Sudha R Raman1, Christopher Bush2, Ruchir N Karmali3, Lawrence H Greenblatt4, Andrew W Roberts5, Asheley C Skinner1. 1. Department of Population Health Sciences, Duke University School of Medicine, and Duke Clinical Research Institute, Duke University, Durham, North Carolina. 2. Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina. 3. Department of Population Health Sciences, Duke University School of Medicine and Duke Clinical Research Institute, Duke University, Durham, North Carolina, and Division of Research, Kaiser Permanente Northern California, Oakland. 4. Department of Medicine and Department of Community and Family Medicine, Duke University School of Medicine, Durham, North Carolina. 5. Department of Population Health and Department of Anesthesiology, University of Kansas Medical Center, Kansas City.
Abstract
BACKGROUND: Opioid prescription patterns, including long-term use, multiple prescribers, and high opioid doses, increase the risk for adverse outcomes; however, previous research in older adult populations has primarily described opioid dose patterns using average daily dose measures or using very high thresholds (i.e., > 100 morphine milligram equivalents [MME] per day). OBJECTIVE: To describe prescription patterns by peak dose among older adults who have newly initiated opioid use in 2014 and describe long-term opioid use and the use of multiple pharmacies and prescribers among those with peak opioid doses over 50 and over 90 MME per day. METHODS: This was a retrospective cohort study of Medicare Part D prescription claims data (5% sample) for beneficiaries aged 65 years and older who were prescribed ≥ 1 opioid prescription in 2014 and did not have an opioid prescription in the preceding 180 days. Within a 1-year period of follow-up, we used prescription claims to characterize individuals' opioid exposure, measuring long-term opioid use (≥ 90 days of continuous opioid supply), unique opioid prescribers, and unique opioid-dispensing pharmacies. Peak MME was defined as the maximum daily MME received across all overlapping opioid prescriptions in the observation period. RESULTS: 144,127 beneficiaries without an opioid prescription in the previous 6 months filled ≥ 1 opioid prescription in 2014. During the 1-year follow-up period, 6.5% of beneficiaries transitioned to long-term opioid use; 39.5% received opioid prescriptions from > 1 prescriber; 18.1% filled opioid prescriptions from > 1 pharmacy; and 21.8% had a peak MME of 50-89. Among the 28.1% of beneficiaries exposed to a peak MME > 50, 8.6% developed long-term opioid use; 7.0% had 3 or more opioid dispensing pharmacies; and 28.0% had 3 or more opioid prescribers. Among the 6.2% of beneficiaries exposed to a peak MME ≥ 90, 18.5% developed long-term opioid use; 13.0% had 3 or more opioid dispensing pharmacies; and 39.6% had 3 or more opioid prescribers. CONCLUSIONS: High doses of opioids were prescribed for about one quarter (28%) of Medicare beneficiaries with new opioid use in 2014. Having multiple opioid prescribers or multiple opioid dispensing pharmacies was common, especially among those prescribed higher doses. These prescription patterns can be particularly helpful to identify older adults with increased opioid-related risk. DISCLOSURES: No funding supported this study. Raman reports research grants from GlaxoSmithKline not related to this study. Roberts was supported by a CTSA grant from NCATS awarded to the University of Kansas Medical Center for Frontiers: The Heartland Institute for Clinical and Translational Research (#KL2TR000119). The other authors have no potential conflicts to report.
BACKGROUND: Opioid prescription patterns, including long-term use, multiple prescribers, and high opioid doses, increase the risk for adverse outcomes; however, previous research in older adult populations has primarily described opioid dose patterns using average daily dose measures or using very high thresholds (i.e., > 100 morphine milligram equivalents [MME] per day). OBJECTIVE: To describe prescription patterns by peak dose among older adults who have newly initiated opioid use in 2014 and describe long-term opioid use and the use of multiple pharmacies and prescribers among those with peak opioid doses over 50 and over 90 MME per day. METHODS: This was a retrospective cohort study of Medicare Part D prescription claims data (5% sample) for beneficiaries aged 65 years and older who were prescribed ≥ 1 opioid prescription in 2014 and did not have an opioid prescription in the preceding 180 days. Within a 1-year period of follow-up, we used prescription claims to characterize individuals' opioid exposure, measuring long-term opioid use (≥ 90 days of continuous opioid supply), unique opioid prescribers, and unique opioid-dispensing pharmacies. Peak MME was defined as the maximum daily MME received across all overlapping opioid prescriptions in the observation period. RESULTS: 144,127 beneficiaries without an opioid prescription in the previous 6 months filled ≥ 1 opioid prescription in 2014. During the 1-year follow-up period, 6.5% of beneficiaries transitioned to long-term opioid use; 39.5% received opioid prescriptions from > 1 prescriber; 18.1% filled opioid prescriptions from > 1 pharmacy; and 21.8% had a peak MME of 50-89. Among the 28.1% of beneficiaries exposed to a peak MME > 50, 8.6% developed long-term opioid use; 7.0% had 3 or more opioid dispensing pharmacies; and 28.0% had 3 or more opioid prescribers. Among the 6.2% of beneficiaries exposed to a peak MME ≥ 90, 18.5% developed long-term opioid use; 13.0% had 3 or more opioid dispensing pharmacies; and 39.6% had 3 or more opioid prescribers. CONCLUSIONS: High doses of opioids were prescribed for about one quarter (28%) of Medicare beneficiaries with new opioid use in 2014. Having multiple opioid prescribers or multiple opioid dispensing pharmacies was common, especially among those prescribed higher doses. These prescription patterns can be particularly helpful to identify older adults with increased opioid-related risk. DISCLOSURES: No funding supported this study. Raman reports research grants from GlaxoSmithKline not related to this study. Roberts was supported by a CTSA grant from NCATS awarded to the University of Kansas Medical Center for Frontiers: The Heartland Institute for Clinical and Translational Research (#KL2TR000119). The other authors have no potential conflicts to report.
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