This cross-sectional study uses deidentified patient information from Optum’s deidentified Integrated Claims-Clinical data set to compare frequency of opioid prescriptions for patients at risk for opioid misuse in the 18-month periods before and after publication of the Centers for Disease Control and Prevention (CDC) opioid prescribing guideline.
Key Points
Question
Have prescriptions for Schedule II opioids with high abuse potential, vs Schedule IV tramadol (lower abuse potential), decreased in the 18-month periods before and after publication of the Centers for Disease Control and Prevention opioid prescribing guideline?
Findings
In this cross-sectional study of 279 435 patients with usable data, the odds of prescriptions for Schedule II opioids were similar before and after publication of the guideline with few exceptions.
Meaning
This study’s findings suggest that, among patients at risk for opioid misuse, the odds of receiving a Schedule II opioid for noncancer pain vs tramadol in the 18-month periods before and after guideline publication were similar to the odds for those not at risk.
Abstract
Importance
It is not known whether decreases in Schedule II (high abuse potential) vs Schedule IV (lower abuse potential) opioid prescriptions overall and among high-risk patients followed publication of the Centers for Disease Control and Prevention (CDC) opioid prescribing guideline on March 15, 2016.
Objectives
To compare the odds of new Schedule II opioid (codeine, hydrocodone, oxycodone) prescriptions vs Schedule IV opioid (tramadol) prescriptions in the 18-month periods before and after the CDC guideline release to determine whether new prescriptions for Schedule II opioids decreased relative to new prescriptions for tramadol and to assess whether patients with benzodiazepine prescriptions or those with depression, anxiety, or substance use disorders had a greater decrease in receipt of Schedule II vs Schedule IV opioids.
Design, Setting, and Participants
Cross-sectional study of Optum’s deidentified Integrated Claims-Clinical data set for 5 million US adults 18 months before and 18 months after March 15, 2016. Eligible patients were 18 years or older, free of HIV and cancer diagnoses, and had a noncancer painful condition. Patients received new prescriptions for codeine, hydrocodone, oxycodone, or tramadol. Data were analyzed from September 5, 2014, to September 14, 2017.
Exposure
The CDC opioid prescribing guideline published on March 15, 2016.
Main Outcomes and Measures
The odds of prescriptions for each Schedule II opioid vs tramadol after guideline publication.
Results
Data from 279 435 patients were included in the study. The mean (SD) age of patients was 52.9 (16.5) years; 61% were female and 79.4% were White. The prevalence of new prescriptions for each drug before and after guideline publication was as follows: codeine, 7.1% vs 7.0%; hydrocodone, 47.4% vs 45.6%; oxycodone, 22.4% vs 24.0%; and tramadol, 23.0% vs 23.4%. Overall, the odds of being prescribed hydrocodone or oxycodone vs tramadol significantly decreased after guideline publication (odds ratios, 0.95; 95% CI, 0.91-0.98 and 0.86; 95% CI, 0.82-0.90, respectively). Odds of being prescribed a Schedule II opioid vs tramadol after vs before guideline publication were similar in patients with and without benzodiazepine comedication or psychiatric disorders.
Conclusions and Relevance
In the 18 months after compared with the 18 months before publication of the CDC prescribing guideline, a 14% decrease in oxycodone prescriptions was observed relative to tramadol. Little change in prescriptions of other Schedule II opioids was observed. Schedule II opioids continue to be prescribed to high-risk patients 18 months after publication of the CDC guideline.
