Abstract
Objective
The objective of this study was to evaluate the incidence of perioperative opioid prescription and the development of new persistent opioid usage in patients prescribed perioperative opioids for common otolaryngological procedures.
Study Design
Retrospective cohort study.
Setting
TriNetX US Collaborative Research Network.
Methods
The TriNetX US Collaborative Research Network was queried to create cohorts of opioid‐naive adult patients who underwent tonsillectomy, sinus surgery, parotidectomy, septoplasty, tympanoplasty, rhinoplasty, or parathyroidectomy between 2010 and 2024. Patients prescribed perioperative opioids (2 weeks before to 1 month after surgery) were compared with those not prescribed opioids. Persistent opioid use was defined as opioid prescription between 3 and 9 months after surgery. Propensity score matching was performed based on demographics, smoking status, mental health diagnoses (eg, mood, anxiety, personality, and substance use disorders), preoperative pain conditions (eg, back, neck, and joint pain), as well as other medical comorbidities, and healthcare utilization.
Results
We identified 319,395 opioid‐naive patients who underwent the selected otolaryngological procedures. Of these patients, 273,898 (85.8%) received perioperative opioids. The rate of perioperative opioid usage was highest for parotidectomy. Across all procedures, patients who received perioperative opioids were more likely to develop new persistent opioid use. The highest risk ratios (RR) were observed for parotidectomy (RR: 2.64; 95% CI: 1.94, 3.59) and tympanoplasty (RR: 2.01; 95% CI: 1.53, 2.66).
Conclusions
Perioperative opioid prescription following common otolaryngological procedures is associated with a higher risk of new persistent opioid use. These findings highlight the need for careful opioid prescribing to reduce long‐term opioid dependence.
Keywords: otolaryngology, perioperative opioids, persistent opioid use
Opioids are widely utilized in perioperative care, but their use carries risks of dependency, misuse, and prolonged consumption. 1 , 2 , 3 The perioperative period is a critical time when opioid prescribing practices can influence both immediate pain control and long‐term patient outcomes. 4 The widespread availability of opioids has contributed to a public health crisis, with increased rates of opioid dependence, overdose, and death reported over the past 2 decades. 5
Persistent opioid use, defined as continued opioid therapy beyond the expected recovery period, is a recognized complication of surgical care. 3 , 6 , 7 Studies have shown that patients who develop persistent opioid use are at an increased risk of transitioning to opioid use disorder (OUD), a chronic condition associated with long‐term morbidity and mortality. 8 Perioperative opioid prescribing is a key modifiable factor influencing this trajectory, with evidence suggesting that higher exposure during the perioperative period directly correlates with the likelihood of prolonged opioid use. 7
Although more frequently studied in the context of major surgical procedures, persistent opioid use has also been observed following lower‐risk surgeries. 7 , 9 , 10 , 11 , 12 Risk factors such as preoperative opioid exposure, psychological comorbidities, and the nature of the procedure contribute to variability in outcomes, necessitating procedure‐specific investigations. 13 Otolaryngological procedures are associated with a wide range of postoperative pain levels and opioid requirements, 14 yet limited data exists regarding the role of perioperative opioid prescriptions in the development of persistent use within otolaryngology. Current evidence suggests that opioids are often overprescribed, with patients consuming less than the prescribed amounts. 15 , 16 However, much of the research is constrained by small sample sizes, limited follow‐up, and single‐institution data. To address this gap, we leveraged the TriNetX platform, a real‐world electronic health record (EHR) network, to examine perioperative opioid prescribing and its association with persistent use across diverse healthcare settings (www.trinetx.com).
This study examines the incidence of perioperative opioid prescriptions and their association with persistent opioid use in opioid‐naive patients undergoing common otolaryngological procedures, including tonsillectomy, sinus surgery, parotidectomy, septoplasty, tympanoplasty, rhinoplasty, and parathyroidectomy. We hypothesize that perioperative opioid prescriptions increase the risk of persistent opioid use, with the degree of risk varying by procedure. By analyzing a large retrospective cohort, this study aims to identify high‐risk procedures and patient populations to support evidence‐based opioid prescribing practices.
