Article Text
PDF
Abstract
Objective To determine if inappropriate tapering/discontinuation of opioids to Alberta patients occurred from mid-2013–2020, as unintended consequences of prescribing guidelines, regulations and policies in response to the North American opioid crisis.
Design A population-based, repeated cross-sectional time-series study.
Setting Alberta, Canada.
Participants Residents of Alberta, Canada aged 18 and older who received an opioid dispense from a community pharmacy from 2013 to 2020.
Main outcome measures The prevalence of potential rapid tapering was measured at a given date (reference day), enveloped by a data window. Dose changes were measured as oral morphine equivalents (OME) per patient, at multiple time points (‘data window’ around a reference day). Chronic recipients were identified, and their prescriptions were contrasted 90 days before and after the reference day to measure OME/day changes.
Results Approximately 9000 dispenses (totalling ~6 million OME) per day were analysed from 2013 to 2020. The total number of opioid recipients was highly cyclic in nature (peaking in winter). The number of chronic opioid recipients remained somewhat stable from ~70K in 2013 to ~86K at the end of 2020. The number of chronic high and very high dose recipients presented a significant decrease after 2017. Approximately 11%–12% of chronic high-dose recipients experienced potential rapid dose tapering at a rate of 50% or more prereference to postreference day at any given point of time. For chronic very high dose recipients, approximately 11.5% experience potential rapid dose tapering at a rate of 50% or more prereference to postreference day at any given point of time. Potential discontinuation remained constant and the interventions did not have a significant impact on the trend.
Conclusion The evidence suggests that changes in prescribing guidelines were not associated with an increase of rapid opioid tapering/discontinuation in Alberta.
- Primary Health Care
- Primary Care
- PUBLIC HEALTH
Data availability statement
Data may be obtained from a third party and are not publicly available.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
STRENGTHS AND LIMITATIONS OF THIS STUDY
The study provides important insights into opioid prescribing practices in Alberta and analysed approximately 9000 opioid dispensations (totalling ~6 million oral morphine equivalent (OME)) per day over an 8-year period.
The study used time series analysis methods to measure and quantify trends.
The study used community pharmacy dispenses received by the Tracked Prescription Programme from Alberta’s Electronic Health Record (Netcare) due to the unavailability of prescription data. Prescription details such as dosage regimen (frequency and duration) are not available in the dataset, so OME/day is estimated to the best of our ability.
Introduction
The North American opioid crisis is often traced back to overprescribing opioids as a potential contributing factor.1 2 In Alberta, from 2014 to 2016, there was a 23% increase in quarterly opioid dispensations from community pharmacies, with >1 million dispenses in the last quarter of 2016.3
Physicians are the largest prescriber group of opioids in Alberta, followed by pharmacists, dentists and nurse practitioners.4
Prescription opioids are used for treating pain and are essential to modern medical practice when prescribed and used appropriately. However, opioids can have substantial adverse effects and carry the potential to cause significant harm, including addiction, poisoning and death.1 In Alberta, from 2014 to 2016, there were over 19 000 opioids and other substance use-related emergency/urgent care visits, averaging 1812 visits per quarter.3
Various initiatives to reduce the harms associated with prescription opioids have been introduced in response to the crisis. Some of these, such as the 2016 US Centers for Disease Control and Prevention (CDC)5 and 2017 Canadian Guidelines for opioid therapy and chronic non-cancer pain,6 have been endorsed by Canadian medical regulators. The College of Physicians and Surgeons of Alberta (CPSA), the medical regulator in Alberta, released a new Standard of Practice (SOP) for prescribing drugs with a potential to cause substance-related harm, including opioids, which defines overarching expectations for ensuring patient safety but does not set any stringent limits on prescription parameters such as prescribed dose.7
As the administrator of the Tracked Prescription Programme (TPP Alberta), CPSA collects data on medications that carry a risk of harm or non-medical use, including opioids, benzodiazepine/z-drugs, and most recently, antibiotics.8 In 2016 CPSA issued the first MD Snapshot-Prescribing report (Snapshot), an interactive quarterly and individualised tool regarding physician prescribing practices. The Snapshot is a resource for self‐reflection and prescribing awareness, it is not meant as a judgement or directive to stop prescribing monitored drugs.8
Multiple studies aiming to understand the effects of new guidelines and policy changes regarding opioid prescribing have been conducted and published in recent years, both qualitative9 10 and quantitative.11–15 In fact, recent research has highlighted the potential negative consequences of medical regulatory interventions.15 16 Since CPSA has received anecdotal reports that cases of abrupt and inappropriate tapering of opioids increased following the release of the Snapshot and other initiatives/guidelines, we investigate 2013–2020 prescribing data to determine if this has, in fact, been an unintended consequence of these policy changes in Alberta.
