Dataset Information

Exposure-Response Association Between Concurrent Opioid and Benzodiazepine Use and Risk of Opioid-Related Overdose in Medicare Part D Beneficiaries.

ABSTRACT:

Importance

Concurrent benzodiazepine use is associated with an increased risk of opioid-related overdose; however, it remains unknown how the overdose risk varies with the days of exposure to both medications.

Objective

To evaluate the exposure-response association between the days with concurrent prescription opioid and benzodiazepine use and the risk of overdose.

Design, setting, and participants

Retrospective cohort study of Medicare Part D claims data from January 1, 2013, to December 31, 2014. Analyses were conducted in fall 2017 and spring 2018. Participants were Medicare Part D beneficiaries who filled at least 1 prescription for an opioid in 2014.

Exposures

Patients were divided into 2 groups based on whether they had opioid and benzodiazepine supplies on the day before overdose or censoring. The first group only had a supply of opioids (n?=?50?583) and the second group had supplies of opioids and benzodiazepines (n?=?20?665). The second group was further categorized into 4 subgroups based on the cumulative number of days with overlapping supplies of opioids and benzodiazepines: 1 to 90 days (n?=?3603), 91 to 180 days (n?=?2930), 181 to 270 days (n?=?4082), and 271 days or more (n?=?10?050).

Main outcomes and measures

Cox proportional hazard models were constructed to compare opioid-related overdose (including fatal and nonfatal overdoses) across time-dependent treatment groups, controlling for demographic characteristics, insurance factors, clinical characteristics, and number of unique opioid and benzodiazepine prescribers.

Results

Of 71?248 total participants, 25?600 (35.9%) were male and 59?532 (83.6%) were white. Mean (SD) age was 66.5 (14.8) years. On the day before overdose or censoring event, 20?665 of 71?248 patients with an opioid prescription (29.0%) were concurrently using benzodiazepines and 14?132 of 20?665 concurrent users (68.4%) had more than 180 days of overlapping supplies of both medications. The risk of overdose was highest on the first days of concurrent opioid and benzodiazepine use and decreased over time; compared with opioid use alone, the hazard ratio for overdose was 5.05 (95% CI, 3.68-6.93) during the first 90 days of concurrent opioid and benzodiazepine use and 1.87 (95% CI, 1.25-2.80) for days 91 to 180 among those who did not have an event before 90 days.

Conclusions and relevance

During the first 90 days, concurrent benzodiazepine use is associated with a 5-fold increase in the risk of opioid-related overdose. The implementation of policies deterring concurrent opioid and benzodiazepine use is warranted. Patients using both medications should be closely monitored, particularly during the first days of concurrent use.

SUBMITTER: Hernandez I

PROVIDER: S-EPMC6324417 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Exposure-Response Association Between Concurrent Opioid and Benzodiazepine Use and Risk of Opioid-Related Overdose in Medicare Part D Beneficiaries.

Hernandez Inmaculada I He Meiqi M Brooks Maria M MM Zhang Yuting Y

JAMA network open 20180601 2

<h4>Importance</h4>Concurrent benzodiazepine use is associated with an increased risk of opioid-related overdose; however, it remains unknown how the overdose risk varies with the days of exposure to both medications.<h4>Objective</h4>To evaluate the exposure-response association between the days with concurrent prescription opioid and benzodiazepine use and the risk of overdose.<h4>Design, setting, and participants</h4>Retrospective cohort study of Medicare Part D claims data from January 1, 20 ...[more]

