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. Author manuscript; available in PMC: 2023 Nov 1.
Published in final edited form as: Int J Drug Policy. 2022 Sep 16;109:103852. doi: 10.1016/j.drugpo.2022.103852

SHIFTS IN SUBSTANCE USE PATTERNS AMONG A COHORT OF PEOPLE WHO USE OPIOIDS AFTER DELISTING OF OXYCONTIN IN BC, CANADA: AN INTERRUPTED TIME SERIES STUDY

Mohammad Karamouzian a,b,e, Jane A Buxton b, Celestin Hategeka c,f, Ekaterina Nosova a, Kanna Hayashi a, M-J Milloy a,d, Thomas Kerr a,d
PMCID: PMC9885984  NIHMSID: NIHMS1868305  PMID: 36122483

Abstract

Background

OxyContin was delisted from Canadian provincial drug formularies in March 2012 and replaced with a reformulated tamper-resistant form of oxycodone (i.e., OxyNeo). We assessed if delisting of OxyContin was associated with changes in the use of unregulated opioids and other substances among people who use opioids (PWUO).

Methods

Data were derived from two prospective cohort studies of people who use drugs in Vancouver, BC, Canada from 2006 to 2018. PWUO who had at least one follow-up visit before and after delisting of OxyContin were included. Outcomes of interest were self-reported regular (i.e., at least weekly) use of heroin, non-prescribed prescription opioids, cannabis, methamphetamine, crack cocaine, and powder cocaine during the previous six months. Using quasi-experimental interrupted time series, we fit generalized least squares models to assess participants’ immediate and long-term substance use practices after the policy change.

Results

We analyzed data from 1014 participants who contributed to 17457 visits during the study. Following the delisting of OxyContin, heroin use increased immediately by 5.17% (95% confidence intervals [CI]: 0.68 to 9.67) and over time by 0.47% (0.35 to 0.58) per month. Non-prescribed prescription opioid use increased immediately by 1.80% (0.10 to 3.50) and over time by 0.16% (0.12 to 0.19) per month. Cannabis use increased immediately by 4.37% (0.88 to 7.87) and over time by 0.11% (0.02 to 0.19) per month. Methamphetamine use did not increase immediately but increased over time by 0.10% (0.01 to 0.18) per month. Crack cocaine use decreased immediately by 6.13% (−10.94 to −1.69) but not significantly over time. Lastly, powder cocaine use did not increase immediately or over time.

Conclusions

Delisting of OxyContin in BC was not associated with a reduction in unregulated opioid use among PWUO. Our findings point to a shift in substance use patterns of PWUO post-intervention and further highlight the unintended consequences of supply-reduction interventions in addressing the opioid epidemic.

Keywords: Canada, Interrupted time series, Opioid-related disorders, OxyContin, Prescription opioids, Substance use

INTRODUCTION

The introduction of long-acting oxycodone (OxyContin, Purdue Pharma) into Canadian provincial drug formularies in 2000 has been associated with a rapid increase in opioid toxicity deaths and hospitalizations (Dhalla et al., 2009 ; Fischer, Vojtila, & Kurdyak, 2017 ; Gomes et al., 2017). OxyContin was marketed as a safe, potent alternative to previously available weaker opioids (e.g., codeine and meperidine) that could serve as a long-acting opioid. However, its controlled-release characteristic was easily overcome when people learned to crush the pills and swallow, snort, or inject them to experience a morphine-like high (Fischer et al., 2017). In the Canadian province of Ontario, although the prescription rates of other opioids had remained relatively constant from 2003 to 2008, prescription of OxyContin increased by over 100% and contributed to increased opioid toxicity deaths (Gomes et al., 2011). Ten years after the introduction of OxyContin into Canadian drug formularies, prescription opioid use quadrupled despite the number of patients living with chronic pain remaining relatively constant (Gomes et al., 2017).