Methods
Database Description
This study was performed using the US Collaborative Network of the TriNetX platform, a federated, aggregated EHR research network, containing de‐identified EHR data from 122 million patients across 66 healthcare organizations (HCOs) within the United States. This retrospective study is exempt from institutional review board or ethics committee approval. The data reviewed is a secondary analysis of existing data, involves no interaction with human subjects, and meets the de‐identification standard in Section §164.514(a) of the HIPAA Privacy Rule.
Study Population
For this study, we defined and characterized cohorts using codes from the International Classification of Diseases, 10th Revision (ICD‐10), Logical Observation Identifiers Names and Codes (LOINC), Current Procedural Terminology (CPT), and the Veterans Affairs (VA) Drug Classification system. The ICD‐10 is a global system for coding and classifying diseases, injuries, and deaths. LOINC is a universal standard and ontology for identifying medical observations, tests, and measurements. A CPT code is a five‐digit code that identifies medical procedures and services performed by healthcare professionals. The VA Drug Classification system categorizes medications to support standardized pharmacy management across healthcare facilities.
The study included adult opioid‐naive patients, 18 years and older, who underwent common otolaryngological procedures between 2010 and 2024. Procedures assessed included tonsillectomy, sinus surgery, parotidectomy, septoplasty, tympanoplasty, rhinoplasty, and parathyroidectomy. These procedures represent commonly performed otolaryngologic operations that are consistently coded across TriNetX and span a range of postoperative pain and prescribing patterns, making them suitable for evaluating variability in perioperative opioid exposure and persistent use. The CPT codes used to identify these procedures are detailed in the Supplemental Material, available online. Patients prescribed opioids perioperatively, defined as 2 weeks before to 1 month after the procedure, were compared with those not prescribed opioids. This exposure window was selected to capture real‐world prescribing practices, including anticipatory postoperative prescriptions that are frequently written and filled shortly before surgery, and is consistent with a prior study of patients undergoing urologic surgeries. 10 Data for this study was collected between 04/27/2025 and 05/01/2025.
Exclusion criteria included patients who received an opioid prescription between 1 year and 2 weeks before surgery, those with a history of opioid misuse or dependence (ICD‐10: F11.1 and F11.2), and patients who underwent additional surgical procedures involving anesthesia (CPT Section ID: 1002796) within 1 to 9 months postoperatively. Although these criteria exclude subsequent procedures, same‐day concomitant operations performed under the same anesthetic encounter cannot always be distinguished within TriNetX due to coding granularity and may remain included.
Statistical Analysis
Patients were stratified based on both the type of otolaryngological procedure and whether they received a perioperative opioid prescription. This created procedure‐specific cohorts of patients who did or did not receive perioperative opioids.
The primary outcome was persistent opioid use, defined as the presence of an opioid prescription documented between 3 and 9 months following the index procedure. This definition is consistent with methodologies used in prior large database studies, where persistent postoperative opioid use was identified based on prescription records within a defined postoperative interval. 6 , 10 , 12 To adjust for potential confounding variables, 1:1 propensity score matching (PSM) was conducted using logistic regression within the TriNetX Analytics Platform. Matching was performed using greedy nearest‐neighbor algorithms with a caliper of 0.1 pooled standard deviations. Variables used for matching included baseline demographics (age, sex, and race/ethnicity), smoking status, preoperative pain diagnoses (eg, back pain, joint pain, pelvic pain, abdominal pain), mental health conditions (eg, anxiety disorders, mood disorders, substance use disorders, personality disorders), medical comorbidities (eg, diabetes mellitus, hypertension), and healthcare utilization. The balance of covariates before and after PSM, stratified by procedure, is presented in the Supplemental Material, available online. After PSM, the proportion of patients developing persistent opioid use was compared between each of the 2 procedure‐specific cohorts. Risk ratios (RR) with 95% confidence intervals (CI) were calculated to assess the magnitude of the difference. Statistical significance was evaluated using Z‐tests, with a P < .001 or a 95% CI that did not cross 1.0 considered significant. A stringent P < .001 threshold was selected to limit type I error in the context of the large cohort size and multiple procedure‐specific comparisons. The mean number of opioid prescriptions in the 3 to 9 months postoperative period was also calculated in each cohort by dividing the total number of prescriptions received during the 3 to 9 months postoperative period by the number of patients who received opioids during this time; patients who did not receive opioids during this period were excluded from these calculations. Baseline characteristics were also compared between patients who received perioperative opioids and developed persistent use and those who received perioperative opioids but did not develop persistent use to explore potential contributors to prolonged opioid use. All statistical analyses were conducted using the R statistical package, version 3.2.3 (R Program for Statistical Computing), embedded within the TriNetX platform.
