Quantification of missing prescriptions in commercial claims databases: results of a cohort study.

PURPOSE: This study aims to quantify the magnitude of missed dispensings in commercial claims databases. METHODS: A retrospective cohort study has been used linking PharMetrics, a commercial claims database, to a prescription database (LRx) that captures pharmacy dispensings independently of payment method, including cash transactions. We included adults with dispensings for opioids, diuretics, antiplatelet medications, or anticoagulants. To determine the degree of capture of dispensings, we calculated the number of subjects with the following: (1) same number of dispensings in both databases; (2) at least one dispensing, but not all dispensings, missed in PharMetrics; and (3) all dispensings missing in PharMetrics. Similar analyses were conducted using dispensings as the unit of analysis. To assess whether a dispensing in LRx was in PharMetrics, the dispensing in PharMetrics had to be for the same medication class and within ±7 days in LRx. RESULTS: A total of 1 426 498 subjects were included. Overall, 68% of subjects had the same number of dispensings in both databases. In 13% of subjects, PharMetrics identified ≥1 dispensing but also missed ≥1 dispensing. In 19% of the subjects, PharMetrics missed all the dispensings. Taking dispensings as the unit of analysis, 25% of the dispensings present in LRx were not captured in PharMetrics. These patterns were similar across all four classes of medications. Of the dispensings missing in PharMetrics, 48% involved a subject who had >1 health insurance plan. CONCLUSIONS: Commercial claims databases provide an incomplete picture of all prescriptions dispensed to patients. The lack of capture goes beyond cash transactions and potentially introduces substantial misclassification bias. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Effect of Opioids on Testosterone Levels: Cross-Sectional Study using NHANES.

OBJECTIVE: Opioids can suppress gonadal hormone production, which may result in low testosterone levels. To date, there have been no large-scale population-based studies examining the extent to which opioid use may contribute to changes in testosterone levels. DESIGN: Cross-sectional study. SETTING: 2011-2012 National Health and Nutrition Examination Survey. SUBJECTS: Participants 17 years and older who had data on prescription medication usage and serum testosterone levels available. Participants were divided in two groups, opioid exposed and unexposed. METHODS: Testosterone levels of participants who responded that they had been exposed (n = 320) to prescription opioids in the past 30 days were compared with those who were unexposed (n = 4909). The number of participants with low testosterone levels was calculated and unadjusted and adjusted analyses were performed. RESULTS: Participants on opioids had higher odds of having low testosterone levels than those unexposed, odd ratio (OR) = 1.40, 95% confidence interval (CI) (1.07-1.84). After controlling for opioid exposure, as the age and the number of comorbidities increased, the odds of having low testosterone levels significantly increased in all categories. Compared with participants between 17 and 45 years of age, participants >70 years had OR = 1.70, 95% CI (1.16-2.50). Compared with participants with no comorbidities, participants with >2 comorbidities had OR = 1.69 95% CI (1.24-2.30). CONCLUSION: When assessing the impact of opioids on testosterone, the effects of age and medical conditions should be considered.

Dose patterns in commercially insured subjects chronically exposed to opioids: a large cohort study in the United States.

BACKGROUND: Little data exist on how opioid doses vary with the length of exposure among chronic opioid users. METHODS: To characterize the change in the dosage of opioids over time, a retrospective cohort study using the PharMetrics database for the years 1999 through 2008 was conducted. Individuals exposed to opioids in 2000 who had 2 opioid dispensings at least 6 months apart and were opioid naive (did not receive any opioid 6 month before their exposure in 2000) were included. The date of the first dispensing in 2000 was defined as the index date and the dispensing had to be for a strong and full agonist opioid. All opioid doses were converted to oral morphine equivalent doses. Exposure was classified as continuous or intermittent. Mean, median, interquartile range, and 95th percentile of opioid dose over 6-month periods, as well as the percentage of subjects who ever received a high or very high opioid dose, were calculated. RESULTS: Among the 48,986 subjects, the mean age was 44.5 years and 54.5% were women. Intermittent exposure was observed in 99% of subjects; continuous exposure was observed in 1% of subjects. The mean duration of exposure for the subjects who were continuously exposed to opioids was 477 days. In subjects with no cancer diagnosis who were continuously exposed to opioids, the mean, 25th, 50th, and 75th percentile of dose was stable during the first 2 years of use, but the 95th percentile increased. Seven percent of them were exposed to doses of 180 mg or more of morphine at some point. CONCLUSIONS: Dose escalation is uncommon in subjects with intermittent exposure to opioids. For subjects with continuous exposure to opioids who have cancer, doses rise substantially with time. For those without cancer, doses remain relatively stable for the first 2 years of use, but subsequently increase. Seven percent of subjects with no cancer diagnosis will be exposed to daily doses of 180 mg or more of morphine equivalent at some point.

Comparison of morphine, ketorolac, and their combination for postoperative pain: results from a large, randomized, double-blind trial.

BACKGROUND: Meta-analyses report similar numbers needed to treat for nonsteroidal antiinflammatory drugs (NSAIDs) and opioids. Differences in baseline pain intensity among the studies from which these numbers needed to treat were derived may have confounded the results. NSAIDs have an opioid-sparing effect, but the importance of this effect is unclear. Therefore, the authors sought to compare the proportions of subjects who obtain pain relief with ketorolac versus morphine after surgery and to determine whether the opioid-sparing effect of an NSAID reduces the magnitude of opioid side effects. METHODS: The study was a double-blind, randomized controlled trial. The authors randomly assigned 1,003 adult patients to receive 30 mg ketorolac or 0.1 mg/kg morphine intravenously. They calculated the proportion of subjects who achieved at least 50% reduction in pain intensity 30 min after analgesic administration. Further, so long as pain intensity 30 min after analgesic administration was 5 or more out of 10, patients received 2.5 mg morphine every 10 min until pain intensity was 4 or less out of 10. The authors assessed the presence of opioid-related side effects. RESULTS: Five hundred patients received morphine and 503 received ketorolac. Fifty percent of patients in the morphine group achieved pain relief, compared with 31% in the ketorolac group (difference, 19%; 95% confidence interval, 13-25%). The ketorolac-morphine group required less morphine (difference, 6.5 mg; 95% confidence interval, -5.8 to -7.2) and had a lower incidence of side effects (difference, 11%; 95% confidence interval, 5-16%) than the morphine group. CONCLUSIONS: Opioids are more efficacious analgesics than NSAIDs, although historic data for these two drugs yield similar numbers needed to treat. Adding NSAIDs to the opioid treatment reduces morphine requirements and opioid-related side effects in the early postoperative period.