In February 2012, Purdue Pharma which had led an aggressive marketing campaign to promote the use of OxyContin for addressing non-cancer pain (Van Zee, 2009), replaced it with OxyNEO, a tamper-resistant formulation which was neither crushable nor water-soluble (Gomes et al., 2017). Shortly after, in March 2012, seven Canadian provinces announced that OxyContin would be delisted from their drug formularies to address the high numbers of opioid toxicity (Fischer & Keates, 2012 ; Gomes et al., 2017). This supply-level intervention meant that with a few exceptions (e.g., for people on social assistance), OxyContin would no longer be covered by the provincial drug benefits programs.

Between February 2012 and April 2016, the quantity of opioids (milligrams of morphine equivalents) dispensed across Canada dropped by 14.9%, with Ontario (22.8% drop) and British Columbia (BC; 30% drop) having the largest declines. Moreover, after the introduction of OxyNEO, the national oxycodone dispensing rate dropped by 46.4%, from 26.4 tablets/100 people to 14.6 tablets/100 people during the same period (Gomes et al., 2017). However, studies examining the broader impact of OxyContin delisting and introduction of OxyNEO report discrepant findings. For example, some studies in both the U.S. and Australia have found that the reformulation of OxyContin resulted in reduced non-medical use of OxyContin (Havens, Leukefeld, DeVeaugh-Geiss, Coplan, & Chilcoat, 2014 ; Degenhardt et al., 2015), decreased street prices for OxyContin and reduced Oxycontin-related poisonings (Severtson et al., 2013), and decreased sales of 80 mg oxycodone and reduced injection use of reformulated OxyContin among people who inject drugs (Degenhardt et al., 2015), whilst others have found that it resulted in increased opioid-related harms and mortality (Butler et al., 2013 ; Cassidy, DasMahapatra, Black, Wieman, & Butler, 2014 ; Evans, Lieber, & Power, 2019). More recently, an analysis of aggregate state-level data in the U.S. suggested that reformulation of OxyContin has not only led to increased heroin-related deaths, but also contributed to increased incidence of blood-borne infections (e.g., hepatitis B and C) due to heroin’s higher likelihood of being injected than OxyContin (Beheshti, 2019).

While estimates on aggregate-level dispensing patterns of OxyContin help shed light on how opioid prescription patterns changed in North America after the delisting of OxyContin, the understanding of potential modifications in substance use patterns of people who use opioids (PWUO) after the policy was implemented remains limited. This is particularly important given the considerable body of international evidence indicating that supply-level reduction of opioids and inducing shocks to the unregulated drug market often lead to shifts in substance use patterns (Degenhardt et al., 2005 ; Evans et al., 2019 ; Harris, Forseth, & Rhodes, 2015 ; Mital, Miles, McLellan-Lemal, Muthui, & Needle, 2016). In this study, we drew on data from two long-running cohorts of adult people who use drugs recruited from community settings in Vancouver, Canada, to assess if delisting of OxyContin and the introduction of tamper-resistant OxyContin in BC in March 2012 was associated with changes in the use of unregulated opioids and other substances.

METHODS

Data for this analysis was derived from two open prospective community-recruited cohort studies of adult people who use drugs in Vancouver, BC, Canada. These cohorts are the Vancouver Injection Drug Users Study (VIDUS) and the AIDS Care Cohort to evaluate Exposure to Survival Services (ACCESS), the details of which are previously described (Strathdee et al., 1998 ; Wood et al., 2009). In brief, VIDUS includes HIV-seronegative people who inject drugs, and ACCESS includes people who use drugs and are living with HIV. VIDUS participants that become HIV-seropositive during the study are transferred to ACCESS. Cohort recruitment occurs through community-based approaches, including postering, outreach to settings frequented by people who use drugs (e.g., the open drug market, low-barrier harm reduction facilities) and word-of-mouth. Eligibility criteria for enrolment in the cohorts include: having used drugs (other than, or in addition to, cannabis) in the previous month, being a resident of Vancouver, and providing written informed consent. All cohort participants complete a questionnaire at baseline and semi-annually (i.e., twice a year). The interviewer-administered questionnaires collect a wide range of data, including but not limited to participants’ socio-demographic characteristics, substance use practices, sexual behaviours, history of encounters with police, history of homelessness, and harm reduction or healthcare services utilization. Study instruments are harmonized between the VIDUS and ACCESS cohorts and use the same measures except for items specific to HIV risk or HIV disease. Participants receive a $40 honorarium at each study visit, and both cohorts have received approval from the University of British Columbia and Providence Health Care Research Ethics Boards.