Methods
Study design and participants
We conducted a population-based, repeated cross-sectional time-series study that examined chronic opioid prescription recipients from community pharmacies in Alberta, Canada. Participants included Albertans aged 18 and older who received an opioid dispense from a community pharmacy from 2013 to 2020. Unique provincial health ID numbers were used to identify patients, other identifying information was removed and the analysis was conducted on aggregate data. Opioids dispenses included all opioids monitored by TPP Alberta, including codeine and tramadol. The prescribers of interest were physicians practicing in Alberta, therefore, only their prescriptions were included in our data analysis.
Patient and public involvement
Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our study.
Cohort of interest
Oral morphine equivalent (OME) is a value assigned to opioids to represent their relative potencies and is determined by using an equivalency factor to calculate a dose of morphine that is equivalent to the ordered opioid.17 OME per patient, per day, was estimated by dividing the total opioid dispenses that fell in a time frame of interest by its length of a time.
To identify patients of interest a data window was created around a reference day: 180 days before and 90 days after, the reference date was then translated weekly from mid-2013 to 2020 (figure 1). The number of people who received any amount of opioids in the previous 180 days (prereference day) was computed (figure 2). Chronic opioid recipients (blue line in figure 2) were defined as individuals who received prescriptions in at least half of the 30-day time intervals prereference day (six intervals=180 days), and have non-zero OME/day on the previous 90 days before reference day. The prereference data window was used to determine if a patient qualified as a chronic user. If so, the doses 90 days before and 90 days after the reference day were compared by their percentage reduction or increase. Among chronic patients, we identified high and very high dose receivers as those with >90 OME per day and >200 OME per day, respectively. Finally, rather than limiting the study with an arbitrary cut-off to define tapering, we looked at different levels of dose reduction, for example, ≥30% reduction, ≥50% reduction, ≥70% reduction and complete discontinuation.
Data window, prereference and postreference day. The reference date, and data window around it, are translated weekly in 2013–2020 to observe trends.
Number of patients over time. OME, oral morphine equivalent.
Data sources
For our analysis, we used community pharmacy dispenses received by TPP from Alberta’s Electronic Health Record (Netcare). Dispense data were used due to the unavailability of prescription data. The variables of interest are dispense date and dispense OME.
Measures
We measured the prevalence of potential rapid tapering at a given date (reference day), enveloped by a data window. The reference day was then translated weekly over time from mid-2013 to 2020 (figure 1). Opioid doses, measured by OMEs, were compared before and after the reference day. Subsequently, the number of people who experienced a dosage decrease above the given thresholds (≥30%, ≥50%, ≥70% and discontinuation) was calculated.
Recommendations for safe opioid dose tapering from the US CDC and the Canadian Guidelines discourage dose tapering above 5%–10% of the OME every 2–4 weeks.5 6 The 2017 Canadian guidelines suggest a 5%–10% dose reduction in daily OMEs every 2–4 weeks as a reasonable rate of taper for patients receiving opioids over 90 or more daily OMEs.18 The US CDC provides a dose decrease of 10% of the original per week as a reasonable starting point for tapering opioids.5 Both guidelines recognise that the rate of taper needs to be individualised to what is most appropriate within the clinical context. We used a conservative approach13 to identify rates of tapering that might be considered rapid and in excess of recommended thresholds.
