IADR Abstract Archives
Reducing Dentists’ Opioid Prescribing Using Audit and Feedback Dashboards
Objectives: Dentists are among the leading prescribers of opioid analgesics, writing over 6.4% of all opioid prescriptions and 12% of all immediate-release opioid prescriptions, which are the most commonly misused prescription opioids. The objective of this study was to reduce opioid prescribing by dentists by examining the use of audit and feedback (A&F) as a behavioral intervention.
Methods: The randomized controlled trial (RCT) was implemented in one academic dental setting over a period of one year with 2 intervention groups and 1 control group of standard dental practice (40:40:20 randomization ratio). Dentists in the standard A&F intervention group received A&F dashboards about their own opioid prescribing compared with other similar dentists, and dentists in the enhanced A&F intervention group received standard A&F dashboards with additional information on their patients’ self-reported pain level 7-days after their procedures. Opioid prescriptions per 100 patient encounters were calculated and hierarchical logistic regression (adjusted for provider age, gender, designation, and specialty) was used to model the odds of prescribing an opioid at an encounter.
Results: There were 2,164 encounters where an opioid could have been prescribed by 37 dentists. There were 19.6 opioid prescriptions per 100 encounters in the control group, 3.2 opioids prescriptions per 100 encounters in the standard A&F group, and 3.02 opioid prescriptions per 100 encounters in the enhanced A&F group. The results of the logistic regression model showed that there was a statistically significant (p-value<0.05) intervention effect on the odds of opioid prescribing. The odds of prescribing an opioid were reduced by 72% (p-value=0.00013, 95%CI:0.16–0.55) in the standard A&F group vs the control group, and were reduced by 62% (p-value=0.0094, 95%CI:0.16–0.76) in the enhanced A&F group versus the control group.
Conclusions: A&F dashboards were effective in reducing opioid prescribing in a small sample of dentists through this RCT at one dental institution.
Methods: The randomized controlled trial (RCT) was implemented in one academic dental setting over a period of one year with 2 intervention groups and 1 control group of standard dental practice (40:40:20 randomization ratio). Dentists in the standard A&F intervention group received A&F dashboards about their own opioid prescribing compared with other similar dentists, and dentists in the enhanced A&F intervention group received standard A&F dashboards with additional information on their patients’ self-reported pain level 7-days after their procedures. Opioid prescriptions per 100 patient encounters were calculated and hierarchical logistic regression (adjusted for provider age, gender, designation, and specialty) was used to model the odds of prescribing an opioid at an encounter.
Results: There were 2,164 encounters where an opioid could have been prescribed by 37 dentists. There were 19.6 opioid prescriptions per 100 encounters in the control group, 3.2 opioids prescriptions per 100 encounters in the standard A&F group, and 3.02 opioid prescriptions per 100 encounters in the enhanced A&F group. The results of the logistic regression model showed that there was a statistically significant (p-value<0.05) intervention effect on the odds of opioid prescribing. The odds of prescribing an opioid were reduced by 72% (p-value=0.00013, 95%CI:0.16–0.55) in the standard A&F group vs the control group, and were reduced by 62% (p-value=0.0094, 95%CI:0.16–0.76) in the enhanced A&F group versus the control group.
Conclusions: A&F dashboards were effective in reducing opioid prescribing in a small sample of dentists through this RCT at one dental institution.