Data were included from participants from the first study visit where they met the criteria for regular opioid use (i.e., using unregulated opioids on an at least weekly basis or having received opioid agonist therapy [OAT] in the previous six months). Participants were asked: “In the last 6 months, when you were using, which of the following opioids (i.e., heroin, fentanyl, and any prescription opioids that were used non-medically) did you use?” and were provided with a list of opioids. This approach has been previously used in substance use research (Karamouzian, Pilarinos, Hayashi, Buxton, & Kerr, 2022 ; Socías et al., 2020). To ensure that all participants were exposed to the intervention of interest, the analytic sample was further restricted to participants who had at least one follow-up visit before (January 1, 2006 to February 30, 2012) and after (April 1, 2012 to November 30, 2018) the policy change. Overall, data were included from 154 months; 74 before and 80 after the implementation of the policy change in March 2012.

We assessed six self-reported dichotomous outcomes measuring regular (i.e., at least weekly) use of different substances during the previous six months, including heroin, non-prescribed prescription opioids (i.e., prescription opioids not prescribed for the participant or used for the experience or feeling they caused, such as oxycodone, hydrocodone, morphine, paracetamol, tramadol, fentanyl), cannabis, methamphetamine, crack cocaine, and powder cocaine.

We conducted separate quasi-experimental interrupted time series (ITS) on all outcomes. ITS is a robust quasi-experimental design that utilizes data obtained at several intervals to examine potential causal associations between a particular intervention and specific outcomes (Hategeka, Ruton, Karamouzian, Lynd, & Law, 2020). The outcomes were summarized as monthly proportions based on the date of the interview. We used these aggregated figures to fit generalized least squares (GLS) models that included terms for the baseline level of each outcome at the beginning of the study period in 2006 (i.e., intercept), existing trend before delisting of OxyContin (coded as 1 … 155), immediate level change post-implementation in each outcome (coded as 0 before versus 1 after) and trend change (coded as 0 before and 1 … 81 after) post-implementation of the policy. This allowed an assessment of participants’ immediate and long-term substance use practices after the policy change while controlling for baseline levels and trends.

As monthly observations might have been correlated over time, we also tested for autocorrelation using the Durbin-Watson test and autocorrelation function [ACF] and partial-ACF plots. We controlled for autocorrelation by including a first-order autocorrelation term in the GLS models (Bernal, Cummins, & Gasparrini, 2017 ; Hategeka et al., 2020). The best-fitting ITS model for each outcome was selected based on the Akaike’s information criterion. Seasonality was assessed for all outcomes but was not detected. We considered a one-month phase-in period (i.e., March 2012) to allow enough time for the policy change to be incorporated into prescription practices and excluded this period from the analysis. Given that we measured regular substance use in the previous six months, we also considered a phase-in period of six months as a sensitivity analysis. All analyses were conducted in R software (version 4.1.1). P -values were two-sided and considered significant at a level <0.05.

RESULTS

Out of 1910 participants that contributed to 21391 observations during the study period (2006 to 2018), 1015 unique participants had data before and after delisting of OxyContin. After removing 85 observations with missing values to primary outcomes, 1014 participants contributed to 17457 visits in the final analytical sample. The median (IQR) number of responses contributing to each time point (month) was consistent across time (56; Q1: 50, Q3: 62). Characteristics of the participants at the first observation during the study period are presented in Table 1. At baseline, most participants were from VIDUS (642; 63.3%) and self-identified as men (642; 63.9%). The median (Q1, Q3) age of the participants was 41.9 (35.6, 47.5), and they predominantly self-identified as White (461; 45.7%) or Indigenous (325; 32.2%).

