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Abstract
Background Opioid overprescribing is commonplace after total hip (THA) and total knee arthroplasty (TKA). Preliminary data demonstrated that approximately 32% of the opioids prescribed at discharge from our hospital following THA and TKA remain unused. This is a concern given that unused prescribed opioids are available for diversion and may result in misuse and abuse.
Methods Pre-intervention data were collected between 1 November 2018 and 10 December 2018. An intervention bundle was then introduced, including education of patients and providers, a standardised pain management algorithm and an autopopulated discharge prescription. The aim of this quality improvement initiative was to reduce the amount of opioid (average oral morphine equivalents (OME)) dispensed (based on the discharge prescription provided) following THA and TKA at our institution by 15% by 1 April 2019.
Design Using an interrupted time series design, the outcome measure was the amount of opioid (OME) dispensed from the discharge prescription provided. Process measures included the percentage of autopopulated discharge prescriptions, the percentage of patients receiving education at discharge and the percentage of nurses and residents receiving standardised education. Balancing measures included patient satisfaction with postoperative pain management, and the percentage of patients filling the second half of the part-fill or requiring a subsequent opioid prescription.
Results With 600 patients identified, mean OME dispensed at discharge was reduced by 26.3% (from 522.2 to 384.9 mg) after our interventions started. Utilisation of autopopulated part-fill prescriptions was 95.8%. There was no change in patient satisfaction nor in the proportion of patients requiring an additional opioid prescription post-intervention. Only 39% of patients filled the second half of the part-fill prescription post-intervention.
Conclusions Mean OME dispensed at discharge per patient was reduced with no change in patient satisfaction after introduction of the intervention bundle.
- Pain Management
- PDSA
- Postoperative Care
- Quality improvement
- Surgery
Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information.
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/.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
Overprescribing opioids after total hip and knee replacement is a commonplace with excess medication available for diversion and abuse. This is a major concern amidst the current opioid crisis.
WHAT THIS STUDY ADDS
The implementation and sustainability of this bundle can be easily adaptable at other medical centres.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
Our study outlines a successful quality improvement bundle that reduced the amount of opioids dispensed from the acute postsurgery discharge prescription.
Introduction
The use of opioids is commonplace following total hip arthroplasty (THA) and total knee arthroplasty (TKA), with up to 80% of patients complaining of moderate to severe pain during the early postoperative period.1 2 However, previous studies have shown that a large proportion of the opioid prescribed typically remains unused following arthroplasty surgery, with over 90% of the excess not being disposed of appropriately, leading to the potential for diversion and misuse.3–6
In North America, the growing opioid crisis has led to calls for improved opioid stewardship. In Ontario alone, 2833 people died from opioid-related causes between 2013 and 2016 with up to 64% of these deaths resulting from prescribed opioids.7 Preliminary data from our hospital, collected from THA and TKA patients between May 2017 and March 2018, showed that 32% of the opioids we were prescribing remained unused at 12 weeks postoperatively.8
A number of studies have suggested that prescribing fewer opioid pills at discharge is associated with lower opioid consumption without a negative impact on pain scores, patient satisfaction or Patient-Reported Outcome Scores.1 4 9–11 A systematic review by Wetzel et al identified the following strategies to improve opioid prescribing patterns12 : implementing preoperative counselling about pain and opioid expectations with or without shared decision-making on the quantity of opioids to be prescribed at discharge13–16; developing guidelines for prescribing opioids17 18 and standardising the default pain medication in the electronic ordering system.19 20 Other successful interventions include having pharmacists assist with prescribing21 and educational interventions targeted to prescribing physicians.22–24 The American Academy of Orthopedic Surgeons in conjunction with the American Society of Anesthesiologists has released guidelines on standardised prescribing practices, identifying those at risk for prolonged opioid use and safe disposal of opioids in an attempt to curb overprescribing and diversion.25–27
The challenge is developing a comprehensive multimodal intervention that can be effectively implemented and sustained within the local context of a specific institution and patient population. Although the literature is abundant on reducing the quantity of prescribed opioid, to our knowledge, very few of these studies have used a system-based quality improvement (QI) approach to implement a change in prescribing patterns. Here, we describe our QI initiative to achieve our goal of reducing oral morphine equivalents (OME) dispensed based on the discharge prescription by 15% following THA and TKA surgery at our tertiary care institution.
