Opioid prescribing patterns in emergency departments and future opioid use in adolescent patients

American Journal of Emergency Medicine xxx (xxxx) xxx

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Opioid prescribing patterns in emergency departments and future opioid use in adolescent patients Patrick J. Van Winkle a,⇑, Ali Ghobadi a,e, Qiaoling Chen b, Michael Menchine c, Adam L. Sharp d a

Kaiser Permanente, Orange County, 3440 La Palma Ave, Anaheim, CA 92806, United States Southern California Permanente Medical Group, 100 South Los Robles Ave, Pasadena, CA 91101, United States c University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, United States d Kaiser Permanente, Los Angeles, 4867 Sunset Blvd, Los Angeles, CA 90027, United States e Kaiser Permanente School of Medicine, Department of Clinical Science, 100 South Los Robles Ave, Pasadena, CA 91101, United States b

a r t i c l e

i n f o

Article history: Received 1 October 2019 Accepted 17 October 2019 Available online xxxx Keywords: Adolescent Young adult Pain management Opioid

a b s t r a c t Objective: Evidence suggests that exposure to opioids in adolescence increases risk of future opioid use. We evaluate if exposure to high versus low intensity opioid prescribers in the Emergency Department (ED) influences the risk of future opioid use in adolescents. Methods: Retrospective study of opioid-naïve patients 10 to 17 years seen in one of 14 EDs between January 2013 and December 2014. We categorized ED providers into quartiles according to the proportion of encounters resulting in opioid prescriptions. Primary outcome was use of opioids in the subsequent 12 months. Analysis adjusted for patient characteristics and compared future use of opioids for patients seen by the lowest versus the highest prescribing quartiles. Results: We included 9,688 patient encounters evaluated by the lowest opioid prescribing physician quartile versus 9,467 in the highest. The highest quartile gave opioid prescriptions to 14.9% of their patients compared to 2.8% for the lowest quartile. No association with future opioid use was found for patients evaluated by low versus high prescriber quartiles (OR 0.99, 95% CI 0.90-1.08). Patients with increasing age (OR 2.15, 95% CI 1.92-2.42) and white versus Hispanic ethnicity (OR 1.55, 95% CI 1.331.80) were associated with recurrent opioid use. Conclusion: We found no association between high intensity opioid prescribers and recurrent 12 month use of opioids in opioid-naïve adolescents seen in the ED. This likely reflects various factors that put adolescents at risk for recurrent opioid use and may indicate the importance of the second prescription from primary care after initial exposure to opioids. Ó 2019 Elsevier Inc. All rights reserved.

1. Introduction Adolescent patients have experienced dramatic increases in exposure to opioids for the treatment of acute and chronic pain [1,2]. Nearly 18% of high school seniors have received a prescription for opioids, and exposure to these legitimate prescriptions can put youth at risk for future misuse [3–5]. This can be true even among adolescents who otherwise have low risk for drug abuse or

Abbreviations: ED, emergency department; ICD-9, International Classification of Disease, 9th revision; KPSC, Kaiser Permanente Southern California. ⇑ Corresponding author at: Pediatric Hospitalist, Kaiser Permanente, 3440 East La Palma Ave, Anaheim, CA 92806, United states. E-mail addresses: [email protected] (P.J. Van Winkle), ali.x.ghobadi@ kp.org (A. Ghobadi), [email protected] (Q. Chen), [email protected] (A.L. Sharp).

those who strongly disapprove of illegal drug use [6]. Ultimately, nearly 1 in 10 acknowledge misusing opioids [7–8], making prescription opioids second only to marijuana as the most commonly abused substances by young patients [9]. This information can create a dilemma for physicians evaluating adolescents for painful injuries or illnesses. Understanding the association of long-term opioid use with high versus low prescribing emergency physicians will help to better understand the risks involved with an emergency department opioid prescription. Patients commonly receive opioids in the emergency department (ED) and at hospital discharge for pain related diagnoses [1,10–13]. In the post-operative context, opioids prescribed to pediatric patients after appendectomy have shown higher odds of returning to the ED [14] and other reports have found opioid prescribing for acute surgical pain is associated with persistent

https://doi.org/10.1016/j.ajem.2019.10.020 0735-6757/Ó 2019 Elsevier Inc. All rights reserved.