PMID: 30646080

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Project description:Importance:Benzodiazepines, which are associated with safety-related harms for older adults, were not covered when the US Medicare Part D prescription drug benefit began. Coverage was extended to benzodiazepines in 2013. Objective:To examine whether the expansion of benzodiazepine coverage among Medicare Advantage (MA) beneficiaries was associated with increases in fall-related injuries or overdoses among older adults. Design, Setting, and Participants:This ecological study used interrupted time-series with comparison-series analyses of MA claims data from 4?635?312 age-eligible MA beneficiaries and 940?629 commercially insured individuals (comparison group) stratified by age (65-69, 70-74, 75-79, and ?80 years) to separately compare trends in fall-related injury and overdose before (January 1, 2010, to December 31, 2012) and after (January 1, 2013, to December 31, 2015) coverage expansion for benzodiazepines. Data analysis was performed from September 1, 2018, to August 31, 2019. Exposures:Expansion of benzodiazepine coverage in Medicare Part D in 2013. Main Outcomes and Measures:Monthly rate of fall-related injury and overdose. Results:In 2012 (the year before the policy change), women constituted 57.5% of the MA group and 47.4% of the comparison group. A total of 25.8% of individuals in the MA group were aged 65 to 69 years, and 29.3% were 80 years or older (mean [SD], 75.1 [6.4] years); 56.7% of individuals in the comparison group were aged 65 to 69 years, and 15.1% were 80 years or older (mean [SD] age, 70.9 [6.5] years). In the MA group, 4?635?312 individuals contributed 156?754?749 person-months from 2010 through 2015; in the comparison group, 940?629 individuals contributed 25?104?534 person-months. After coverage of benzodiazepines began, the rate (ie, slope) of fall-related injury among MA beneficiaries increased from before to after coverage among all age groups. Compared with the comparison group, the increase in rate was statistically significant for those 80 years or older (rate changes for the MA vs comparison groups: 0.12 [95% CI, 0.07 to 0.17] vs -0.01 [95% CI, -0.11 to 0.10]; P?=?.04 for interaction). The overdose trend changed from decreasing to increasing among MA beneficiaries after coverage for all age groups, with a statistically significant increase compared with the comparison group among those aged 65 to 69 years (rate changes for the MA vs comparison groups: 0.23 [95% CI, 0.17 to 0.30] vs 0.02 [95% CI, -0.06 to 0.11]; P?<?.001 for interaction) and among those 80 years or older (rate changes for the MA vs comparison groups: 0.07 [95% CI, 0.00 to 0.14] vs -0.20 [95% CI, -0.35 to -0.05]; P?=?.002 for interaction). Results among MA beneficiaries were consistent when stratified by sex and when limited to those prescribed opioids. Conclusions and Relevance:Medicare's expansion of benzodiazepine coverage may have been associated with increases in the rates of overdose among adults ages 65 to 69 years and in the rates of overdose and fall-related injury among those 80 years or older.

Project description:ImportanceCurrent approaches to identifying individuals at high risk for opioid overdose target many patients who are not truly at high risk.ObjectiveTo develop and validate a machine-learning algorithm to predict opioid overdose risk among Medicare beneficiaries with at least 1 opioid prescription.Design, setting, and participantsA prognostic study was conducted between September 1, 2017, and December 31, 2018. Participants (n = 560 057) included fee-for-service Medicare beneficiaries without cancer who filled 1 or more opioid prescriptions from January 1, 2011, to December 31, 2015. Beneficiaries were randomly and equally divided into training, testing, and validation samples.ExposuresPotential predictors (n = 268), including sociodemographics, health status, patterns of opioid use, and practitioner-level and regional-level factors, were measured in 3-month windows, starting 3 months before initiating opioids until loss of follow-up or the end of observation.Main outcomes and measuresOpioid overdose episodes from inpatient and emergency department claims were identified. Multivariate logistic regression (MLR), least absolute shrinkage and selection operator-type regression (LASSO), random forest (RF), gradient boosting machine (GBM), and deep neural network (DNN) were applied to predict overdose risk in the subsequent 3 months after initiation of treatment with prescription opioids. Prediction performance was assessed using the C statistic and other metrics (eg, sensitivity, specificity, and number needed to evaluate [NNE] to identify one overdose). The Youden index was used to identify the optimized threshold of predicted score that balanced sensitivity and specificity.ResultsBeneficiaries in the training (n = 186 686), testing (n = 186 685), and validation (n = 186 686) samples had similar characteristics (mean [SD] age of 68.0 [14.5] years, and approximately 63% were female, 82% were white, 35% had disabilities, 41% were dual eligible, and 0.60% had at least 1 overdose episode). In the validation sample, the DNN (C statistic = 0.91; 95% CI, 0.88-0.93) and GBM (C statistic = 0.90; 95% CI, 0.87-0.94) algorithms outperformed the LASSO (C statistic = 0.84; 95% CI, 0.80-0.89), RF (C statistic = 0.80; 95% CI, 0.75-0.84), and MLR (C statistic = 0.75; 95% CI, 0.69-0.80) methods for predicting opioid overdose. At the optimized sensitivity and specificity, DNN had a sensitivity of 92.3%, specificity of 75.7%, NNE of 542, positive predictive value of 0.18%, and negative predictive value of 99.9%. The DNN classified patients into low-risk (76.2% [142 180] of the cohort), medium-risk (18.6% [34 579] of the cohort), and high-risk (5.2% [9747] of the cohort) subgroups, with only 1 in 10 000 in the low-risk subgroup having an overdose episode. More than 90% of overdose episodes occurred in the high-risk and medium-risk subgroups, although positive predictive values were low, given the rare overdose outcome.Conclusions and relevanceMachine-learning algorithms appear to perform well for risk prediction and stratification of opioid overdose, especially in identifying low-risk subgroups that have minimal risk of overdose.