Methods
This report follows the Standards for QI Reporting Excellence guidelines for innovations that improve quality and safety in healthcare.
Study design
This was a QI study with an interrupted time series design, which followed the Institute for Health Care Improvement’s Model for Improvement.28 The three phases of the study were as follows: (1) assessment of the problem and development of the QI intervention, (2) implementation of the intervention and (3) assessment of the intervention’s effectiveness and sustainability. An Ishikawa diagram, the 5 Why’s, a Pareto chart and process mapping were used to assess the problem. Plan-Do-Study-Act (PDSA) cycles were then used to develop and implement the intervention, which consisted of a bundle of changes designed to address the major root causes of the overprescribing problem.
Study setting and population
The study was conducted in the orthopaedic unit at a university-affiliated, tertiary care centre for adults in Toronto, Canada. The average length of stay for elective THA and TKA patients at our institution is 1 day. Patients typically return to outpatient clinic for routine follow-up visits at 4–6 weeks, 3 months and 1 year following surgery. Patients included in this study were those who underwent elective primary THA and TKA and were discharged home from the acute care hospital. Patients excluded from the study were those on high doses of opioids preoperatively (defined as using more than 45 mg OME per day), those undergoing revision surgery, and those patients discharged to a rehab facility. Patients discharged to an inpatient rehabilitation facility were excluded as they did not receive an opioid prescription at the time of discharge from the acute care hospital. As well, opioid prescriptions and dispensation from these facilities were highly variable as was the timing of discharge home and were controlled by the rehabilitation physicians. Less than 10% of patients are discharged to an inpatient rehabilitation facility following THA or TKA at our hospital.
Study team and analysis of the problem
Between September and November 2018, an opioid stewardship team, identified through stakeholder mapping, was assembled and used diagnostic tools to identify the root causes of overprescription of opioids following THA and TKA at our hospital. Team members included an orthopaedic surgeon and resident, a staff anaesthesiologist, an acute pain service (APS) nurse practitioner, an orthopaedic ward nurse-in-charge, two pharmacists, a nurse educator and two physiotherapists. Seven contributing root causes were identified and ranked based on the healthcare providers’ perception of importance (online supplemental appendix 1). A driver diagram developed for the root causes suggested that a multimodal intervention addressing the top five root causes would provide the optimal effect on reducing opioids dispensed at discharge following THA and TKA. The top five ranked root causes identified by the team were as follows:
Supplemental material
Lack of patient knowledge about postoperative pain management strategies.
Lack of nursing knowledge about pain management education for patients.
Lack of knowledge among orthopaedic residents about optimal discharge pain management prescribing.
Lack of a standardised opioid prescription template for THA and TKA patients.
Lack of provider knowledge and use of strategies such as part-fill instructions and expiry dates.
Intervention (change ideas)
Patient education and pain management pamphlets
To improve patient knowledge about pain management strategies, the opioid stewardship team created a written pamphlet that included information about the importance of multimodal analgesia, how to taper off opioids and methods for safe storage and disposal. The pamphlet was piloted with several patients and improved based on this usability testing prior to full implementation. Clerical staff included the finalised pamphlet as a standard component in the discharge package provided to THA and TKA patients. Incorporating the new pamphlet into the standard workflow also acted as a physical reminder for nursing staff to provide patient education on safe opioid use and disposal at discharge.
Education of nurses and prescribing physicians
Nurses and physicians underwent training on appropriate discharge prescribing for pain management, including use of a standardised opioid prescribing algorithm, autopopulated part-fill instructions with expiry dates and how to educate patients using the pain management pamphlets. Nurses received a standardised 15 min Power-Point presentation that was presented nine times over 2 weeks from 19 November 2018 to 30 November 2018 with the goal of educating at least 80% of the orthopaedic nursing staff.