Please cite this article as: P. J. Van Winkle, A. Ghobadi, Q. Chen et al., Opioid prescribing patterns in emergency departments and future opioid use in adolescent patients, American Journal of Emergency Medicine, https://doi.org/10.1016/j.ajem.2019.10.020

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P.J. Van Winkle et al. / American Journal of Emergency Medicine xxx (xxxx) xxx

use [15]. Adolescents who self-report medical and nonmedical use of prescription opioids were more likely to report that the medical use came prior to the nonmedical use [16], and 80% of teenagers that use opioids illicitly reported using remaining opioid prescription medication [7]. In Medicare patients, an association with future opioid prescriptions has been linked to visits with high (vs low) prescribing ED physicians [17]. In the adolescent population this link between opioid prescriptions given at discharge from the ED and future use has not been reported. The goal of this investigation is to examine if exposure to high versus low intensity opioid prescribers in the ED influences the risk of future opioid use in opioid-naïve adolescents. We also examine patient level factors associated with future opioid use and the timing of future use.

to 90,000, totaling about 900,000 visits per year. Of these ED visits, approximately 19% are pediatric patients and 70–80% are health plan members. Only opioid-naïve patients that had one-year continuous membership pre and post ED visit were included. Opioid-naïve was defined as no opioid dispensed within one year prior to index ED visit. Future opioid prescription was defined as one filled more than seven days and up to 12 months following the index ED visit. Opioid prescriptions filled within seven days of the ED visit were thought to reflect prescribing at that visit. We restricted the study cohort to patients with Kaiser insurance and those that were discharged home from the ED. We limited our outpatient prescription analysis to Kaiser members because our data set does not reliably capture outpatient prescriptions for patients with different insurance.

2. Methods

2.3. Study protocol

2.1. Study design

We categorized physicians according to the proportion of patients to whom they prescribed opioids at each ED. Accordingly, high intensity prescribers are the quartile of providers who prescribe to the highest proportion of their patients at any given ED. They were compared to low intensity prescribers, the quartile of providers who prescribed to the lowest proportion of their ED patients. Only providers that had at least 100 patient encounters over the study period were included. We test the hypothesis that exposure to high intensity versus low intensity prescribers is associated with higher odds of future opioid use. Since patients generally cannot choose their provider when they

We conducted a retrospective cohort study to evaluate opioid prescribing patterns from January 1, 2013 to December 31, 2014 in 14 community EDs within an integrated health delivery system, Kaiser Permanente Southern California (KPSC). 2.2. Study setting and population KPSC provides health care to over four million members and study EDs see an annual volume of patients ranging from 25,000

Table 1 Demographics and clinical characteristics of adolescent patients seen in the emergency department stratified by high and low prescribing intensity providers.

Age, mean (SD) Age, n (%) 10–13 14–17 Gender, n (%) Female Male Race/ethnicity, n (%) White Black Hispanic Asian/Pacific Islander Other/unknown Elixhauser comorbidity index, n (%) 0 1 2 or above Emergency Severity Index (given at triage), n (%) 1 to 3 4 to 5 Pain score Minimal (0–3) Moderate (4–6) Severe (7–10) Primary diagnosis, n (%) Infectious and Parasitic Diseases Mental illness Disorders of the nervous system and sense organs Diseases of the GI and GU systems Complications of pregnancy, childbirth, and the puerperium Diseases of the skin and subcutaneous tissue Diseases of the musculoskeletal system and connective tissue Injury and poisoning Symptoms including syncope, fever, abdominal pain, malaise Diseases of the respiratory and cardiovascular systems Other With outpatient opioid prescription at index ED visit, n (%) No Yes

