the Drug Enforcement Administration and Medicaid Databases. SETTING: USA. PARTICIPANTS: Patients who were dispensed methadone at US opioid treatment programmes (OTPs). PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcomes were the overall pattern in methadone distribution and the number of OTPs in the USA per year. The secondary outcome was Medicaid prescriptions for methadone. RESULTS: Methadone distribution for OUD has expanded significantly over the past decade, with an average state increase of +96.96% from 2010 to 2020. There was a significant increase in overall distribution of methadone to OTP from 2010 to 2020 (+61.00%, p<0.001) and from 2015 to 2020 (+26.22%, p<0.001). However, the distribution to OTPs did not significantly change from 2019 to 2021 (-5.15%, p=0.491). There was considerable state-level variation in methadone prescribing to Medicaid patients with four states having no prescriptions. CONCLUSIONS: There have been dynamic changes in methadone distribution for OUD. Furthermore, pronounced variation in methadone distribution among states was observed, with some states having no OTPs or Medicaid coverage. New policies are urgently needed to increase access to methadone treatment, address the opioid epidemic in the USA and reduce overdose deaths.

Genetics and prescription opioid use (GaPO): study design for consenting a cohort from an existing biobank to identify clinical and genetic factors influencing prescription opioid use and abuse.

BACKGROUND: Prescription opioids (POs) are commonly used to treat moderate to severe chronic pain in the health system setting. Although they improve quality of life for many patients, more work is needed to identify both the clinical and genetic factors that put certain individuals at high risk for developing opioid use disorder (OUD) following use of POs for pain relief. With a greater understanding of important risk factors, physicians will be better able to identify patients at highest risk for developing OUD for whom non-opioid alternative therapies and treatments should be considered. METHODS: We are conducting a prospective observational study that aims to identify the clinical and genetic factors most stongly associated with OUD. The study design leverages an existing biobank that includes whole exome sequencing and array genotyping. The biobank is maintained within an integrated health system, allowing for the large-scale capture and integration of genetic and non-genetic data. Participants are enrolled into the health system biobank via informed consent and then into a second study that focuses on opioid medication use. Data capture includes validated self-report surveys measuring addiction severity, depression, anxiety, and nicotine use, as well as additional clinical, prescription, and brain imaging data extracted from electronic health records. DISCUSSION: We will harness this multimodal data capture to establish meaningful patient phenotypes in order to understand the genetic and non-genetic contributions to OUD.