Margaret Lowenstein1,2,3, Erik Hossain4, Wei Yang5, David Grande6,7,8, Jeanmarie Perrone7,9, Mark D Neuman7,10, Michael Ashburn7,10, M Kit Delgado7,5,9. 1. National Clinician Scholars Program, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. margaw@pennmedicine.upenn.edu. 2. Department of Medicine, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA. margaw@pennmedicine.upenn.edu. 3. The Leonard Davis Institute of Health Economics, University of Pennsylvania, 1310 Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, USA. margaw@pennmedicine.upenn.edu. 4. Data Analytics Center, Penn Medicine, Philadelphia, PA, USA. 5. Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. 6. National Clinician Scholars Program, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. 7. The Leonard Davis Institute of Health Economics, University of Pennsylvania, 1310 Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, USA. 8. Division of General Internal Medicine, Perelman School of School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. 9. Center for Emergency Care Policy and Research, Department of Emergency Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. 10. Department of Anesthesia and Critical Care, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
Abstract
BACKGROUND: Prescribing limits are one policy strategy to reduce short-term opioid prescribing, but there is limited evidence of their impact. OBJECTIVE: Evaluate implementation of a state prescribing limit law and health system electronic medical record (EMR) alert on characteristics of new opioid prescriptions, refill rates, and clinical encounters. DESIGN: Difference-in-differences study comparing new opioid prescriptions from ambulatory practices in New Jersey (NJ) to controls in Pennsylvania (PA) from 1 year prior to the implementation of a NJ state prescribing limit (May 2016-May 2017) to 10 months after (May 2017-March 2018). PARTICIPANTS: Adults with new opioid prescriptions in an academic health system with practices in PA and NJ. INTERVENTIONS: State 5-day opioid prescribing limit plus health system and health system EMR alert. MAIN MEASURES: Changes in morphine milligram equivalents (MME) and tablet quantity per prescription, refills, and encounters, adjusted for patient and prescriber characteristics. KEY RESULTS: There were a total of 678 new prescriptions in NJ and 4638 in PA. Prior to the intervention, median MME/prescription was 225 mg in NJ and 150 mg in PA, and median quantity was 30 tablets in both. After implementation, median MME/prescription was 150 mg in both states, and median quantity was 20 in NJ and 30 in PA. In the adjusted model, there was a greater decrease in mean MME and tablet quantity in NJ relative to PA after implementation of the policy plus alert (- 82.99 MME/prescription, 95% CI - 148.15 to - 17.84 and - 10.41 tabs/prescription, 95% CI - 19.70 to - 1.13). There were no significant differences in rates of refills or encounters at 30 days based on exposure to the interventions. CONCLUSIONS: Implementation of a prescribing limit and EMR alert was associated with an approximately 22% greater decrease in opioid dose per new prescription in NJ compared with controls in PA. The combination of prescribing limits and alerts may be an effective strategy to influence prescriber behavior.
BACKGROUND: Prescribing limits are one policy strategy to reduce short-term opioid prescribing, but there is limited evidence of their impact. OBJECTIVE: Evaluate implementation of a state prescribing limit law and health system electronic medical record (EMR) alert on characteristics of new opioid prescriptions, refill rates, and clinical encounters. DESIGN: Difference-in-differences study comparing new opioid prescriptions from ambulatory practices in New Jersey (NJ) to controls in Pennsylvania (PA) from 1 year prior to the implementation of a NJ state prescribing limit (May 2016-May 2017) to 10 months after (May 2017-March 2018). PARTICIPANTS: Adults with new opioid prescriptions in an academic health system with practices in PA and NJ. INTERVENTIONS: State 5-day opioid prescribing limit plus health system and health system EMR alert. MAIN MEASURES: Changes in morphine milligram equivalents (MME) and tablet quantity per prescription, refills, and encounters, adjusted for patient and prescriber characteristics. KEY RESULTS: There were a total of 678 new prescriptions in NJ and 4638 in PA. Prior to the intervention, median MME/prescription was 225 mg in NJ and 150 mg in PA, and median quantity was 30 tablets in both. After implementation, median MME/prescription was 150 mg in both states, and median quantity was 20 in NJ and 30 in PA. In the adjusted model, there was a greater decrease in mean MME and tablet quantity in NJ relative to PA after implementation of the policy plus alert (- 82.99 MME/prescription, 95% CI - 148.15 to - 17.84 and - 10.41 tabs/prescription, 95% CI - 19.70 to - 1.13). There were no significant differences in rates of refills or encounters at 30 days based on exposure to the interventions. CONCLUSIONS: Implementation of a prescribing limit and EMR alert was associated with an approximately 22% greater decrease in opioid dose per new prescription in NJ compared with controls in PA. The combination of prescribing limits and alerts may be an effective strategy to influence prescriber behavior.
Entities:
Keywords:
addiction; health policy; health services research; opioid
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