Analysis
Autoregressive integrated moving average (ARIMA) model was chosen to perform the trend analysis as patient dose tapering can be seen as an event on a time series that is autocorrelated and non-stationary. ARIMA models are routinely used to evaluate population-level interventions.11 15 19–21 Three parameters (p, d, q) specify an ARIMA model. The first and last, p and q, correspond to the orders of the autoregressive (AR) and moving average (MA) parts. AR and MA are different techniques used to analyse stationary time series data. The middle parameter, d, corresponds to the difference part, which is used to make a time series stationary. ARIMA is a combination of these methods for a better fit of the model.
The automated algorithm auto.arima in the forecast package for R was used to identify the ARIMA model terms.22 The impact of the interventions is modelled with ramp and step functions, to accommodate for an immediate slope change in trend after the intervention dates, or a level shift after the intervention date, respectively.
To evaluate the impact of the Snapshots, we included intervention functions in the ARIMA model at release dates (December 2016, May 2017, August 2017, December 2018, May 2018, August 2018, November 2018, February 2019, September 2019, February 2020 and September 2020). To account for the release of the CDC and Canadian opioid prescribing guidelines, intervention functions in April 2016 and May 2017 were also examined. Finally, the effective date of the related opioid prescribing SOP in Alberta (April 2017) was evaluated as well.
For the measures evaluated, the best fit was recorded along with the (p, d, q) parameters, coefficient of association (corresponding 95% CI) and associated p values (see online supplemental tables 1 and 2). Positive coefficient values indicate an increase in trends, while negative values signal a decrease in trends. Values of p<0.05 were considered a statistically significant effect.
Supplemental material
Results
Approximately 9000 dispenses (totalling ~6 million OME) per day were analysed from 2013 to 2020. Figure 2 depicts the total number of opioid recipients, which has a highly cyclic nature with the number of people who receive any opioid prescription peaking annually during the winter. An overall decrease was noted during 2020. The number of chronic opioid recipients remained relatively stable from ~70K in 2013 to ~86K at the end of 2020, peaking around 2016–2017 at ~94K. Among chronic patients, high and very high dose recipients show a decrease in numbers after 2017, representing an overall downward trend from 18% to 12% and 9% to 5%, respectively. It is worth mentioning that the further decrease of patient numbers in 2020 could be linked to the COVID pandemic.20 23 The prevalence of potential dose tapering among chronic recipients with high and very high opioid doses has remained somewhat stable or, since 2015, downward in trend (figures 3 and 4). Approximately 11%–12% of chronic high dose recipients experience potential rapid dose tapering at a rate of 50% or more prereference to postreference day at any given point of time. This percentage has remained stable, decreasing from 13%–14% in 2015–2017 to 9%–10% in 2020. For chronic very high dose recipients, approximately 11.5% experience potential rapid dose tapering at a rate of 50% or more prereference to postreference day at any given point of time. Potential discontinuation has also remained constant and the interventions did not have a significant impact on the trend.
Potential rapid dose tapering among high-dose recipients.
Potential rapid dose tapering among very high dose recipients.
Effect estimates from the main analysis (see online supplemental tables 1 and 2) show that the observed association of a given intervention with ongoing trends was not significant in some cases. In the instances the intervention functions were significant, we look at the coefficient estimations and their confidence intervals (fourth column). Negative values indicate a decreasing trend while positive values are associated with an increase. Similar results can be observed regarding potential discontinuation (see online supplemental tables 3 and 4).
Discussion
Our study is the first exploration of potential rapid tapering and/or discontinuation of opioids in Alberta, and this work adds to existing evidence from other jurisdictions in Canada and USA. Alberta’s 2013–2020 prescription opioid dispense data show a relatively stable number of chronic patients overall. We observed a significant decrease in the number of high and very high dose recipients after 2017 in our analysis. Overall, 11%–12% of chronic high dose and 11.5% of chronic very high dose recipients experienced potential rapid dose tapering (>50% dose reduction prereference to postreference day) at any given point of time. However, these percentages have remained stable for both groups of chronic recipients and actually tended to decrease before the release of the inaugural MD Snapshot-Prescribing reports in 2016.