Orthopaedic residents were provided with individual education on the intervention package and autopopulated discharge order set by the ward pharmacist. After the initial period of focused education, the standardised opioid prescribing protocols were incorporated into orientation sessions for new nurses and physicians (including trainees).
Standardised opioid prescribing algorithm
Based on historical prescription patterns and review with stakeholders, the opioid stewardship team developed a standardised oral multimodal discharge prescription template for pain management. Baseline data showed that patients were typically discharged with a prescription for sixty 1 mg or 2 mg pills of hydromorphone, with older patients typically receiving the lower dose. We; therefore, selected hydromorphone 2–4 mg orally every 4 hours PRN for patients under the age of 75 and hydromorphone 1–2 mg orally every 4 hours PRN for patients 75 and older. In order to minimise reliance on opioids, the standardised prescription template also included standing acetaminophen (1000 mg orally three times per day×14 days) and celecoxib (200 mg orally daily×14 days) for all patients without a contraindication (alterations were allowed for patients with allergies and/or intolerances).
All patients were seen by our APS, which is run by the anaesthesiology service with the involvement of dedicated nurse practitioners. APS was responsible for customising pain medications in hospital, when required, and discharge prescriptions were modified for patients with atypical requirements. The standardised prescription was reviewed with three orthopaedic residents and four orthopaedic surgeons as well as members of the APS for their opinions and recommendations before finalising the algorithm.
Automated part-fill instructions with expiry dates on opioid prescriptions
Baseline data collected at our institution (May 2017 to March 2018) showed that 55% of patients required opioids for less than 2 weeks and these patients accounted for the majority of the excess quantity of opioid prescribed.8 Additionally, 78% of THA and 49% of TKA patients reported having unused opioid.8 Based on this information (and feedback from three community pharmacists, two physicians and an information technology (IT) expert), the opioid stewardship team decided on a standardised discharge opioid prescription totaling 60 pills, split into two 30 pill part-fills, with the instruction ‘dispense 30 tablets today, then dispense a further 30 tablets in at least 3 days if required for pain, expiry date 30 days from date of prescription’ autopopulated into the discharge prescription template through our electronic medical record (EMR). Implementing this change required collaboration with our hospital’s IT department, as such an automated discharge prescription template had not previously been used at our hospital. We felt this was important, however, to ensure that the intended discharge prescription was reliably and sustainably implemented, despite frequent changeover in trainees (many of whom were familiar with more traditional opioid prescribing practices still in use at other sites).
Study of interventions and measures
A family of measures, including outcome, balancing and process measures, was developed and then longitudinally tracked to inform our PDSA cycles. Data were collected through manual chart review and patient surveys (online supplemental appendix 2) and reviewed on a weekly basis.
The primary outcome measure was the mean OME dispensed per arthroplasty patient based on the opioid prescription provided at discharge. The OME dispensed per patient was calculated from the amount of opioid prescribed at discharge (retrospective chart review) and whether or not the second part-fill was obtained (patient surveys). Clinic staff collected survey data from patients at their initial postoperative follow-up visit (4–6 weeks postdischarge).
Process measures included: (1) the percentage of discharge opioid prescriptions including part-fill instructions, (2) the percentage of discharge packages including a pain pamphlet and (3) percent of nurses and residents receiving pain management training.
Balancing measures included: (1) patient satisfaction with the postoperative pain management protocol (assuming patient would be less satisfied if they experienced either financial or logistical hardship as a result of having to obtain the second part-fill or if their pain management was poor), (2) the percentage of patients obtaining the second part-fill and (3) the percentage of patients who requested an additional opioid prescription after the initial prescription was completed.
All data from surveys were input into a central password-protected database that was stored on a secure hospital server. Data were double-checked by a second member of the opioid stewardship team to ensure accuracy.