Introduction
The release of the Centers for Disease Control and Prevention (CDC) Guideline for Prescribing Opioids for Chronic Pain1 in March 2016 offered recommendations for opioid therapy in primary care patients with noncancer pain. The guideline’s publication was followed by accelerated declines in opioid prescribing rates, high-dose prescribing, and benzodiazepine coprescribing.2,3,4 Research on the effect of the guidelines has yet to assess whether the type of opioid prescribed has changed. In addition, no findings that indicate whether patients with psychiatric disorders who are at risk for opioid misuse5,6 are less likely to receive opioids with high abuse potential after guideline publication are available. We limited analysis to codeine, hydrocodone, oxycodone, and tramadol because they are the opioids most frequently dispensed in the United States.7,8,9,10 These opioids were also selected because tramadol, a Schedule IV drug, has been associated with fewer adverse events than hydrocodone and oxycodone10 and has a lower abuse potential than Schedule II drugs (eg, codeine, hydrocodone, and oxycodone).11
Although the CDC guidelines do not include advice on prescribing specific opioids, we expected the declines in dose, duration, and benzodiazepine coprescribing to be accompanied by increased use of tramadol relative to Schedule II opioids. We compared the odds of new Schedule II opioid (codeine, hydrocodone, oxycodone) prescriptions with the odds of Schedule IV opioid (tramadol) prescriptions for 18 months before and 18 months after release of the CDC guideline to assess whether (1) new Schedule II prescriptions decreased more than Schedule IV prescriptions, (2) benzodiazepine coprescriptions were associated with a greater decrease in Schedule II vs Schedule IV opioid prescriptions, and (3) high-risk patients who had depression, anxiety, or substance use disorders had a greater decrease in receipt of Schedule II vs Schedule IV opioids.
Methods
We used Optum’s deidentified Integrated Claims-Clinical data set (2010-2018) for 5 million patients (≥18 years) throughout the United States. We used this database because it contains more data on patient characteristics than medical claims data and includes information on outpatient and inpatient encounters, academic and nonacademic health care systems, and commercially insured, government insured, and uninsured patients. The study outcome was opioid prescribing measured 18 months before and 18 months after the study exposure: CDC guideline publication on March 15, 2016.1 Because data were deidentified, this study was considered to be non–human subjects research by the Saint Louis University Institutional Review Board and therefore deemed exempt from the need for institutional review board approval or patient informed consent. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies.
Data were included if patients had a noncancer pain diagnosis, were free of cancer and HIV, and had been enrolled in the database in the 6-month period prior to a new Schedule IV or II opioid prescription. Data on patients who received new prescriptions for codeine, hydrocodone, oxycodone, a combination medication (eg, hydrocodone-acetaminophen), or tramadol were also included. A new prescription was defined as one that followed a period of 6 months or more without a prescription for any opioid, including methadone. Patients could enter the study anytime they met eligibility criteria. If any demographic variable for a patient was missing, data for that patient were excluded. Data for 70 patients in the 18-month period before guideline publication and 74 patients in the 18-month period after guideline publication were excluded because patients were not identified as male or female. The cohort creation is shown in the eFigure in the Supplement. The total number of patients with usable data was 279 435 (141 219 before and 138 216 after guideline publication).
Detailed definitions for all variables are provided in the eTable in the Supplement. Risk factors for opioid misuse were defined using International Classification of Diseases, Ninth Revision, and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, coding algorithms for depression, anxiety disorders, alcohol and drug abuse or dependence, and nicotine dependence. Benzodiazepine coprescription was measured any time in the period before or after guideline publication.
Covariates included age, sex, race and ethnicity, clinician type at time of new opioid prescription, patient’s census geographic region, obesity, and painful conditions. We adjusted for chronological time at occurrence of a new opioid prescription. This was expressed as months since September 14, 2014 (first possible new opioid prescription date). Diagnostic codes for more than 900 conditions for which an opioid may be prescribed12 were used to categorize painful conditions such as arthritis, musculoskeletal pain, back pain, neuropathic pain, and headache pain.13 Covariates for the cohort before guideline publication were measured from September 14, 2014, to March 14, 2016, and covariates for the cohort after guideline publication were measured from March 15, 2016, to September 15, 2017.