Results
A total of 319,395 patients undergoing otolaryngology procedures were included in the analysis. Of these, 45,497 patients (14.2%) did not receive a perioperative opioid prescription, while 273,898 patients (85.8%) did receive a prescription (Table 1). The most common procedure was septoplasty (n = 102,031, 31.9%), followed by sinus surgery (n = 56,066, 17.6%) and parathyroidectomy (n = 49,699, 15.6%). Tonsillectomy accounted for 44,355 cases (13.9%), tympanoplasty for 28,347 cases (8.9%), and parotidectomy for 20,271 cases (6.3%). Rhinoplasty was the least frequent procedure, performed in 18,626 patients (5.8%).
Table 1.
Perioperative Opioid Prescribing Rate Stratified by Procedure
| Otolaryngology procedure | Total | No perioperative opioids | Perioperative opioids prescribed |
|---|---|---|---|
| Tonsillectomy | 44,355 | 3867 (8.7%) | 40,488 (91.3%) |
| Parotidectomy | 20,271 | 1433 (7.1%) | 18,838 (92.9%) |
| Tympanoplasty | 28,347 | 2677 (9.4%) | 25,670 (90.6%) |
| Septoplasty | 102,031 | 8125 (8%) | 93,906 (92%) |
| Parathyroidectomy | 49,699 | 5181 (10.4%) | 44,518 (89.6%) |
| Rhinoplasty | 18,626 | 1762 (9.5%) | 16,864 (90.5%) |
| Sinus surgery | 56,066 | 22,452 (40%) | 33,614 (60%) |
| All surgeries | 319,395 | 45,497 (14.2%) | 273,898 (85.8%) |
Perioperative opioid prescribing rates varied significantly by procedure. The highest rates were observed for parotidectomy (92.9%), followed by septoplasty (92%), tonsillectomy (91.3%), rhinoplasty (90.5%), tympanoplasty (90.6%), parathyroidectomy (89.6%), and sinus surgery (60%).
After PSM, 3854 patients were included in each cohort for tonsillectomy, with 6% of opioid recipients developing persistent use compared to 3.6% of non‐recipients (RR: 1.68, 95% CI: 1.37‐2.07; P < .001) (Figure 1). For parotidectomy, 1431 patients were included in each group, and persistent opioid use was observed in 9.8% of opioid recipients compared to 3.7% of nonrecipients (RR: 2.64, 95% CI: 1.94‐3.59; P < .001). In the tympanoplasty cohort, 2672 patients were included in each cohort, and 5.4% of patients who received opioids developed persistent use compared to 2.7% of nonrecipients (RR: 2.01, 95% CI: 1.53‐2.66; P < .001). Among 8125 patients undergoing septoplasty, 5.9% of opioid recipients developed persistent use compared to 3.8% of nonrecipients (RR: 1.55, 95% CI: 1.35‐1.78; P < .001). For parathyroidectomy, 5181 patients were included in each group, and 4.4% of opioid recipients developed persistent use compared to 3.1% of nonrecipients (RR: 1.43, 95% CI: 1.17‐1.74; P < .001). In the sinus surgery cohort, there were 21,287 patients included in each cohort, and 8.7% of patients who received opioids developed persistent use compared to 6.9% of those who did not (RR: 1.26, 95% CI: 1.18‐1.35; P < .001). For rhinoplasty, 1752 patients were included in each cohort, and 5% of opioid recipients developed persistent use compared to 3% of nonrecipients (RR: 1.64, 95% CI: 1.17‐2.30). However, this result was not statistically significant (P = .003). The mean number of opioid prescriptions among patients who actually received opioid prescriptions during the 3‐ to 9‐month period following the index procedure was comparable between patients who received perioperative opioid prescriptions and those who did not (Table 2).