Data analysis
Patient demographics were assessed using measures of central tendency. When comparing the pre-intervention and post-intervention groups, χ2 tests were used to determine significance between groups for non-continuous variables (Gender, TKA/THA) and Student’s t-test was used to determine significance for continuous variables. Demographics were analysed comparing the entire pre-intervention and post-intervention populations as well for only those patients who completed the surveys pre-intervention and post-intervention.
Statistical process control (SPC) was applied to analyse the outcome, balancing and process measures. Average OME dispensed and patient satisfaction scores were monitored using X bar and S charts. In order to calculate OME, patients had to respond to the question about whether or not they picked up the second part-fill on the survey. If this field was blank, the data were considered missing and no OME was calculated for that patient. Additional opioid prescriptions requested beyond the initial discharge prescription were likewise excluded from the OME calculation as we were unable to confirm the exact details of any such prescriptions. P charts were used to monitor the measures that consisted of proportions of patients. To differentiate special cause variation from common cause variation on the SPC charts, QI Macros SPC software for Microsoft Excel was used (this software has built-in analytics allowing the identification of special cause variation). Healthcare rules were followed when identifying special cause variation.
We performed a separate subgroup analysis of patients in the post-intervention group to identify the differences in outcome and balancing measures between THA and TKA. Independent Student’s t-tests were used to compare the difference in means for normally distributed data including patient satisfaction and non-parametric OME. The χ2 test was used to determine significance between the discrete non-continuous variables, second part-fill pick up and requirement for an additional opioid prescription. Significance was set at p<0.05.
Results
Between 1 November 2018 and 25 June 2019, we identified 600 patients who underwent primary THA or TKA. The mean survey response rate was 55.5% (n=333/600) with a response rate of 57.9% pre-intervention and 54.5% post-intervention. Patient demographics pre-intervention and post-intervention are presented in table 1 and were similar across all groups. Implementation of the QI bundle began on 11 December 2018. In the post-intervention period, the mean OME dispensed based on the discharge prescription was reduced by 26.3%, from 522.2 to 384.9 mg OME (figure 1). Special cause variation was detected between 12 December 2018 and 25 June 2019 (8 or more consecutive points were below the centreline) and a new baseline was created once it was clear that the system was stable at a new, lower, OME dispensed.
Patient demographics
Outcome measure: mean oral morphine equivalents (OME) dispensed based on discharge prescription after THA and TKA. THA, total hip arthroplasty; TKA, total knee arthroplasty; UCL, upper control limit; LCL, lower control limit.
In the post-intervention period, 95.8% of opioid prescriptions included part-fill instructions and expiry dates (online supplemental appendix 3). Based on random audits conducted between 16 January 2019 and 1 March 2019, pain pamphlets were included in 84% of discharge packages. Special cause variation was detected on 25 February and 26 February (two points outside the control limits) as the percentage of discharge packages including pain pamphlets dropped to 0% (online supplemental appendix 4). After identifying the astronomical points, the study team performed a deep dive and identified that casual clericals, who were not aware of this new task, were working on the orthopaedic ward on these dates. As a result, casual clerical staff were subsequently educated about this new task, which resolved the issue. All orthopaedic residents (100%) and 89% of the nurses received opioid stewardship education and training.
There was no change in patient satisfaction between the pre-intervention and post-intervention groups, which remained at a mean of 7.5 (Numerical Analogue Scale, from 0 (not satisfied) to 10 (very satisfied) throughout the project (figure 2). The percentage of patients obtaining the second half of the part-fill prescription was 38.9% (online supplemental appendix 5). The percentage of patients requiring a further opioid prescription was similar between the pre-intervention and post-intervention groups (21% pre-intervention vs 22.5% post-intervention, online supplemental appendix 6). Post-intervention 43.9% of patients (n=119/271) were dispensed half or less of their initial opioid prescription and did not require a second bottle pick-up nor an additional opioid prescription.
Balancing measure: mean patient satisfaction with multimodal analgesia prescription protocol (scale from 0 (not satisfied) to 10 (very satisfied)).
