The dissertation is intended to guide the selection and implementation of health department-led interventions with a long-term goal of reducing opioid overdose deaths. This dissertation is comprised of three aims. First, a narrative review describes models of buprenorphine treatment, summarizes retention in buprenorphine treatment, and includes descriptions of how each study defined and measured retention in treatment to aid cross-study comparisons. Trends in buprenorphine retention, as well as heterogeneity in trends, are described, and sub-analyses examine the role clinician experience in inducting patients on buprenorphine treatment may play in promoting retention. Lastly, the effect of a specific intervention—academic detailing—aimed at reducing the prescribing of opioid analgesics is measured using methods aimed at isolating the impact of a policy intervention that occurred at the same time as the detailing campaign.
Overall, this dissertation finds a lack of consistency in how retention in buprenorphine treatment is measured, which precludes easy identification of the most effective models and interventions for retention in buprenorphine treatment. Additionally, significant variation in buprenorphine treatment retention and trends in buprenorphine treatment was observed, suggesting opportunities for improvement. From 2015 to 2019, retention in buprenorphine increased among New York City residents; however, in 2019, the predicted prevalence of retention for three months was 52.7% and 34.6% for six months, below rates observed in other studies. Lastly, this dissertation should prompt public health officials to reconsider using academic detailing campaigns to decrease opioid analgesic prescribing, given that decreases in prescribing practices were only observed following one detailing campaign, which coincided with a policy change, and did not occur following another campaign, which took place two years after the policy change.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/1w8c-jg95 |
| Date | January 2023 |
| Creators | Nolan, Michelle L. |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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