Figure 1.
Rate of persistent opioid use in patients with and without perioperative opioid prescriptions.
Table 2.
Total and Mean Number of Opioid Prescriptions Associated With Persistent Opioid Use Stratified by Procedure in a Propensity Score–Matched Cohort
| Tonsillectomy | ||
| No perioperative opioids | Perioperative opioid Rx | |
| No. of patients | 3854 | 3854 |
| Opioid Rx in the 3‐9‐mo follow‐up, n (%) | 138 (3.6%) | 232 (6%) |
| Risk ratio (95% CI); P‐value | ‐‐‐ | 1.68 (1.37, 2.07); P < .001 |
| Mean ± SD, No. of Rx | 3.57 ± 7.00 | 1.95 ± 2.08 |
| Parotidectomy | ||
| No perioperative opioids | Perioperative opioid Rx | |
| No. of patients | 1431 | 1431 |
| Opioid Rx in the 3‐9‐mo follow‐up, n (%) | 53 (3.7%) | 140 (9.8%) |
| Risk ratio (95% CI); P‐value | ‐‐‐ | 2.64 (1.94, 3.59); P < .001 |
| Mean ± SD, No. of Rx | 4.47 ± 4.72 | 3.23 ± 5.25 |
| Tympanoplasty | ||
| No perioperative opioids | Perioperative opioid Rx | |
| No. of patients | 2672 | 2672 |
| Opioid Rx in the 3‐9‐mo follow‐up, n (%) | 72 (2.7%) | 145 (5.4%) |
| Risk ratio (95% CI); P‐value | ‐‐‐ | 2.01 (1.53, 2.66); P < .001 |
| Mean ± SD, No. of Rx | 1.71 ± 1.64 | 1.54 ± 1.49 |
| Septoplasty | ||
| No perioperative opioids | Perioperative opioid Rx | |
| No. of patients | 8125 | 8125 |
| Opioid Rx in the 3‐9‐mo follow‐up, n (%) | 310 (3.8%) | 480 (5.9%) |
| Risk ratio (95% CI); P‐value | ‐‐‐ | 1.55 (1.35, 1.78); P < .001 |
| Mean ± SD, No. of Rx | 1.79 ± 2.31 | 1.93 ± 3.66 |
| Parathyroidectomy | ||
| No perioperative opioids | Perioperative opioid Rx | |
| No. of patients | 5181 | 5181 |
| Opioid Rx in the 3‐9‐mo follow‐up, n (%) | 160 (3.1%) | 228 (4.4%) |
| Risk ratio (95% CI); P‐value | ‐‐‐ | 1.43 (1.17, 1.74); P < .001 |
| Mean ± SD, No. of Rx | 2.36 ± 5.08 | 2.40 ± 4.51 |
| Rhinoplasty | ||
| No perioperative opioids | Perioperative opioid Rx | |
| No. of patients | 1752 | 1752 |
| Opioid Rx in the 3‐9‐mo follow‐up, n (%) | 53 (3.0%) | 87 (4.9%) |
| Risk ratio (95% CI); p‐value | ‐‐‐ | 1.64 (1.17, 2.30); P = .003 |
| Mean ± SD, No. of Rx | 1.91 ± 2.68 | 1.69 ± 1.23 |
| Sinus surgery | ||
| No perioperative opioids | Perioperative opioid Rx | |
| No. of patients | 21,287 | 21,287 |
| Opioid Rx in the 3‐9‐mo follow‐up, n (%) | 1463 (6.9%) | 1844 (8.7%) |
| Risk ratio (95% CI); P‐value | ‐‐‐ | 1.26 (1.18, 1.35); P < .001 |
| Mean ± SD, No. of Rx | 2.31 ± 3.63 | 2.95 ± 5.85 |
Abbreviation: CI, confidence interval.