Subgroup analysis post-intervention demonstrated mean OME dispensed of 366.5 mg (SD 179.4, range 0–1200 mg) for THA and 405.5 mg (SD 196.8, range 0–900 mg) for TKA. In spite of this difference, these values were not statistically significant. Similarly, patient satisfaction was higher in the THA group but did not reach statistical significance. The proportion of patients requiring the second part-fill of the prescription or an additional opioid prescription was significantly greater in the TKA cohort. Subgroup analysis is presented in online supplemental appendix 7.
Discussion
The implementation of a multimodal QI bundle designed to reduce the quantity of opioids dispensed at our institution following THA and TKA led to a 26% reduction in the mean OME dispensed from the discharge prescription (from 522.2 to 384.9 mg). In spite of this reduction, there was no impact on patient satisfaction or the number of patients requiring a further opioid prescription. Hannon et al similarly reported that reducing postdischarge oxycodone from 90 to 30 tablets in THA and TKA patients resulted in equivalent pain and PROM scores while reducing unused opioid.1
The 26% reduction in OME dispensed is comparable to a 34% reduction demonstrated by Meisenberg et al, who also implemented a multimodal intervention to reduce opioid prescription.11 Similarly, development and initiation of a prescribing guideline by Howard et al for laparoscopic cholecystectomy patients led to a prescription size reduction of 119 mg OME, which is similar to the absolute OME reduction of 137.3 mg achieved in our study.17 The success of multimodal interventions could be the result of incorporating the perspectives of physicians and allied health staff in the analysis and decision-making process. Additionally, combining interventions targeted at the patient and healthcare staff respectively with effective system-based interventions including automation of the standardised autopopulated discharge prescription and expiry dates further improves the efficacy.
Approximately 39% of our post-intervention patients required the full 60 tablets and 22.5% required a further opioid prescription; however, a number of these further prescriptions were related to the potency of the initial medication and associated side effects. In spite of the reduced OME dispensed, 43.9% of patients required half or less of their prescription quantity. This result was mirrored in our preliminary data.8 It is, therefore, evident that a substantially reduced discharge opioid prescription is acceptable for almost 50% of patients undergoing THA and TKA. It remains challenging, however, to accurately predict preoperatively which patients will have a larger opioid requirement.
Autopopulated standardised discharge prescriptions including part-fill instructions had never been used previously at our institution. However, by collaborating with our IT team, we were able to develop a custom solution within our EMR. This intervention was likely crucial to the success of our initiative, acting as a strong standardised reminder and almost a forcing function (although the suggested prescription could be over-ridden). Without this intervention, it may have been very difficult to ensure that all orthopaedic residents remembered the appropriate multimodal prescription template as well as how to write in the part-fill and expiry instructions. Utilisation of the part-fill prescription remained at >95% from the first day post-intervention to the target date of 1 April 2019. This extremely high rate of utilisation remained unchanged for a further 3 months proving the sustainability of this automated intervention.
Although use of part-fill opioid prescriptions is a common strategy used for patients with substance use disorders, using part-fill opioid instructions for all postoperative opioid discharge prescriptions will add to the armamentarium of opioid stewardship interventions for the general population.29 Moreover, use of part-fills should increase patient interaction with healthcare providers as the patient is required to speak with a pharmacist before obtaining the outstanding quantity of opioids. This has the potential benefit of increased monitoring of opioid use as well as potential early identification of opioid misuse or postoperative issues that may be causing excessive postoperative pain.
Study strengths
This study was pragmatic and applied to a real-world population of THA and TKA patients that should be typical of those treated in high-volume arthroplasty centres, allowing for generalisability of our results. Our study used reproducible and validated QI techniques to significantly reduce opioid dispensation in the acute postoperative period. The specific tools developed, such as part-fill instructions, patient and provider education and the pain pamphlet, can be adapted to almost any hospital practice and protocol (day surgery vs in-patient arthroplasty). Patients at our institution were included irrespective of the aforementioned model of care. Provider education rates were high and uptake was significant, which is reflected in the result of our process measures including pain pamphlet inclusion and use of part-fill prescriptions which remained >95% throughout the post-intervention period.
