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Opioid Dependence Subsequent to Exposure to Prescription Opioids
Author(s) -
Shah S.,
Okunev I.,
Tranby E.,
FrantsveHawley J.,
Monopoli M.,
Shaya F.
Publication year - 2020
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/1475-6773.13521
Subject(s) - medicine , medicaid , medical prescription , opioid , odds ratio , population , medicare part d , cohort study , logistic regression , opioid use disorder , prescription drug , health care , pharmacology , environmental health , receptor , economic growth , economics
To determine whether the length, dose, and/or frequency of opioid prescriptions correlates with the subsequent diagnosis of opioid use disorder (OUD) among Medicaid enrollees and if there are higher odds of developing opioid dependence after receiving opioid prescriptions for dental procedures versus medical procedures. Our design was a nested case‐control in a cohort of continuously enrolled, opioid‐naïve (no opioid prescription for 1 year before the first prescription of opioid) Medicaid enrollees with at least one opioid prescription between January 1, 2013, and December 31, 2017, in IBM Watson Health’s MarketScan Medicaid database. The cases were defined as enrollees with diagnosed opioid use disorder, and controls were drawn from the same population who were not diagnosed with OUD. They were matched (up to 1:2) by age, sex, race, baseline pain diagnosis, number of Elixhauser comorbidities, and similar exposure time for prescription opioids. Outcome variable was the diagnosis of OUD, and the predictor variables were cumulative length of opioid prescriptions, morphine milligram equivalent (MME) dose, and frequency of opioids. The correlation was explored through multivariate logistic regression, and the model was re‐adjusted for baseline matching characteristics. The study population is opioid‐naïve Medicaid enrollees with at least one opioid prescription between January 1, 2013, and December 31, 2017, in IBM Watson Health’s MarketScan Medicaid database. Among a matched cohort of 1051 cases and 2053 controls, odds of OUD increased significantly for prescription count of 2‐3 (OR = 1.3, CI = 1.1‐1.6), 4‐5 days (OR = 2.0, CI = 1.4‐2.8), and above 6 (OR = 5.1, CI = 3.3‐7.8), compared to one prescription. Odds of OUD increased significantly for cumulative prescription length of 31‐60 days (OR = 1.8, CI = 1.3‐2.3), 61‐90 days (OR = 2.9, CI = 1.5‐5.6), and above 91 days (OR = 10.1, CI = 5.0‐20.4), compared to 5 days or less. Odds of OUD for average prescription length of 16‐30 days (OR = 1.9, CI = 1.3‐2.5) were significantly more compared to 5 days or less. Odds of OUD increased significantly for cumulative MME dose of 120‐180 (OR = 1.7, CI = 1.2‐2.3), and for 180 and above (OR = 4.1, CI = 2.8‐5.8), compared less than or equal to 20. Odds of OUD for average MME dose of 91 and above (OR = 1.9, CI = 1.2‐3.0) were significantly more compared less than or equal to 20. Moreover, enrollees who received opioid prescription for dental procedure were less likely (OR = 0.5, CI = 0.4‐0.7) to develop OUD then who received prescriptions for medical procedures. The study concluded that when number of prescriptions, days supplied, and morphine milligram equivalent dose go up, the odds of developing OUD increases significantly. Therefore a quantitative association between prescription opioid exposure and subsequent dependence in established. Moreover, the odds of developing OUD are less for prescriptions received after dental procedures compared to medical procedures. The study informs the opioid prescribing and opioid‐prescribing guidelines for clinical practice. DentaQuest Partnership for Oral Health Advancement.