Low intensity (n = 9,668)

High intensity (n = 9,467)

Standardized difference

13.6 (2.28)

13.8 (2.29)

0.06

4497 (46.5%) 5171 (53.5%)

4158 (43.9%) 5309 (56.1%)

4751 (49.1%) 4917 (50.9%)

4606 (48.7%) 4861 (51.3%)

2030 (21%) 1133 (11.7%) 5591 (57.8%) 634 (6.6%) 280 (2.9%)

2026 (21.4%) 1110 (11.7%) 5437 (57.4%) 638 (6.7%) 256 (2.7%)

4238 (43.8%) 4176 (43.2%) 1254 (13%)

4258 (45%) 4017 (42.4%) 1192 (12.6%)

4780 (49.4%) 4888 (50.6%)

3864 (40.8%) 5603 (59.2%)

3162 (32.7%) 2749 (28.4%) 3757 (38.9%)

2935 (31%) 2759 (29.1%) 3773 (39.9%)

143 (1.5%) 466 (4.8%) 738 (7.6%) 821 (8.5%) 30 (0.3%) 211 (2.2%) 386 (4%) 3767 (39%) 1650 (17.1%) 1351 (14%) 105 (1.1%)

120 (1.3%) 405 (4.3%) 735 (7.8%) 685 (7.2%) 30 (0.3%) 233 (2.5%) 384 (4.1%) 4218 (44.6%) 1254 (13.2%) 1299 (13.7%) 104 (1.1%)

9395 (97.2%) 273 (2.8%)

8061 (85.1%) 1406 (14.9%)

0.05 0.01

0.02

0.02

0.17

0.04

0.14

0.43

Please cite this article as: P. J. Van Winkle, A. Ghobadi, Q. Chen et al., Opioid prescribing patterns in emergency departments and future opioid use in adolescent patients, American Journal of Emergency Medicine, https://doi.org/10.1016/j.ajem.2019.10.020

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come to an ED setting, the exposure to a high versus low prescriber is quasi-random and not subject to patient level factors. As such any association between exposure to a high opioid prescriber and future use is less likely to be confounded by selection or omitted variable bias and more likely to represent a causal relationship. This strategy has been previously deployed and reported [17]. 2.4. Measurements All data were obtained from KPSC’s electronic medical records which include information about health plan membership, health care utilization, diagnoses, pharmacy, and all clinical data captured as part of the electronic health record documentation. Various patient and encounter variables were included for analysis: race/ ethnicity; gender; insurance status; Emergency Department; primary diagnosis of ED visit; and Emergency Severity Index given at triage. The Elixhauser comorbidity index was used for risk adjustment of any chronic medical conditions [18]. To evaluate the use of opioids across different diagnoses we used the Clinical Classifications Software for International Classification of Disease, 9th revision (ICD-9-CM). As noted on the website (https://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp#download), the ICD-9-CM’s codes are collapsed into a smaller number of clinically meaningful categories.

2.5. Data analysis Patients do not self-select emergency physicians and thus patients’ characteristics (both observed and unobserved) are expected to be similar across patients treated by physicians with different prescribing intensity. The distributions of demographic and clinical characteristics of the study cohorts were stratified by patients who were seen by high-intensity prescribers and those who were seen by low-intensity prescribers; balance was assessed using standardized difference (Cohen’s d), which is insensitive to sample size. A standardized difference of 0.2 or greater in absolute value is considered imbalance, and above 0.1 but less than 0.2 is considered meaningful. The association between provider prescribing intensity and recurrent use of opioids was estimated using patient-level multivariable logistic regression, adjusting for patients’ age, sex, race or ethnicity, primary diagnosis of ED visit, Emergency Severity Index given at triage, and Elixhauser comorbidity index. To account for grouping of patients within EDs, we used generalized estimating equations with each ED as a clustering variable. All analyses were conducted using SAS version 9.4, Cary, North Carolina, USA. This study was approved by the Kaiser Permanente Southern California Institutional Review Board according to the declaration of Helsinki and federal regulations. Consent was waived.

