Yuhua Bao1, Hao Zhang2, Katherine Wen3, Phyllis Johnson2, Philip J Jeng2, Lisa R Witkin4, Sean Nicholson3, M Carrington Reid5, Bruce R Schackman6. 1. Department of Population Health Sciences, Weill Cornell Medicine, New York, New York; Department of Psychiatry, Weill Cornell Medicine, New York, New York. Electronic address: yub2003@med.cornell.edu. 2. Department of Population Health Sciences, Weill Cornell Medicine, New York, New York. 3. Department of Policy Analysis and Management, College of Human Ecology, Cornell University, Ithaca, New York. 4. Department of Anesthesiology, Weill Cornell Medicine, New York, New York; Division of Pain Medicine, NewYork-Presbyterian Lower Manhattan Hospital, NewYork-Presbyterian, New York, New York. 5. Department of Medicine, Weill Cornell Medicine, New York, New York. 6. Department of Population Health Sciences, Weill Cornell Medicine, New York, New York; Department of Psychiatry, Weill Cornell Medicine, New York, New York; Department of Medicine, Weill Cornell Medicine, New York, New York.
Abstract
INTRODUCTION: This study assesses the associations between the recent implementation of robust features of state Prescription Drug Monitoring Programs and the abrupt discontinuation of long-term opioid therapies. METHODS: Data were from a national commercial insurance database and included privately insured adults aged 18-64 years and Medicare Advantage enrollees aged ≥65 years who initiated a long-term opioid therapy episode between Quarter 2 of 2011 and Quarter 2 of 2017. State Prescription Drug Monitoring Programs were characterized as nonrobust, robust, and strongly robust. Abrupt discontinuation was measured on the basis of high daily morphine milligram equivalents over the last 30 days of a long-term opioid therapy episode or no sign of tapering before discontinuation. Difference-in-differences models were estimated in 2019‒2020 to assess the association between robust Prescription Drug Monitoring Programs and abrupt discontinuation. RESULTS: Among nonelderly privately insured adults, robust Prescription Drug Monitoring Programs were associated with an increase from 14.8% to 15.4% (4% relative increase, p=0.02) in the rate of ending long-term opioid therapy with ≥60 daily morphine milligram equivalents. For older Medicare Advantage enrollees, strongly robust Prescription Drug Monitoring Programs were associated with a reduction from 4.8% to 4.3% (10.4%, p=0.01) and from 3.0% to 2.4% (17.3%, p=0.001) in the rate of ending long-term opioid therapy with ≥90 and 120 daily morphine milligram equivalents, respectively. Prescription Drug Monitoring Programs robustness was not associated with clinically meaningful changes in the rate of discontinuing long-term opioid therapy without tapering. CONCLUSIONS: Discontinuation without tapering was the norm for long-term opioid therapies in the samples throughout the study years. Findings do not support the notion that policies aimed at enhancing Prescription Drug Monitoring Program use were associated with substantial increases in abrupt long-term opioid therapy discontinuation.
INTRODUCTION: This study assesses the associations between the recent implementation of robust features of state Prescription Drug Monitoring Programs and the abrupt discontinuation of long-term opioid therapies. METHODS: Data were from a national commercial insurance database and included privately insured adults aged 18-64 years and Medicare Advantage enrollees aged ≥65 years who initiated a long-term opioid therapy episode between Quarter 2 of 2011 and Quarter 2 of 2017. State Prescription Drug Monitoring Programs were characterized as nonrobust, robust, and strongly robust. Abrupt discontinuation was measured on the basis of high daily morphine milligram equivalents over the last 30 days of a long-term opioid therapy episode or no sign of tapering before discontinuation. Difference-in-differences models were estimated in 2019‒2020 to assess the association between robust Prescription Drug Monitoring Programs and abrupt discontinuation. RESULTS: Among nonelderly privately insured adults, robust Prescription Drug Monitoring Programs were associated with an increase from 14.8% to 15.4% (4% relative increase, p=0.02) in the rate of ending long-term opioid therapy with ≥60 daily morphine milligram equivalents. For older Medicare Advantage enrollees, strongly robust Prescription Drug Monitoring Programs were associated with a reduction from 4.8% to 4.3% (10.4%, p=0.01) and from 3.0% to 2.4% (17.3%, p=0.001) in the rate of ending long-term opioid therapy with ≥90 and 120 daily morphine milligram equivalents, respectively. Prescription Drug Monitoring Programs robustness was not associated with clinically meaningful changes in the rate of discontinuing long-term opioid therapy without tapering. CONCLUSIONS: Discontinuation without tapering was the norm for long-term opioid therapies in the samples throughout the study years. Findings do not support the notion that policies aimed at enhancing Prescription Drug Monitoring Program use were associated with substantial increases in abrupt long-term opioid therapy discontinuation.
Authors: Yuhua Bao; Katherine Wen; Phyllis Johnson; Philip J Jeng; Zachary F Meisel; Bruce R Schackman Journal: Health Aff (Millwood) Date: 2018-10 Impact factor: 6.301
Authors: Rebecca L Haffajee; Michelle M Mello; Fang Zhang; Alan M Zaslavsky; Marc R Larochelle; J Frank Wharam Journal: Health Aff (Millwood) Date: 2018-06 Impact factor: 6.301
Authors: Nathan Smith; Silvia S Martins; June Kim; Ariadne Rivera-Aguirre; David S Fink; Alvaro Castillo-Carniglia; Stephen G Henry; Stephen J Mooney; Brandon D L Marshall; Corey Davis; Magdalena Cerdá Journal: Addiction Date: 2018-10-22 Impact factor: 6.526
Authors: Gery P Guy; Kun Zhang; Michele K Bohm; Jan Losby; Brian Lewis; Randall Young; Louise B Murphy; Deborah Dowell Journal: MMWR Morb Mortal Wkly Rep Date: 2017-07-07 Impact factor: 17.586
Authors: Yongkang Zhang; Phyllis Johnson; Philip J Jeng; M Carrington Reid; Lisa R Witkin; Bruce R Schackman; Jessica S Ancker; Yuhua Bao Journal: J Gen Intern Med Date: 2018-09-11 Impact factor: 6.473