Table 1.

Socio-demographic characteristics of 1014 people who use opioids in Vancouver, Canada (January 2006-November 2018).

Characteristics First observation in the study period;
n (%)
Cohort
VIDUS 642 (63.3)
ACCESS 372 (36.7)
Age (Median, IQR) 41.9 (35.6, 47.5)
Self-reported gender
Man 642 (63.9%)
Woman 352 (35.1%)
Transgender 11 (11%)
Ethnicity
White 461 (45.7)
Indigenous 325 (32.2)
Asian or Black 29 (2.8)
Other 194 (19.3)
Homelessness (Last 6 Months) 346 (34.1)
Incarceration (Last 6 Months) 186 (18.5)
Residence in Downtown Eastside (Last 6 Months) 744 (73.4)
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Notes: IQR: Interquartile range.

ITS model summaries for each outcome are presented in Table 2. Fig. 1 -a presents the monthly proportion of regular heroin use among participants. At the beginning of the study period, the prevalence of regular heroin use was 49.83% (95% confidence intervals [CI]: 46.23 to 53.43%). The trend of regular heroin use was already declining before delisting of OxyContin (−0.36% per month; 95% CI: −0.45 to −0.28%). Following the policy change, the prevalence of regular heroin use increased immediately by 5.17% (95% CI: 0.68 to 9.67%) and over time by 0.47% per month (95% CI: 0.35 to 0.58%).

Table 2.

Interrupted time series model coefficients representing substance use among people who use opioids before and after delisting of OxyContin in Vancouver, BC, Canada.

Substance Intercept (95% CI) Baseline trend pre- intervention (95% CI) P - value Immediate level change post- intervention (95% CI) P - value Trend change post- intervention (95% CI) P - value
Heroin 49.83 (46.23, 53.43) −0.36 (−0.45, −0.28) <0.001 5.17 (0.68, 9.67) 0.025 0.47 (0.35, 0.58) <0.001
Non-prescribed PO 22.32 (21.11, 23.52) −0.17 (−0.20, −0.15) <0.001 1.80 (0.10, 3.50) 0.040 0.16 (0.12, 0.19) <0.001
Cannabis 37.15 (34.41, 39.89) −0.11 (−0.17, −0.04) <0.001 4.37 (0.88, 7.87) 0.015 0.11 (0.02, 0.19) 0.0135
Methamphetamine 5.91 (3.16, 8.65) 0.02 (−0.02, 0.08) 0.336 2.28 (−0.54, 5.11) 0.115 0.10 (0.01, 0.18) 0.028
Crack cocaine 73.40 (68.97, 77.82) −0.35 (−0.44, −0.25) <0.001 −6.31 (−10.94, −1.69) 0.008 0.04 (−0.10, 0.18) 0.560
Powder cocaine 25.29 (23.08, 27.50) −0.12 (−0.17, −0.07) <0.001 1.78 (−1.11, 4.69) 0.230 0.01 (−0.05, 0.08) 0.629
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Notes: Substance use measures are self-reported and include regular (i.e., at least weekly) use during the previous six months; PO: Prescription opioids.

Figure 1. People who use opioids’ substance use level and trend change before and after delisting OxyContin in Vancouver, BC, Canada.

Figure 1.

Figure 1.

Figure 1.

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Notes: The vertical dashed line denotes policy change in March 2012, and the rectangular grey box represents the phase-in period. Observed monthly percentages are presented with red dots before delisting OxyContin, a grey dot during the phase-in period, and blue dots after the delisting OxyContin. The full line represents the estimated regression line, and the dashed red line represents the counterfactual scenario (i.e., ITS model predictions had OxyContin not been delisted).