Table 2 Adjusted odds ratio from logistic regression for recurrent opioid use in the 12 months following an index ED visit for adolescent patients seen in the emergency department.

Provider prescribing intensity Lowest Highest Age 10-13 years 14-17 years Gender Female Male Race/ethnicity Hispanic Asian Black White Others/unknown Primary diagnosis Diseases of the respiratory and cardiovascular systems Complications of pregnancy, childbirth, and the puerperium Diseases of the GI and GU systems Diseases of the musculoskeletal system and connective tissue Diseases of the skin and subcutaneous tissue Disorders of the nervous system and sense organs Infectious and Parasitic Diseases Injury and poisoning Mental illness Symptoms including syncope, fever, abdominal pain, malaise Other Elixhauser comorbidity index 0 1 2 or above Maximum pain score Minimal (0–3) Moderate (4–6) Severe (7–10) Emergency Severity Index (given at triage) Level 4–5 Level 1–3

OR

95% CI

Reference 0.99

0.90

1.08

Reference 2.15

1.92

2.42

Reference 1.02

0.93

1.12

Reference 0.94 1.02 1.55 0.74

0.77 0.86 1.33 0.52

1.16 1.21 1.80 1.06

Reference 2.92 1.36 1.32 1.25 0.93 1.23 1.34 1.23 0.88 1.05

1.98 1.07 0.92 0.92 0.73 0.88 1.20 0.94 0.75 0.67

4.30 1.72 1.88 1.71 1.17 1.71 1.50 1.60 1.03 1.64

Reference 1.10 1.21

0.99 1.10

1.22 1.33

Reference 1.35 1.89

1.15 1.57

1.58 2.26

Reference 1.22

1.07

1.41

Medical center is treated as clustering variable.

Please cite this article as: P. J. Van Winkle, A. Ghobadi, Q. Chen et al., Opioid prescribing patterns in emergency departments and future opioid use in adolescent patients, American Journal of Emergency Medicine, https://doi.org/10.1016/j.ajem.2019.10.020

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P.J. Van Winkle et al. / American Journal of Emergency Medicine xxx (xxxx) xxx

3. Results 3.1. Demographic and clinical characteristics We included 9,688 patient encounters evaluated by the lowest opioid prescribing physician quartile versus 9,467 in the highest. The highest quartile gave opioid prescriptions to 14.9% of their patients compared to 2.8% for the lowest quartile, an over fivefold difference. Overall, the patient groups were similar with absolute standardized difference less than 0.2. Characteristics of the study sample are given in Table 1. 3.2. Description of recurrent opioid use There was no significant difference in the percent of patients that filled an opioid prescription seven days to 12 months after the index ED visit comparing low and high physician quartiles (9.9% lowest quartile vs 10.0% highest, P = 0.773). For the patients in the low prescriber group that filled a prescription, the majority (80.0%) filled one prescription, 19.4% filled two to four, and 0.6% filled greater than four prescriptions. For patients in the high intensity prescriber group, the majority (80.5%) filled one prescription, 18.3% filled two to four, and 1.2% filled greater than four prescriptions. There was not a significant difference in the number of prescriptions filled between the two groups (P = 0.588). After adjustment for observable patient factors and hospital fixed effects, we observed no association between exposure to high versus low intensity prescribers and recurrent use of opioids in the 12 months following the ED visit in this opioid-naïve patient population (OR 0.99, 95% CI 0.90–1.08) (Table 2). For the timing of the prescriptions in the 12 months following the index ED visit, 27.1% were filled in the seven to 30 days after the index ED visit. The majority of prescriptions (72.9%) were

filled in the 11 months following that initial month (Fig. 1). For months two to 12, the distribution of the filled prescriptions was relatively even, with a minimum of 5.7% and a maximum of 7.8%. The level of filled prescriptions did not decrease over time after the initial month, with 6.7% of the prescriptions filled in the 12th month. The medications filled are listed in Table 3; hydrocodone (58.4%) and codeine (30.9%) made up the majority of prescriptions. 3.3. Factors associated with recurrent opioid use In the multivariate analysis, multiple factors were found to be independently associated with differential odds of recurrent use of opioids in the 12 months following the index ED visit (Table 2). Increasing patient age (OR 2.15, 95% CI 1.92–2.42), white race versus Hispanic ethnicity (OR 1.55, 95% CI 1.33–1.80), more comor-