Statistical Analysis
The data analysis was performed from May to July 2020. Crude, bivariate associations of opioid type and covariates were compared for the 18-month periods before and after guideline publication using χ2 tests and independent samples t tests, with standardized mean difference measuring effect size. Odds of being prescribed a Schedule II opioid vs a Schedule IV opioid in the 18-month periods before and after guideline publication were compared in a fully adjusted multinomial logistic regression model, which included all covariates and risk factors for opioid misuse. Effect modification was tested by examining the interaction term of the variable before and after guideline publication and the effect modifier before and after guideline publication. Because effect modification analysis included 24 separate tests and comparisons, the false discovery rate–adjusted P value (q value) was used to adjust for multiple comparisons and test for significance.14 The significance threshold was P < .05, and all tests were 2-sided.
Results
Data were obtained from 279 435 patients with a mean (SD) age of 52.9 (16.5) years; 61% were female and 79.4% were White. The prevalence of new prescriptions for each drug before and after guideline publication was as follows: codeine, 7.1% vs 7.0%; hydrocodone, 47.4% vs 45.6%; oxycodone, 22.4% vs 24.0%; and tramadol, 23.0% vs 23.4% (Table 1). The distributions of demographic factors, geographic region, obesity, benzodiazepine coprescriptions, diagnoses of psychiatric disorders, and clinician specialties were not meaningfully different (standardized mean difference, <10) in the 18-month period before vs the 18-month period after guideline publication.
Table 1. Type of Opioid Prescribed and Characteristics of Patients 18 Months Before and 18 Months After CDC Guideline Publication on March 15, 2016.
| Total (N = 279 435), No. (%) | Before guideline publication (n = 141 219), No. (%) | After guideline publication (n = 138 216), No. (%) | SMD, % | |
|---|---|---|---|---|
| Type of new opioid prescription | ||||
| Codeine | 19 786 (7.1) | 10 079 (7.1) | 9707 (7.0) | −0.4 |
| Hydrocodone | 129 943 (46.5) | 66 983 (47.4) | 62 960 (45.6) | −3.8 |
| Oxycodone | 64 865 (23.2) | 31 658 (22.4) | 33 207 (24.0) | 3.8 |
| Tramadol | 64 841 (23.2) | 32 499 (23.0) | 32 342 (23.4) | 0.9 |
| Demographic characteristics | ||||
| Age, mean (SD), y | 52.9 (16.5) | 52.2 (16.5) | 53.5 (16.4) | 7.6 |
| Sex | ||||
| Female | 170 406 (61.0) | 86 460 (61.2) | 83 946 (60.7) | −1.0 |
| Male | 109 029 (39.0) | 54 759 (38.8) | 54 270 (39.3) | 1.0 |
| Race | ||||
| African American | 38 903 (13.9) | 20 068 (14.2) | 18 835 (13.6) | −1.7 |
| White | 221 742 (79.4) | 111 766 (79.1) | 109 976 (79.6) | 1.0 |
| Other or unknowna | 18 790 (6.7) | 9385 (6.7) | 9405 (6.8) | 0.6 |
| Ethnicity | ||||
| Hispanic | 14 890 (5.3) | 7377 (5.2) | 7513 (5.4) | 0.9 |
| Not Hispanic | 250 569 (89.7) | 126 945 (89.9) | 123 624 (89.4) | −1.5 |
| Unknown | 13 976 (5.0) | 6897 (4.9) | 7079 (5.1) | 1.1 |
| Region | ||||
| Midwest | 139 114 (49.8) | 69 561 (49.3) | 69 553 (50.3) | 2.1 |
| Northeast | 22 542 (8.1) | 10 676 (7.6) | 11 866 (8.6) | 3.8 |