Fig. 1 -b presents the participants’ monthly proportion of regular non-prescribed prescription opioid use. At the beginning of the study period, the prevalence of regular non-prescribed prescription opioid use was 22.32% (95% CI: 21.11 to 23.52%). The trend of regular non-prescribed prescription opioid use was already declining before delisting of OxyContin (−0.17% per month; 95% CI: −0.20 to −0.15%). Following the policy change, the prevalence of regular non-prescribed prescription opioid use increased immediately by 1.80% (95% CI: 0.10 to 3.50%) and over time by 0.16% per month (95% CI: 0.12 to 0.19%).

Fig. 1 -c presents the participants’ monthly proportion of regular cannabis use. At the beginning of the study period, the prevalence of regular cannabis use was 37.15% (95% CI: 34.41 to 39.89%). The trend of regular cannabis use was already declining before delisting of OxyContin (−0.11% per month; 95% CI: −0.17 to −0.04%). Following the policy change, the prevalence of regular cannabis use increased immediately (4.37%; 95% CI: 0.88 to 7.87%) and over time (0.11% per month; 95% CI: 0.02 to 0.19%).

Fig. 1 -d presents the participants’ monthly proportion of regular methamphetamine use among the participants. At the beginning of the study period, the prevalence of regular methamphetamine use was 5.91%. The trend of regular methamphetamine use was relatively stable before delisting of OxyContin (0.02% per month; 95% CI: −0.02 to 0.08%). Following the policy change, the prevalence of regular methamphetamine use did not increase immediately (2.28%; 95% CI: −0.54 to 5.11%); however, it increased over time by (0.10% per month; 95% CI: 0.01 to 0.18%).

Fig. 1 -e presents the participants’ monthly proportion of regular crack cocaine use. At the beginning of the study period, the prevalence of regular crack cocaine use was 73.40% (95% CI: 68.97 to 77.82%). The trend of regular crack cocaine use was already declining before delisting of OxyContin (−0.35% per month; 95% CI: −0.44% to −0.25%). Following the policy change, the prevalence of crack cocaine use immediately decreased by 6.31% (95% CI: −10.94 to −1.69%) but not over time (0.04% per month; 95% CI: −0.10 to 0.18%).

Fig. 1 -f presents the participants’ monthly proportion of regular powder cocaine use. At the beginning of the study period, the prevalence of regular powder cocaine use was 25.29% (95% CI: 23.08 to 27.50%). The trend of regular powder cocaine use was already declining before delisting of OxyContin (−0.12% per month; 95% CI: −0.17 to −0.07%). Following the policy change, the prevalence of powder cocaine use did not increase immediately (1.78%; 95% CI: −1.11 to 4.69%) or over time (0.01% per month; 95% CI: −0.05% to 0.08%).

The ITS findings for all examined outcomes were comparable in the sensitivity analyses considering a six-month phase-in period (See Fig. S1).

DISCUSSION

We assessed how substance use patterns among participants in two harmonized cohorts of PWUO in Vancouver shifted after delisting of OxyContin. The findings suggest that although this supply reduction intervention may have influenced the provincial-level prescription or consumption of OxyContin (Fischer et al., 2017 ; Gomes et al., 2017), it was not associated with a decline in unregulated opioid use among the participants of our cohorts who were using opioids regularly. The ITS models estimated that delisting of OxyContin was significantly associated with increased prevalence and trend of regular heroin, non-prescribed prescription opioids, and cannabis use. In addition, although the policy change was not associated with significant increases in crack cocaine or powder cocaine use over time, it was significantly associated with an upward trend in the regular use of methamphetamine among the participants.