Table 3 Opioid medication filled by adolescent patients in the 12 months following the index emergency department visit. Medication

Dispensing count (%)

Codeine* Hydrocodone Hydromorphone Methadone Morphine Oxycodone Tramadol Total

766 (30.9%) 1447 (58.4%) 5 (0.2%) 1 (0.04%) 5 (0.2%) 123 (5.0%) 130 (5.3%) 2476 (1898 patients**)

* The codeine prescriptions were for acetaminophen with codeine. ** Please note that some patients had more than one prescription.

*Please note the first month starts 7 days aer the index ED visit Fig. 1. Percent of prescriptions filled by adolescent patients per month in the year following the index ED visit. *Please note the first month starts 7 days after the index ED visit.

Please cite this article as: P. J. Van Winkle, A. Ghobadi, Q. Chen et al., Opioid prescribing patterns in emergency departments and future opioid use in adolescent patients, American Journal of Emergency Medicine, https://doi.org/10.1016/j.ajem.2019.10.020

P.J. Van Winkle et al. / American Journal of Emergency Medicine xxx (xxxx) xxx

bidities (OR 1.21, 95% CI 1.10–1.33), and a higher maximum pain score (OR 1.89, 95% CI 1.57–2.26) were associated with recurrent use of opioids. 4. Discussion In this multicenter study of opioid naïve adolescent ED patients, we found no association between subsequent 12-month opioid prescriptions for patient encounters with high versus low opioid ED prescriber groups. Our findings indicate that an initial ED prescription for opioids given to opioid-naïve adolescents is not, in and of itself, the catalyst of future prescription opioid use. Our findings likely reflect the complex set of influences that put adolescents at risk for recurrent opioid use and indicates the key role of subsequent interactions with health care systems and outpatient providers seen in follow up to ED visits. There is a body of literature indicating a relationship between ED opioid prescriptions and future opioid use and misuse, but these studies are mostly from the perspective of patients reporting their initial prescriptions and exposure to opioids in adolescence or young adulthood [3,4,6,19]. These studies do not account for the period of time between the initial prescription and subsequent use. Our results are in contrast to the idea that these initial ED prescriptions cause future opioid use and misuse. Our study is unique in that it looks directly at the relationship between exposure to opioids and the risk of subsequent opioid prescriptions through use of the opioid prescribing intensity of the ED providers. The 10% of patients who filled another opioid prescription in the 12-month follow up period is similar to previous reports [20]. Our study also found older, white, female adolescents were at highest risk [21–23]. These are populations that might be at more risk for future use and misuse of opioids. The body of evidence showing the dangers of opioids in the adolescent population is robust. Our findings don’t minimize the importance of this, however, ED physicians should be reassured that the risk of an ED opioid prescription leading to long term use is low. The trigger to recurrent opioid use might be more influenced by a second prescription at follow-up, rather than the initial encounter. Therefore, the potential for an ED opioid prescription provoking long-term use may be mitigated by factors related to the environment and the health care system. ED providers do not need to deny adolescent patients opioids when clinically indicated. 4.1. Limitations First, this was a retrospective study and thus the findings are associations and not causal relationships. Second, our study was not able to measure important characteristics related to opioid prescribing such as patient satisfaction with the visit or whether patients actually used their discharge medications as indicated. Third, we did not evaluate for return visits related to the primary complaint and cannot obtain medication data on patients that might have gone to an outside ED after their visit for the same issue. Fourth, we relied on data abstraction using the electronic medical record and identifying cohorts for subgroup analysis using ICD-9 codes, which are potentially subject to inaccuracy. Fifth, we are a large managed health care system with an integrated medical record, the generalizability of these results to other care settings is unclear. 4.2. Conclusions In this multicenter study of opioid naïve adolescent ED patients, we found no association between high intensity opioid prescribers and recurrent use of opioids in the following 12 months. Our find-