Prior to this study, the prescribing patterns of our unit were historically variable and based on individual surgeon and prescriber preferences. The clinical area had motivated surgeons to help drive the initiative. In spite of making drastic changes and standardising our prescribing patterns as a unit, using a multidisciplinary committee with physicians and allied health staff allowed us to introduce this change swiftly. In addition, we were able to sustain the intervention by continuing to educate those joining the service beyond the initial transition period. Furthermore, by automating the discharge prescription with a standardised order set linked to THA and TKA patients, we removed the potential for significant deviation from the intended multimodal pain protocol and facilitated compliance with the rapid change.
Limitations
There are a number of limitations to our study. First, we do not report on clinical outcomes such as hospital representation or readmission, nor any overdose data. These secondary outcomes are important clinical indicators and should be included in further studies. Additionally, we have only identified a reduction in the quantity of opioid available for diversion but not ascertained the rate of patients with left-over tablets who used safe disposal methods. We plan to include this in the second part of our study.
Using a survey-based system for data collection creates the potential for recall bias. Access to data through eHealth Ontario is not permitted and data through the Canadian Institute for Health Information would be substantially delayed by 6–12 months or more. This is not a feasible solution for the purposes of a time sensitive dynamic QI study. Contacting the patients’ individual community pharmacies would similarly have been timely and cost-prohibitive as this study was not funded. The study team felt that most patients/caregivers would recall picking up the remaining part-fill and the survey data were, therefore, deemed to be the most effective way to collect this information, accepting the risk of recall bias. As a result, the OME dispensed could only be calculated based on discharge prescription quantity and survey recall. Validation of the OME dispensed and used could be improved with a medication diary and this may be used in future studies.
Finally, the methodology of this study does not allow causation between the multimodal intervention and the reduction of opioids dispensed to be definitively determined. However, temporal association of the special-cause variation with the implementation of our intervention strongly suggests that the intervention was related to the changes in opioid prescribing that were observed.
Future directions
Consistent with our findings, patients undergoing THA have previously been shown to consume 30% less opioid versus patients undergoing TKA.30 Further, Sabatino et al demonstrated that on average 10% more opioid analgesia pills remained unused following THA when compared with TKA.4 Our subgroup analysis suggests that it may be possible to further reduce the OME dispensed to THA patients without compromising patient satisfaction or increasing either uptake of the second part-fill pick-up or the need for an additional opioid prescription. Based on these finding, we plan to further reduce discharge opioid prescription in our THA population.
Conclusion
Reduction in opioid overprescription at hospital discharge without impacting patient satisfaction can be achieved following THA and TKA through the use of standardised opioid prescriptions including part-fill instructions and expiry dates as well as education to patients, nurses and prescribers. The interventions used in this study can be easily adopted at other centres wishing to decrease opioid prescribing in this patient population but will need to be tailored to the local context to ensure sustainability. Using IT solutions such as standardised discharge prescription templates incorporated into the hospital EMR may be helpful to increase the sustainability of opioid stewardship interventions.
Data availability statement
All data relevant to the study are included in the article or uploaded as online supplemental information.
Ethics statements
Patient consent for publication
Ethics approval
The local institutional review board reviewed this quality improvement initiative and deemed neither research ethics board approval nor written informed consent from participants to be required.
Acknowledgments
Thank you to St Michael’s Hospital for recognising and honoring our team with a Health Disciplines Interprofessional Collaboration Award in 2020
References
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
Contributors VL, BC, SS, CJ, AP, EL, SY, PR-R, KT and SW planned the design of the study. VL, BC and SW designed the data collection tools and SS, CJ, AP, EL, SY, PR-R and KT reviewed. AP and CJ collected the data. VL and SW monitored data collection and wrote the statistical analysis. VL, DC and SW cleaned and analysed the data and drafted and revised the paper. BC, SS, CJ, AP, EL, SY, PR-R and KT reviewed and revised the paper. SW is the guarantor of the project.
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 involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
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.