| South | 85 678 (30.7) | 44 344 (31.4) | 41 334 (29.9) | −3.2 |
| West | 21 209 (7.6) | 11 080 (7.9) | 10 129 (7.3) | −2.0 |
| Unknown | 10 892 (3.9) | 5558 (3.9) | 5334 (3.9) | −0.4 |
| Pain diagnosis | ||||
| Arthritis | 171 208 (61.3) | 82 288 (58.3) | 88 920 (64.3) | 12.5 |
| Musculoskeletal pain | 168 291 (60.2) | 82 811 (58.6) | 85 480 (61.9) | 6.6 |
| Back pain | 137 777 (49.3) | 70 059 (49.6) | 67 718 (49.0) | −1.2 |
| Neuropathic pain | 31 744 (11.4) | 16 244 (11.5) | 15 500 (11.2) | −0.9 |
| Headache pain | 54 968 (19.7) | 28 136 (19.9) | 26 832 (19.4) | −1.3 |
| Obesity | 151 462 (54.2) | 75 490 (53.5) | 75 972 (55.0) | 3.0 |
| Benzodiazepine coprescription | 49 169 (17.6) | 25 462 (18.0) | 23 707 (17.2) | −2.3 |
| Depression | 41 177 (14.7) | 19 963 (14.1) | 21 214 (15.4) | 3.4 |
| Anxiety disorders | 43 196 (15.5) | 20 610 (14.6) | 22 586 (16.3) | 4.8 |
| Alcohol abuse or dependence | 9216 (3.3) | 4538 (3.2) | 4678 (3.4) | 1.0 |
| Drug abuse or dependence | 11 757 (4.2) | 5619 (4.0) | 6138 (4.4) | 2.3 |
| Smoking/nicotine dependence | 90 818 (32.5) | 42 862 (30.4) | 47 956 (34.7) | 9.3 |
| Clinician type associated with prescription | ||||
| Anesthesiology/pain medicine | 2272 (0.8) | 1111 (0.8) | 1161 (0.8) | 0.6 |
| Surgical specialty | 46 420 (16.6) | 22 667 (16.1) | 23 753 (17.2) | 3.0 |
| Emergency/urgent care | 50 991 (18.2) | 26 682 (18.9) | 24 309 (17.6) | −3.4 |
| Hospital | 2531 (0.9) | 1299 (0.9) | 1232 (0.9) | −0.3 |
| Primary care | 45 401 (16.2) | 24 413 (17.3) | 20 988 (15.2) | −5.7 |
| Other specialty | 99 146 (35.5) | 49 514 (35.1) | 49 632 (35.9) | 1.8 |
| Unknown | 32 674 (11.7) | 15 533 (11.0) | 17 141 (12.4) | 4.4 |
Abbreviations: CDC, Centers for Disease Control and Prevention; SMD, standardized mean difference.
Other races included Asian, Hispanic, and Native American.
As shown in Table 2, after adjusting for covariates, the odds of receiving hydrocodone and oxycodone after guideline publication were significantly lower than those in the period before guideline publication (odds ratios [ORs], 0.95; 95% CI, 0.91-0.98 for hydrocodone and 0.86; 95% CI, 0.82-0.90 for oxycodone). Benzodiazepine coprescriptions were associated with greater odds of receiving a prescription for hydrocodone or oxycodone compared with tramadol (ORs, 1.07; 95% CI, 1.04-1.10 for hydrocodone and 1.19; 95% CI, 1.15-1.23 for oxycodone). Depression and anxiety disorders were significantly associated with greater odds of receiving a hydrocodone prescription (ORs, 1.09; 95% CI, 1.05-1.12 for depression and 1.07; 95% CI, 1.04-1.11 for an anxiety disorder) and an oxycodone prescription (ORs, 1.23; 95% CI, 1.18-1.27 for depression and 1.16; 95% CI, 1.11-1.20 for an anxiety disorder) compared with tramadol. Alcohol abuse or dependence was significantly associated with lower odds of receiving a prescription for hydrocodone vs tramadol (OR, 0.89; 95% CI, 0.84-0.94), and drug abuse or dependence was significantly associated with greater odds of receiving a prescription for codeine or oxycodone vs tramadol (ORs, 1.13; 95% CI, 1.03-1.23 for codeine and 1.40; 95% CI, 1.32-1.49 for oxycodone).