Our findings suggest that following delisting of OxyContin, some PWUO may have resorted to use of other unregulated drugs, including heroin and other similar or more potent non-prescribed prescription opioids. Several studies have shown that PWUO’s substance use patterns were altered after delisting of OxyContin. For example, in a qualitative study conducted from March to December 2012 in Ontario, Canada, a group of marginalized people who were regularly using prescription opioids reported shifting to other unregulated opioid or non-opioid drugs or supplementing their opioids with other drugs post-implementation of the policy (Fischer et al., 2017). In the U.S., a quasi-experimental assessment of 2566 PWUO initiating OAT showed that oxycodone which was reported as the primary drug of choice among 36% of the participants before the policy change, declined to 13% following the reformulation of OxyContin. Conversely, PWUO’s preference shifted toward hydromorphone (32%) and fentanyl (20%), and their use of heroin increased by 100% after the policy change (Cicero & Ellis, 2015). Similarly, at the supervised injection facility in Sydney, Australia, client visits for injection of OxyContin declined drastically post-policy change in April 2014; however, this positive impact was partly offset by increasing visits for injecting heroin, morphine, and fentanyl (Jauncey, Livingston, Salmon, & Dietze, 2018).

Although our findings illustrate how PWUO’s individual substance use patterns in BC have shifted after the delisting of OxyContin, they provide limited insight on the population-level impact of this policy intervention which seem to vary across different settings. For example, a recent ITS analysis of state-wide mortality data in the U.S. suggests that the reformulation of OxyContin has been the primary factor that ignited U.S.’s heroin epidemic. Evans et al. looked at data from 2004 to 2014 and concluded that the combined rate of prescription opioids- and heroin-related mortality was not reduced after the reformulation of OxyContin and concluded that the reduction in deaths caused by reductions in prescription opioids-related mortality were offset by increases in heroin-related deaths (Evans et al., 2019). Conversely, a population-level analysis based on cohort data from the National Opioid Medications Abuse Deterrence in Australia suggests that the introduction of tamper-resistant formulation of controlled-release oxycodone was not significantly associated an increase or decrease in population-level indicators of opioid use, opioid-related overdose or OAT uptake (Larance et al., 2018). Larance et al. also meta-analyzed data from sentinel populations and observed no pooled effect on switching to heroin (Larance et al., 2018). These differences could be partly explained by the contextual differences between Australia and North America, where several responses were initiated over a short period of time (e.g., the development of opioid prescription guidelines and prescription monitoring programs). Moreover, most people in the Australian study were injecting oxycodone which could limit the study findings’ generalizability to North American settings where non-injection use of OxyContin is common (Cassidy et al., 2014 ; Larance et al., 2018).

While regular use of crack cocaine and powder cocaine among the participants was not significantly impacted and continued a downward trend, there was a considerable shift towards increased regular cannabis and methamphetamine use among the participants. Several studies have reported that people who use drugs may use cannabis as a harm reduction strategy to substitute for other substances (Mok et al., 2022), to help manage chronic pain (Lake et al., 2019), and reduce opioid-related craving and withdrawal symptoms (Scavone, Sterling, & Van Bockstaele, 2013). Therefore, a shift to increased regular cannabis use following the delisting of OxyContin is plausible. On the other hand, while the upward shift in methamphetamine use may be partly associated with the so-called oxycodone drought (Fischer & Keates, 2012) in Canada, it is unlikely that this supply-reduction intervention has been solely responsible for the upward trend of methamphetamine use among PWUO, which began in the early 2010s. For example, a recent assessment of methamphetamine use among 1984 people who use drugs in Vancouver estimated the self-reported use of methamphetamine in the previous six months among the participants to have increased from 19% in 2006 to 36% in 2017; an increase that was significantly associated with several individual-level substance use and sexual behaviours (Bach et al., 2020). In the U.S., self-reported monthly use of methamphetamines increased from 18.8% in 2011 to 34.2% in 2017 among participants in public and private OAT centres. Regardless of how much of the increase in regular methamphetamine use among PWUO is attributed to the delisting of OxyContin, the observed increasing trend of methamphetamine use among our participants highlights the urgent need to develop policies and interventions to address the emergence of “twin epidemics” among PWUO (Karamouzian et al., 2022 ; Strickland, Havens, & Stoops, 2019).