To explore factors associated with persistent opioid use outside of perioperative opioid prescription, we compared baseline characteristics between patients who received perioperative opioids and developed persistent opioid use (n = 16,094) versus those who did not develop persistent use (n = 223,206) (Table 3). Patients who developed persistent opioid use were older (mean age 51 years vs 45.7 years; P < .001) and had higher prevalences of comorbidities, including diabetes mellitus (14% vs 8%; P < .001) and hypertensive diseases (37% vs 21%; P < .001). Pain‐related diagnoses, such as dorsalgia (30% vs 17%; P < .001), joint pain (31% vs 19%; P < .001), and abdominal and pelvic pain (26% vs 16%; P < .001), were significantly more common in the persistent opioid use group. Mental health conditions, including mood disorders (20% vs 12%; P < .001) and anxiety disorders (20% vs 13%; P < .001), were also more prevalent. These findings suggest that pre‐existing pain conditions, mental health comorbidities, and indicators of chronic disease may collectively contribute to the increased risk of prolonged opioid use following perioperative exposure.
Table 3.
Baseline Characteristic Comparison of Patients Receiving Perioperative Opioids Stratified by Subsequent Persistent Opioid Use Status
| Variables | Perioperative opioids and new persistent opioid use (n = 16,094) | Perioperative opioids and no new persistent opioid use (n = 223,206) | P‐value |
|---|---|---|---|
| Age at index event (years); Mean (SD) | 51 (17.3) | 45.7 (18.1) | <.001 |
| Female | 8554 (53) | 120,018 (54) | .128 |
| Male | 7111 (44) | 97,124 (44) | .014 |
| Diabetes mellitus | 2300 (14) | 17,073 (8) | <.001 |
| Hypertensive diseases | 5943 (37) | 47,940 (21) | <.001 |
| Anxiety disorders | 3266 (20) | 29,377 (13) | <.001 |
| Mood disorders | 3294 (20) | 27,634 (12) | <.001 |
| Nicotine dependence | 2061 (12) | 16,888 (8) | <.001 |
| Alcohol related disorders | 499 (3) | 3749 (2) | <.001 |
| Dorsalgia | 4768 (30) | 38,249 (17) | <.001 |
| Joint pain | 4939 (31) | 41,981 (19) | <.001 |
| Pain, not elsewhere classified | 2630 (16) | 20,567 (9) | <.001 |
| Myalgia | 1225 (8) | 8808 (4) | <.001 |
| Chest pain | 1586 (10) | 12,069 (5) | <.001 |
| Abdominal and pelvic pain | 4223 (26) | 35,913 (16) | <.001 |
| Headache | 2875 (18) | 24,254 (11) | <.001 |
| Migraine | 1574 (10) | 12,878 (6) | <.001 |
Data are presented as n (%) unless otherwise indicated.
Discussion
The study demonstrates a significant association between perioperative opioid prescribing and the development of persistent opioid use among patients undergoing common otolaryngological procedures. Specifically, parotidectomy had the highest relative risk of persistent opioid use (RR: 2.64), followed by tympanoplasty (RR: 2.01), tonsillectomy (RR: 1.68), septoplasty (RR: 1.55), parathyroidectomy (RR: 1.43), and sinus surgery (RR: 1.26). Rhinoplasty did not show a statistically significant difference in persistent opioid use compared to nonprescribed patients. The notably higher perioperative prescribing rate observed for parotidectomy in our dataset may reflect heterogeneity in case complexity, variation in coding granularity (eg, inability to distinguish superficial from deep procedures), and institutional differences in postoperative pain management within TriNetX, contributing to patterns that may differ from single‐institution clinical experience.