Table 2. Fully Adjusted Multinomial Model Measuring the Association Between Factors Associated With Opioid Misuse and Type of New Opioid Prescription Between the 18-Month Periods Before and After CDC Guideline Publicationa.
| Factor | OR (95% CI) | ||
|---|---|---|---|
| Codeine vs tramadol | Hydrocodone vs tramadol | Oxycodone vs tramadol | |
| Patient cohort | |||
| Before guideline publication | 1 [Reference] | 1 [Reference] | 1 [Reference] |
| After guideline publication | 0.97 (0.91-1.03) | 0.95 (0.91-0.98) | 0.86 (0.82-0.90) |
| Benzodiazepine coprescription | 0.99 (0.94-1.04) | 1.07 (1.04-1.10) | 1.19 (1.15-1.23) |
| Depression | 1.00 (0.95-1.05) | 1.09 (1.05-1.12) | 1.23 (1.18-1.27) |
| Anxiety disorders | 1.00 (0.95-1.06) | 1.07 (1.04-1.11) | 1.16 (1.11-1.20) |
| Alcohol abuse/dependence | 1.01 (0.92-1.12) | 0.89 (0.84-0.94) | 0.93 (0.87-0.99) |
| Drug abuse/dependence | 1.13 (1.03-1.23) | 0.99 (0.93-1.04) | 1.40 (1.32-1.49) |
| Nicotine dependence | 0.92 (0.88-0.95) | 1.20 (1.18-1.23) | 1.35 (1.31-1.38) |
Abbreviations: CDC, Centers for Disease Control and Prevention; OR, odds ratio.
Adjusted for age, sex, race, ethnicity, pain diagnoses, obesity, clinician type and US geographic region, and chronological time of first eligible opioid prescription (months since first possible new opioid date of September 14, 2014).
As shown in Table 3, the odds of receiving a prescription for codeine compared with a prescription for tramadol in the 18-month period after vs the 18-month period before guideline publication were higher among those with benzodiazepine coprescriptions (OR, 1.21; 95% CI, 1.03-1.42) vs those without benzodiazepine coprescriptions (OR, 0.93; 95% CI, 0.87-0.99); however, false discovery rate–adjusted P values showed that this difference was not statistically significant (q = .07). Results also showed that the odds of receiving a Schedule II opioid prescription vs tramadol in the 18-month period after vs the 18-month period before guideline publication did not significantly differ by depression, anxiety disorders, drug or alcohol abuse or dependence, and nicotine dependence.
Table 3. Stratified Estimates of Type of New Prescription Opioid in the 18-Month Periods After vs Before CDC Guideline Publication According to Factors Associated With Opioid Misuse.
| Factor | OR (95% CI) | Overall interaction P value (FDR q value)a | ||
|---|---|---|---|---|
| Codeine vs tramadol | Hydrocodone vs tramadol | Oxycodone vs tramadol | ||
| Benzodiazepine | ||||
| No benzodiazepine (after vs before) | 0.93 (0.87-0.99) | 0.93 (0.89-0.97) | 0.86 (0.82-0.90) | .02 (.17) |
| Benzodiazepine (after vs before) | 1.21 (1.03-1.42) | 1.02 (0.93-1.12) | 0.88 (0.79-0.98) | |
| P value (FDR q value) comparing stratum ORsa | .004 (.07) | .09 (.40) | .74 (.74) | |
| Depression | ||||
| No depression (after vs before) | 0.98 (0.91-1.05) | 0.94 (0.90-0.98) | 0.87 (0.83-0.91) | .08 (.40) |
| Depression (after vs before) | 0.92 (0.76-1.10) | 1.01 (0.91-1.13) | 0.82 (0.73-0.93) | |
| P value (FDR q value) comparing stratum ORsa | .52 (.60) | .19 (.56) | .42 (.57) | |
| Anxiety | ||||
| No anxiety (after vs before) | 0.97 (0.90-1.04) | 0.93 (0.90-0.97) | 0.86 (0.81-0.90) | .39 (.57) |
| Anxiety (after vs before) | 0.97 (0.82-1.16) | 1.02 (0.92-1.14) | 0.90 (0.80-1.01) | |
| P value (FDR q value) comparing stratum ORsa | .96 (.96) | .11 (.40) | .43 (.57) | |
| Alcohol abuse/dependence | ||||