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ings indicate that the initial prescription might not be, in isolation, a key driver of future opioid use. While judicious use of opioids is clearly warranted, our findings suggest that ED providers do not need to deny adolescents opioids out of fear of provoking future use. Our findings acknowledge the importance of primary care follow up and judicious use of the second opioid prescription for the health and safety of adolescent patients. Funding source This research was supported by a grant from the Regional Research Committee of Kaiser Permanente Southern California (KP-RRC-20160401). Presentations Data from this study was presented in poster format at the Pediatric Hospital Medicine Conference in Seattle, WA on July 27, 2019. Declaration of Competing Interest All authors have no competing interests to declare. Acknowledgments The authors thank the patients of Kaiser Permanente for helping us improve care through the use of information collected through our electronic health record systems. This research was supported by a grant from the Regional Research Committee of Kaiser Permanente Southern California (KP-RRC-20160401). References [1] Fortuna RJ, Robbins BW, Caiola E, Joynt M, Halterman JS. Prescribing of controlled medications to adolescents and young adults in the United States. Pediatrics 2010;126(6):1108–16. https://doi.org/10.1542/peds.2010-0791. [2] Baker JA, Avorn J, Levin R, Bateman BT. Opioid prescribing after surgical extraction of teeth in medicaid patients, 2000–2010. JAMA 2016;315 (15):1653–4. https://doi.org/10.1001/jama.2015.19058. [3] McCabe SE, West BT, Teter CJ, Boyd CJ. Medical and nonmedical use of prescription opioids among high school seniors in the United States. Arch Pediatr Adolesc Med 2012;166(9):797–802. https://doi.org/10.1001/ archpediatrics.2012.85. [4] Cicero TJ, Ellis MS, Surratt HL, Kurtz SP. The changing face of heroin use in the United States: a retrospective analysis of the past 50 years. JAMA Psychiatry. 2014;71(7):821–6. https://doi.org/10.1001/jamapsychiatry.2014.366. [5] Butler MM, Ancona RM, Beauchamp GA, et al. Emergency Department Prescription Opioids as an Initial Exposure Preceding Addiction. Ann Emerg Med 2016;68(2):202–8. https://doi.org/10.1016/j.annemergmed.2015.11.033. [6] Miech R, Johnston L, O’Malley PM, Keyes KM, Heard K. Prescription opioids in adolescence and future opioid misuse. Pediatrics 2015;136(5):e1169–77. https://doi.org/10.1542/peds.2015-1364. [7] McCabe SE, West BT, Teter CJ, Cranford JA, Ross-Durow PL, Boyd CJ. Adolescent nonmedical users of prescription opioids: brief screening and substance use disorders. Addict Behav 2012;37(5):651–6. https://doi.org/10.1016/j. addbeh.2012.01.021. [8] Manchikanti L, Singh A. Therapeutic opioids: a ten-year perspective on the complexities and complications of the escalating use, abuse, and nonmedical use of opioids. Pain Physician 2008;11(2 Suppl):S63–88. [9] Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings. Substance Abuse and Mental Health Services Administration; 2011. [10] Mazer-Amirshahi M, Mullins PM, Rasooly IR, van den Anker J, Pines JM. Trends in prescription opioid use in pediatric emergency department patients. Pediatr Emerg Care 2014;30(4):230–5. https://doi.org/10.1097/ PEC.0000000000000102. [11] Sheridan DC, Meckler GD, Spiro DM, Koch TK, Hansen ML. Diagnostic testing and treatment of pediatric headache in the emergency department. J Pediatr 2013;163(6):1634–7. https://doi.org/10.1016/j.jpeds.2013.07.006. [12] Richer LP, Laycock K, Millar K, et al. Treatment of children with migraine in emergency departments: national practice variation study. Pediatrics 2010;126(1):e150–5. https://doi.org/10.1542/peds.2009-2337. [13] Hudgins JD, Porter JJ, Monuteaux MC, Bourgeois FT. Trends in opioid prescribing for adolescents and young adults in ambulatory care settings. Pediatrics 2019;143(6). https://doi.org/10.1542/peds.2018-1578. [14] Anderson KT, Bartz-Kurycki MA, Ferguson DM, et al. Too much of a bad thing: Discharge opioid prescriptions in pediatric appendectomy patients. J Pediatr Surg 2018;53(12):2374–7. https://doi.org/10.1016/j.jpedsurg.2018.08.034. [15] Harbaugh CM, Lee JS, Hu HM, et al. Persistent Opioid Use Among Pediatric Patients After Surgery. Pediatrics 2018;141(1):e20172439. https://doi.org/ 10.1542/peds.2017-2439.

