P-010 - Pharmaceutical Automated Reporting: An Opioid Stewardship Tool

Abstract Title: Pharmaceutical Automated Reporting: An Opioid Stewardship Tool

Background: Although Saskatchewan's population is small compared to other provinces in Canada, opioid-related harms are significant. In 2022, Saskatchewan had 21.3 apparent opioid toxicity deaths per 1000 population compared to Manitoba, which has a similar population size of 1.4 million, but had only 3.7 deaths per 1000 population (1). Saskatchewan, along with British Columbia and Alberta, exhibited the highest rates of opioid-related hospitalizations in Canada. The misuse of opioids poses a notable hazard to the community; opioid stewardship initiatives have begun addressing these pressing issues (2).

Clinical decision support systems (CDSS) have been suggested as a way to address barriers to adherence to opioid prescribing guidelines (3–5). Some studies have shown improvements in adherence to guidelines and confidence in treating opioid use disorder, while others have reported low utilization rates of CDSS (6–9). To improve the safety of opioid use, it is recommended that Opioid Stewardship Programs (OSPs) use electronic CDSS to promote stewardship interventions (4).

Purpose/Objectives: Within our acute care facilities (~700 beds combined), there are no inpatient addiction medicine teams, acute, chronic, or transitional pain services available. There are limited specialists to support clinicians and patients with opioid therapy. Much of this responsibility falls onto the OSP, consisting of two pharmacists, a nurse practitioner, two data analysts, and a research scientist. There are challenges for our OSP team, with a limited number of clinicians, to identify and address the opioid-related risks within our facilities. It is difficult for our small, resource-limited center, lacking an integrated electronic health record and limited funding, to incorporate third-party CDSSs to help direct appropriate prescribing. Due to the widespread use of opioids in acute care and the high risk for opioid-related harms, we developed our own CDSS to direct daily interventions and report data-driven patterns and systemic deficiencies, thereby promoting safer opioid prescribing, resource allocation, patient safety, and improved outcomes.


Methods: The Pharmaceutical Automated Reporting (PAR) Tool consolidates inpatient prescription information from pharmacy drug utilization reports and organizes patients according to predetermined logic. The tool automatically classifies patients based on risks associated with opioid prescriptions and the activation of opioid-related risk factors that may lead to potential harm. The risk factors were chosen based on the pharmacist opioid safety and intervention tool (10), published opioid stewardship research (11,12), as well as information from the Opioid Stewardship Checklist (13) which highlights the Institute for Safe Medication Practices Targeted Medication Safety Best Practices for hospitals.

The risk factors include, within the last 24 hours, morphine milligram equivalents (MME) equal to or exceeding 90, potential opioid agonist therapy, administration of naloxone, absence of naloxone prescription with opioid prescription, multiple opioids prescribed, intravenous therapy lasting more than seven days, frequent dosing (every 1 hour, 2 hours, or 3 hours), combination of benzodiazepines and opioids, and potential use of the Clinical Institute Withdrawal Assessment for Alcohol, Revised (CIWA) protocol. We accounted for opioids administered on an as-scheduled dose and those administered on an as-needed basis in the total daily MME calculation. Black Box testing and clinician evaluation were employed to validate the tool for accuracy.


Results: In the first seven months of utilization, the PAR Tool evaluated 10,562 distinct patient visits (on average 312 per day), resulting in the detection of 10,450 (98.9%) patients with at least one opioid-related risk factor and 6590 (62.4%) triggering multiple risk factors simultaneously. Furthermore, the Tool has examined 65,688 individual patient prescriptions for potential risk factors associated with opioid-related harm.

Patient visit findings (data collected in the preceding 24 hours relative to the date of the report; n=10,562):

• No Naloxone Prescription with an Opioid Prescription: 79.2% (8361)


• High Frequency Dosing (q1h, q2h, or q3h): 42.8% (4518)


• Multiple Opioids Prescribed: 37.8% (3992)


• Benzodiazepines and an Opioid: 9.7% (1026)


• Over Seven Days of Intravenous Therapy: 9.5% (1004)


• MMEs** Taken Over or Equal to 90: 6.9% (724)


• Possible Opioid Agonist Therapy: 5.8% (617)


• Possible CIWA Use: 1.2% (125)


• Naloxone Given: 1.2% (123)*

Additional findings (data over the patient’s entire visit; n=7,988):

• Average Available MMEs** per Opioid Prescription: 389


• Total Population with Calculable MMEs** >= 50 Available: 87.3% (6970)


• Total Population with Calculable MMEs** >= 90 Available: 75.9% (6060)


• Total Population Naloxone Prescriptions: 20.3% (2139)

< *Naloxone usage determined by removal from automated medication cabinet (PYXIS).

**MMEs were determined to be not calculable for patient-controlled analgesia, parenteral fentanyl, epidural, spinals, intrathecal pumps, or cassettes.



Conclusions/Implications for future research and/or clinical care: Resource-scarce health systems have an opportunity to utilize open-source coding to create an internal CDSS to address potentially harmful opioid prescribing. The PAR Tool has enhanced the efficiency, accuracy, and quantity of patient triage for opioid-harm-related risk factors. The tool has identified specific areas where data-driven interventions should be focused to engage in targeted behavioural change in promoting appropriate prescribing practices. Access to system-level data is used to direct and track stewardship interventions and to inform systemic policy change around appropriate opioid use.

Limitations include the requirement for clinical interpretation and an inability to prevent potentially harmful opioid orders in real-time. Lastly, the code is dependent on the standardized output of the pharmaceutical reports, if there is a change in the report structure the code must be modified.

Future research should investigate the acceptance rate of OSP recommendations, the effectiveness of behavioural change interventions, and the impact on quality indicators.


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13. Editors of Therapeutic Research Center. Hospital Pharmacist’s Letter/Pharmacy Technician’s Letter. 2020. Opioid Stewardship Checklist.