| No alcohol (after vs before) | 0.97 (0.91-1.04) | 0.94 (0.91-0.98) | 0.86 (0.82-0.90) | .90 (.90) |
| Alcohol (after vs before) | 0.94 (0.64-1.38) | 0.98 (0.78-1.23) | 0.83 (0.65-1.07) | |
| P value (FDR q value) comparing stratum ORsa | .87 (.87) | .73 (.73) | .78 (.78) | |
| Drug abuse/dependence | ||||
| No drug (after vs before) | 0.98 (0.91-1.04) | 0.94 (0.91-0.98) | 0.87 (0.83-0.91) | .24 (.56) |
| Drug (after vs before) | 0.81 (0.57-1.15) | 1.00 (0.81-1.24) | 0.78 (0.63-0.98) | |
| P value (FDR q value) comparing stratum ORsa | .30 (.57) | .57 (.63) | .39 (.57) | |
| Nicotine dependence | ||||
| No nicotine (after vs before) | 0.95 (0.88-1.02) | 0.94 (0.89-0.98) | 0.85 (0.81-0.90) | .67 (.68) |
| Nicotine (after vs before) | 1.04 (0.91-1.18) | 0.97 (0.90-1.04) | 0.89 (0.82-0.96) | |
| P value (FDR q value) comparing stratum ORsa | .24 (.56) | .42 (.57) | .49 (.60) | |
Abbreviations: CDC, Centers for Disease Control and Prevention; FDR, false discovery rate; OR, odds ratio.
The FDR-adjusted P values (ie, the q values) were adjusted for age, sex, race, ethnicity, pain diagnoses, obesity, clinician type and US geographic region, and chronological time of first eligible opioid prescription (months since first possible new opioid date of September 14, 2014) before and after CDC guideline publication.
A sensitivity analysis was conducted to exclude patients who received medication-assisted therapy with buprenorphine in the 6-month period prior to a new Schedule IV or II opioid prescription. Data for a total of 382 patients were excluded because they received buprenorphine treatment: 169 before guideline publication and 213 after guideline publication. Results were nearly identical to the original results.
Discussion
Except for a 14% decrease in the odds of patients receiving oxycodone vs tramadol, we found no evidence of substantial changes in the odds of receiving a prescription for a Schedule II opioid vs tramadol in the 18 months after, compared with the 18 months before, publication of the CDC opioid prescribing guideline. Unexpectedly, a larger decrease in prescriptions for hydrocodone and oxycodone vs tramadol was not observed among patients who already had benzodiazepine prescriptions or those with depression, anxiety disorders, and substance use disorders compared with patients without these risk factors.
Analysis of US pharmacy data revealed a 25.3% decrease in high-dose prescriptions and a drop of 16.9% in the opioid prescribing rate between 2015 and 2017.3 Hydrocodone is by far the most common opioid prescribed in the United States. Thus, our observation of a small (5%) decrease in hydrocodone prescriptions may partly explain the previously reported overall decline in opioid prescribing between 2015 and 2017. However, studies indicating a decline in opioid prescribing have not been limited to new prescriptions and are not directly comparable to the results reported in this study.2,3
Limitations
Limitations include lack of data on dispensed prescriptions. We are unable to assess whether prescriptions were appropriate to patients’ pain severity and pain-related interference with daily life or functioning. Our observation period after publication of the CDC guideline was 18 months, which may be insufficient to detect longer-term trends. Results may not be generalizable to all health care systems, such as the Veterans Health Administration or those in other countries.