Our findings are consistent with another Canadian study that found decreasing trends in prescription opioids across all provinces in recent years.14 Numerous opioid prescribing guidelines, regulations and policies, including prescription monitoring, implemented on provincial and national levels likely influence physician prescribing behaviour.10 14 15 24 25 For example, a study examining the effectiveness of prescription drug monitoring programmes in 24 states in the USA suggested that monitoring programmes alone raised prescribers’ awareness about controlled substance misuse and made them more cautious and reasonable while prescribing opioids.25 Changing prescribers’ behaviour and the corresponding decreasing trends in prescription opioids could also result from increased media coverage of potential negative effects of inappropriate rapid tapering and/or discontinuation on patients.9 15
Comparing the findings of recent studies on rapid tapering of opioids has several limitations. First, there are no standard definitions of long-term opioid therapy, tapering and dosage discontinuation; furthermore, these studies apply different methodological approaches.16 26 However, our results generally align with the findings from the ODPRN (Ontario Drug Policy Research Network) study in Ontario15; their researchers reported downward trends in the numbers of very high dose opioid recipients from 29 413 to 15 730 individuals and in the average monthly prevalence of rapid tapering from 1.4% to 1.2% between 2014 and 2018. Yet, the ODPRN study15 found that rapid opioid dose tapering events temporarily increased in response to drug guidelines, policies and programmes implemented by federal and provincial authorities in 2016 and 2017. These changes, however, were relatively small and short-lived. The study authors highlight the importance of communication and prescriber resources as mitigation strategies for the unintended consequence observed in their study.
Thus, unlike similar studies looking at the impact of new prescribing guidelines and monitoring programmes on potentially inappropriate tapering of opioids, we did not find evidence of rapid opioid tapering and discontinuation in Alberta after the implementation of various prescribing interventions, policies and guidelines.
There are a few limitations with this study. First, Alberta’s Pharmaceutical Information Network data monitored by CPSA do not include days supplied for each dispense, which presents limitations when calculating OME per day. To circumvent this issue, the data window is moved every week during the time period analysed. The OME per day in a time frame of interest (figure 1) is calculated by dividing the total OME by the length of the time period in days. By moving the time frame constantly and comparing 30 days before and after the reference date, we stabilise our estimates consistently. The plots in figures 2–4 reveal a clear trend that suggests our estimates are robust.
Second, our definitions of chronic opioid receivers are somewhat arbitrary (dispenses in at least 3-month periods before the reference date). This threshold was chosen after other definitions were tested, all with similar results. Our justification was that we were interested in observing general trends, and this cut-off was conservative enough, without excluding too many patients of interest. The generalisability of the study results may be limited owing to the limitations discussed, but the results are aligned with the literature.
Despite the limitations regarding actual dispense days and dosage per day, the data available have other elements that could allow for a deeper analysis. For instance, rather than population level study, a network analysis that connects physicians and patients (as nodes) by prescription (as edges) could reveal more nuanced information regarding the types of interactions, prescription recipients, as well as the existence of ‘hubs’ for either physicians and/or patients.
Thus, we can conclude that the release of the CPSA’s MD Snapshot-Prescribing reports; the US CDC and Canadian opioid prescribing guidelines did not create an increase in rapid opioid dose tapering and/or discontinuation in Alberta. At best, some interventions (or the timing of them) are associated with a small decrease in discontinuation trends. Thus, anecdotal reports of potentially inappropriate rapid tapering and/or discontinuation of opioids in Alberta appear to be fiction.
Data availability statement
Data may be obtained from a third party and are not publicly available.
Ethics statements
Patient consent for publication
Ethics approval
Ethics approval for this study was obtained from the University of Alberta’s Health Research Ethics Board (Pro00107844).
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Twitter @IHurava
Contributors NH-C conducted data analysis and prepared the initial draft of the manuscript. FG initiated the study and provided support for the analysis. IH, NAK and NA contributed to the drafting of the manuscript and provided assistance in interpreting the study results. NH-C, FG, IH, NAK and NA critically reviewed the manuscript for significant intellectual content. The final approval of the manuscript was given by NH-C, FG, IH, NAK and NA. All authors agreed to be responsible for all aspects of the work, ensuring that any questions regarding accuracy or integrity are thoroughly investigated and resolved. Guarantor: NH-C.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.