Best Practice Alert for Opioid Prescribing

Opioid Use Clinical Trial

Official title: Best Practice Alert for Post-Surgical Opioid Prescribing At Discharge

Status Completed

Clinical Trial Summary

The investigators will embed a developed decision support tool into the electronic health record (EHR) to individualize pain therapy in surgical patients after hospital discharge and test its performance in a pragmatic clinical trial.

Preliminary data indicate that current opioid prescription practice after surgery follows a "one size fits all" pattern. In-hospital opioid use prior to discharge serves as a reliable indicator to estimate needs for analgesic medications at home. The investigators will test the hypothesis that the existing tool will enable providers to write need-based prescriptions based on prior-to-discharge opioid use, empower patients to maximize alternatives to opioids (ALTO) therapies at home, while minimizing the need for rescue prescriptions. The investigators will test this tool prospectively in a cohort of ~1,000 providers (primary subjects) and ~39,000 surgical patients (secondary subjects) in four University of Colorado Health (UCHealth) hospitals (clusters to be exposed versus (vs.) non-exposed to the intervention).

Clinical Trial Description

Converting knowledge on actual need for opioid pain medications after surgery into tangible benefits can prevent over-prescription of opioids that become available for non-medical use. The objective of this aim is to prescribe pain medications after surgery in a patient-centered fashion. The investigators have used the average amount of opioid medications (in milligram morphine equivalents - MME) taken prior to discharge to inform the clinical decision support tool. This tool will reduce the amount of opioid medications prescribed while maintaining patient post-operative pain control. The calculated "prior to discharge daily MME dose" will be applied to generate a recommendation for the prescription of a cumulative opioid dose that will be displayed when the electronic order entry for the post-discharge pain medication is made in the EHR using a best-practice alert (BPA). In addition, the provider will be prompted to also prescribe non-opioid analgesic medications. This BPA was developed by the Principal Investigator under guidance of the UCHealth System Multidisciplinary Opioid/Pain Management Committee as well as published guidelines.

Based on the relationship between opioids taken prior to discharge and post-discharge opioid intake described above as well as published guidelines for post-discharge prescriptions after surgery will use a tiered approach towards determining the total amount of opioids to be prescribed. Accordingly, the investigators have integrated an algorithm into the BPA such that opioid intake from the EHR only triggers the BPA if the total amount of prescribed opioids exceeds the predicted thresholds.

The opioid prescribing BPA will be assessed over a 44-week period in all eligible patients. At the time of writing the prescription an automatic notification will appear on the care provider's screen that identifies a suggested post-discharge opioid dose within the electronic prescription pad. If approved by the provider, opioid-only prescriptions will be written as suggested. Final dosing decisions and drug choices will remain at the discretion of the treating provider and will be tracked. The investigators will use an all "On" vs. all "Off" configuration to answer the questions if the average amount of total opioids per post-discharge prescription is lower with the BPA active. The investigation will commence with two "Off" periods to assess if reduction in prescribing patterns occurs over time regardless of the intervention. Two "On" periods at the end of the study will determine if any observed changes in prescribing patterns stabilize or continued changes take place. ;

Related Conditions & MeSH terms

• Opioid Use

• NCT number: NCT04446975
• Study type: Interventional
• Source: University of Colorado, Denver
• Status: Completed
• Phase: N/A
• Start date: July 7, 2020
• Completion date: June 8, 2021