Conclusions
Except for the 14% decrease in prescriptions for oxycodone relative to tramadol, our results suggest the guideline release was not associated with changes in the prescribing of Schedule II opioids vs tramadol. The odds of receiving a prescription for hydrocodone or oxycodone vs tramadol in the 18-month periods before and after guideline publication for patients with psychiatric disorders did not differ significantly from the odds for patients without psychiatric disorders. Continued education is warranted to reduce prescribing of opioids with high abuse potential to patients who already have prescriptions for benzodiazepines and those with comorbid psychiatric and substance use disorders.
eTable. Variable Definitions Table
eFigure. Cohort Creation
References
- 1.Dowell D, Haegerich TM, Chou R. CDC Guideline for Prescribing Opioids for Chronic Pain—United States, 2016. JAMA. 2016;315(15):1624-1645. doi: 10.1001/jama.2016.1464 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Bohnert ASB, Guy GP Jr, Losby JL. Opioid prescribing in the United States before and after the Centers for Disease Control and Prevention’s 2016 Opioid Guideline. Ann Intern Med. 2018;169(6):367-375. doi: 10.7326/M18-1243 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Guy GP Jr, Zhang K, Schieber LZ, Young R, Dowell D. County-level opioid prescribing in the United States, 2015 and 2017. JAMA Intern Med. 2019;179(4):574-576. doi: 10.1001/jamainternmed.2018.6989 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Zhang VS, Olfson M, King M. Opioid and benzodiazepine coprescribing in the United States before and after US Food and Drug Administration boxed warning. JAMA Psychiatry. 2019;76(11):1208-1210. doi: 10.1001/jamapsychiatry.2019.2563 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Sullivan MD. Depression effects on long-term prescription opioid use, abuse, and addiction. Clin J Pain. 2018;34(9):878-884. doi: 10.1097/AJP.0000000000000603 [DOI] [PubMed] [Google Scholar]
- 6.Takemoto E, Brackbill R, Martins S, Farfel M, Jacobson M. Post-traumatic stress disorder and risk of prescription opioid use, over-use, and misuse among World Trade Center Health Registry enrollees, 2015-2016. Drug Alcohol Depend. 2020;210:107959. doi: 10.1016/j.drugalcdep.2020.107959 [DOI] [PubMed] [Google Scholar]
- 7.Bigal LM, Bibeau K, Dumbar S. Patterns in opioid prescription in the United States by region and prescribers over a 4-year period. J Opioid Manag. 2019;15(6):499-506. doi: 10.5055/jom.2019.0541 [DOI] [PubMed] [Google Scholar]
- 8.Fuentes AV, Pineda MD, Venkata KCN. Comprehension of top 200 prescribed drugs in the US as a resource for pharmacy teaching, training and practice. Pharmacy (Basel). 2018;6(2):6. doi: 10.3390/pharmacy6020043 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Jeffery MM, Hooten WM, Hess EP, et al. Opioid prescribing for opioid-naive patients in emergency departments and other settings: characteristics of prescriptions and association with long-term use. Ann Emerg Med. 2018;71(3):326-336.e19. doi: 10.1016/j.annemergmed.2017.08.042 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Murphy DL, Lebin JA, Severtson SG, Olsen HA, Dasgupta N, Dart RC. Comparative rates of mortality and serious adverse effects among commonly prescribed opioid analgesics. Drug Saf. 2018;41(8):787-795. doi: 10.1007/s40264-018-0660-4 [DOI] [PubMed] [Google Scholar]
- 11.US Department of Justice; Drug Enforcement Administration . Drugs of Abuse: A DEA Resource Guide, 2017 Edition Accessed October 27, 2020. https://www.dea.gov/sites/default/files/drug_of_abuse.pdf
- 12.Seal KH, Shi Y, Cohen G, et al. Association of mental health disorders with prescription opioids and high-risk opioid use in US veterans of Iraq and Afghanistan. JAMA. 2012;307(9):940-947. doi: 10.1001/jama.2012.234 [DOI] [PubMed] [Google Scholar]
- 13.Scherrer JF, Salas J, Copeland LA, et al. Prescription opioid duration, dose, and increased risk of depression in 3 large patient populations. Ann Fam Med. 2016;14(1):54-62. doi: 10.1370/afm.1885 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Benjamini Y, Hochberg Y. Controlling for the false discovery rate: a practical and powerful approach to multiple testing. JR Statist Soc B. 1995;57:289-300. doi: 10.1111/j.2517-6161.1995.tb02031.x [DOI] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable. Variable Definitions Table
eFigure. Cohort Creation