Please cite this article as: P. J. Van Winkle, A. Ghobadi, Q. Chen et al., Opioid prescribing patterns in emergency departments and future opioid use in adolescent patients, American Journal of Emergency Medicine, https://doi.org/10.1016/j.ajem.2019.10.020

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[16] McCabe SE, West BT, Veliz P, McCabe VV, Stoddard SA, Boyd CJ. Trends in medical and nonmedical use of prescription opioids among US adolescents: 1976–2015. Pediatrics 2017;139(4). https://doi.org/10.1542/peds.2016-2387. [17] Barnett ML, Olenski AR, Jena AB. Opioid-prescribing patterns of emergency physicians and risk of long-term use. N Engl J Med 2017;376(7):663–73. https://doi.org/10.1056/NEJMsa1610524. [18] van Walraven C, Austin PC, Jennings A, Quan H, Forster AJ. A modification of the Elixhauser comorbidity measures into a point system for hospital death using administrative data. Med Care 2009;47(6):626–33. https://doi.org/ 10.1097/MLR.0b013e31819432e5. [19] McCabe SE, Veliz PT, Boyd CJ, Schepis TS, McCabe VV, Schulenberg JE. A prospective study of nonmedical use of prescription opioids during adolescence and subsequent substance use disorder symptoms in early midlife. Drug Alcohol Depend 2019;194:377–85. https://doi.org/10.1016/ j.drugalcdep.2018.10.027.

[20] Whiteside LK, Russo J, Wang J, Ranney ML, Neam V, Zatzick DF. Predictors of sustained prescription opioid use after admission for trauma in adolescents. J Adolesc Health 2016;58(1):92–7. https://doi.org/10.1016/ j.jadohealth.2015.08.011. [21] Tomaszewski DM, Arbuckle C, Yang S, Linstead E. Trends in Opioid Use in Pediatric Patients in US Emergency Departments From 2006 to 2015. JAMA Netw Open 2018;1(8):e186161. https://doi.org/ 10.1001/jamanetworkopen.2018.6161. [22] Groenewald CB, Rabbitts JA, Gebert JT, Palermo TM. Trends in opioid prescriptions among children and adolescents in the United States: a nationally representative study from 1996 to 2012. Pain 2016;157 (5):1021–7. https://doi.org/10.1097/j.pain.0000000000000475. [23] Young AM, Glover N, Havens JR. Nonmedical use of prescription medications among adolescents in the United States: a systematic review. J Adolesc Health Off Publ Soc Adolesc Med 2012;51(1):6–17. https://doi.org/10.1016/ j.jadohealth.2012.01.011.

Please cite this article as: P. J. Van Winkle, A. Ghobadi, Q. Chen et al., Opioid prescribing patterns in emergency departments and future opioid use in adolescent patients, American Journal of Emergency Medicine, https://doi.org/10.1016/j.ajem.2019.10.020