Project description:ImportanceIn response to the opioid epidemic, policies aiming to reduce opioid prescribing, misuse, and abuse may have the unintended consequence of restricting access to necessary opioid therapy for cancer-related pain. It is unknown how opioid prescribing patterns have changed among generalists and oncologists during this era.ObjectiveTo examine trends in opioid prescription rates for Medicare Part D beneficiaries from 2013 to 2017 among oncologists and generalists.Design, setting, and participantsThis repeated cross-sectional study of generalist physicians (internal medicine, family medicine, geriatric medicine, general practice) and oncology specialists (medical oncology, hematology-oncology, and radiation oncology) analyzed the Medicare Provider Utilization and Payment Data: Part D prescriber files from 2013 to 2017.ExposuresGeneralist vs oncology specialty.Main outcomes and measuresOutcomes included physician-level rates of both opioid and long-acting opioid prescriptions per 100 Medicare Part D beneficiaries. Poisson regression was used to estimate annual predicted outcome rates and incidence rate ratios, adjusting for prescriber characteristics and state fixed effects.ResultsWe analyzed the prescribing patterns of 251 820 generalists and 14 210 oncologists. From 2013 to 2017, the annual adjusted predicted mean rate of opioid prescriptions per 100 Medicare beneficiaries decreased from 68.2 to 49.7 among generalists (adjusted incidence rate ratio [aIRR] = 0.73; 95% CI, 0.73-0.73) and from 77.8 to 58.8 among oncologists (aIRR = 0.76; 95% CI, 0.74-0.77). The rate of long-acting opioid prescriptions per 100 Medicare beneficiaries also decreased from 8.0 to 5.4 for generalists (aIRR = 0.67; 95% CI, 0.66-0.68) and from 18.6 to 13.3 for oncologists (aIRR = 0.72; 95% CI, 0.69-0.74).Conclusions and relevanceWe found large declines in opioid prescription rates for Medicare beneficiaries by generalists and oncologists from 2013 to 2017. Opioid policy and advocacy appear to have been effective in reducing the extent of opioid prescribing in the Medicare population. Similar declines between generalists and oncologists raise concern that access to cancer pain management may have been inadvertently restricted. How much of the decrease in prescribing by oncologists is appropriate vs inappropriate deserves further investigation.

Project description:ObjectivesLittle is known about relationships between opioid- and gabapentinoid-use patterns and healthcare expenditures that may be affected by pain management and risk of adverse outcomes. This study examined the association between patients' opioid and gabapentinoid prescription filling/refilling trajectories and direct medical expenditures in US Medicare.MethodsThis cross-sectional study included a 5% national sample (2011-2016) of fee-for-service beneficiaries with fibromyalgia, low back pain, neuropathy, or osteoarthritis newly initiating opioids or gabapentinoids. Using group-based multitrajectory modeling, this study identified patients' distinct opioid and gabapentinoid (OPI-GABA) dose and duration patterns, based on standardized daily doses, within a year of initiating opioids and/or gabapentinoids. Concurrent direct medical expenditures within the same year were estimated using inverse probability of treatment weighted multivariable generalized linear regression, adjusting for sociodemographic and health status factors.ResultsAmong 67 827 eligible beneficiaries (mean age ± SD = 63.6 ± 14.8 years, female = 65.8%, white = 77.1%), 11 distinct trajectories were identified (3 opioid-only, 4 gabapentinoid-only, and 4 concurrent OPI-GABA trajectories). Compared with opioid-only early discontinuers ($13 830, 95% confidence interval = $13 643-14 019), gabapentinoid-only early discontinuers and consistent low-dose and moderate-dose gabapentinoid-only users were associated with 11% to 23% lower health expenditures (adjusted mean expenditure = $10 607-$11 713). Consistent low-dose opioid-only users, consistent high-dose opioid-only users, consistent low-dose OPI-GABA users, consistent low-dose opioid and high-dose gabapentinoid users, and consistent high-dose opioid and moderate-dose gabapentinoid users were associated with 14% to 106% higher healthcare expenditures (adjusted mean expenditure = $15 721-$28 464).ConclusionsDose and duration patterns of concurrent OPI-GABA varied substantially among fee-for-service Medicare beneficiaries. Consistent opioid-only users and all concurrent OPI-GABA users were associated with higher healthcare expenditures compared to opioid-only discontinuers.

Dataset Information

Exposure-Response Association Between Concurrent Opioid and Benzodiazepine Use and Risk of Opioid-Related Overdose in Medicare Part D Beneficiaries.

Importance

Objective

Design, setting, and participants

Exposures

Main outcomes and measures

Results

Conclusions and relevance

Publications

Exposure-Response Association Between Concurrent Opioid and Benzodiazepine Use and Risk of Opioid-Related Overdose in Medicare Part D Beneficiaries.

Similar Datasets

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