We acknowledge the limitations of the study. First, we could not limit the participants to people who were primarily using OxyContin before and after the policy change. Data on OxyContin use alone was unavailable before or after the policy change and limiting the sample to this subgroup was not feasible. Therefore, we studied participants’ use of non-prescribed prescription opioids (including OxyContin) before and after the policy change. Second, using ITS to assess the impact of the regulatory changes regarding OxyContin and leveraging data from two cohorts of PWUO in Vancouver allowed for reducing selection-attrition biases as well as controlling for the pre-existing levels and trends of regular substance use patterns among the study participants. However, we could not include data from an external control group, and unmeasured residual confounding cannot be ruled out. Third, the non-random nature of participant recruitment in the cohorts may limit the generalizability of the findings to all PWUO in Vancouver. Fourth, the primary outcomes of interests were based on self-reports and are subject to potential reporting biases. However, previous studies have shown people who use drugs’ self-reports of substance use to be sufficiently trustworthy (Darke, 1998). Moreover, if there is any potential self-reported bias, it would be consistent across the study and, therefore, not significantly impact the findings of the ITS analysis. Fifth, we did not have data on prescribed opioid use in this analysis; therefore, people who ceased prescribed OxyContin use due to the regulatory changes but did not shift to any other substances may have been excluded from the analytical sample. Lastly, given that cohort data is collected semi-annually, the interview dates were used to create the date variable.

CONCLUSIONS

In conclusion, this ITS analysis suggests that the delisting of OxyContin in BC does not appear to have played an important role in reducing unregulated opioid use among PWUO. Indeed, the reductions in OxyContin dispensing may have been potentially offset by increases in the use of heroin or non-prescribed opioids. Our findings also indicated a shift in substance use patterns of PWUO following the policy change. While supply-reduction efforts remain a part of the comprehensive response to the opioid epidemic in Canada and the U.S, and may indeed lead to short-term drops in the use or prescription of certain opioids, they are not a ‘silver bullet’, may result in unintended harms, and may fail to produce meaningful positive, long-term, population-level outcomes.

Supplementary Material

Supplementary Figures

HIGHLIGHTS.

  • Delisting of OxyContin in BC was not associated with a reduction in unregulated opioid use among people who use opioids.

  • Following the delisting of OxyContin in BC, some people who use opioids shifted their substance use patterns.

  • Reductions in OxyContin dispensing after delisting of OxyContin were potentially offset by increases in use of heroin or non-prescribed opioids.

Funding sources

This study was funded by the US National Institute on Drug Abuse (NIDA) (U01-DA038886 and U01-DA021525) and a Canadian Institutes of Health Research (CIHR) Foundation Grant (20R74326).

Declarations of Interest

M.K. and C.H. are supported by the Banting Postdoctoral Fellowship. M.K. was supported by Vanier Canada Graduate Scholarship and the Pierre Elliott Trudeau Foundation Doctoral Scholarship when the initial version was drafted. K.H. is supported by a Michael Smith Foundation for Health Research (MSFHR) Career Scholar Awards and CIHR New Investigator Award (MSH 141971). K.H. also holds the St. Paul’s Hospital Chair in Substance Use Research and is supported in part by the St. Paul’s Foundation and the NIDA (U01-DA038886). M.J.M. is supported by the US National Institutes of Health (U01-DA0251525). He is the Canopy Growth professor of cannabis science at the University of British Columbia, a position established through arms-length gifts to the university from Canopy Growth, a licensed producer of cannabis, and the Government of British Columbia’s Ministry of Mental Health and Addictions.

Footnotes

Ethics approval

The cohorts receive annual ethics approval from the University of British Columbia / Providence Health Care research ethics board (ACCESS: H05–50233, VIDUS: H05–50234 / H14–01396).

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