The baseline characteristic analysis in our study further emphasizes the influence of patient‐specific factors on the development of persistent opioid use. Patients who were prescribed perioperative opioids and subsequently developed persistent opioid use were older and had significantly higher rates of comorbidities, including diabetes mellitus, hypertensive diseases, and pre‐existing pain conditions such as dorsalgia, joint pain, and pelvic pain. Mental health conditions, including depression and anxiety, were also more prevalent in this group. These findings suggest that baseline health and psychological factors play a critical role in susceptibility to prolonged opioid use and should be considered in perioperative planning and pain management. These results align with other research that identified pre‐existing comorbidities and mental health conditions as significant risk factors for persistent opioid use. 13
The association between perioperative opioid prescribing and persistent opioid use is well documented across surgical specialties, with rates of approximately 5% to 6% reported even after less invasive procedures. 7 In plastic and reconstructive surgery, 6.6% of patients developed persistent opioid use, with those who filled opioid prescriptions during the perioperative period being significantly more likely to experience persistent and prolonged use compared to those who did not fill perioperative opioid prescriptions. 17 In urological surgery, a study of adolescents and young adults demonstrated that postoperative opioid prescribing increased the risk of persistent opioid use across a range of procedures, with RRs varying from 2.18 for inguinal hernia repair to 17.0 for hypospadias repair. 9 Similarly, a study of opioid‐naive male patients undergoing fertility‐related surgeries found that perioperative opioid prescribing doubled the risk of persistent use. 10 In gynecological surgery, women undergoing posthysterectomy prolapse repair who received opioids within 7 days postoperatively were significantly more likely to develop new opioid dependence, regardless of the surgical approach used. 12 These findings identify perioperative opioid exposure as a key determinant of long‐term opioid use. Furthermore, a meta‐analysis of persistent postoperative opioid use after cardiac surgery identified perioperative opioid prescribing as a significant and modifiable risk factor for prolonged opioid use. 18 Although some procedures in our analysis demonstrated more modest effect sizes, these differences remain clinically meaningful given the high procedural volume and the potential cumulative impact on population‐level opioid exposure. Taken together, our findings extend this evidence to otolaryngological procedures and highlight the need for targeted strategies to minimize unnecessary opioid prescribing.
Importantly, these findings should be interpreted as evidence supporting careful opioid stewardship rather than a directive to eliminate postoperative opioids. Clinicians should use these results to reinforce multimodal analgesic strategies, reassess routine prescribing habits, and identify patients at elevated risk for persistent use, particularly those with pain, mental health, or chronic disease comorbidities. Given that our outcome reflects prescription activity rather than verified consumption, the observed associations underscore the influential role of prescribing decisions themselves and suggest that even modest reductions in routine perioperative opioid exposure may meaningfully decrease persistent use at the population level.
The importance of implementing targeted interventions in otolaryngology is further emphasized by recommendations from the American Academy of Otolaryngology‐Head and Neck Surgery Foundation (AAO‐HNSF). These guidelines advocate for preoperative counseling to set realistic expectations for postoperative pain, the use of multimodal analgesia with nonopioid medications (eg, NSAIDs and acetaminophen) as first‐line treatments, and the judicious prescribing of opioids at the lowest effective dose for the shortest duration. 14 Furthermore, evidence from a study conducted at a tertiary care academic otolaryngology practice reported that over 95% of surgical patients received an opioid prescription, often without tailoring to the specific analgesic needs of different procedures. 19 Addressing these discrepancies through procedure‐specific pain management strategies could reduce unnecessary opioid prescriptions.
Future work should prioritize the development and validation of procedure‐specific prescribing protocols, integration of risk stratification tools into perioperative workflows, and evaluation of multimodal analgesic pathways across diverse otolaryngology practices. Studies incorporating patient‐reported pain outcomes, adherence patterns, and real‐world opioid consumption will be essential to guide evidence‐based prescribing and refine strategies that minimize the risk of persistent opioid use without compromising postoperative pain control.
Limitations
This study has several limitations. First, the use of electronic health record data introduces potential misclassification bias, as procedure and diagnosis coding accuracy (ICD‐10, CPT) varies across institutions and may limit the granularity with which procedural complexity, comorbidities, and clinical context can be assessed. Second, opioid prescription fills serve as a proxy for exposure but do not capture actual consumption, adherence, or access to opioids from nonmedical sources. Our definition of persistent opioid use, based on the presence of an opioid prescription between 3 and 9 months postoperatively, follows methodology used in prior large database work. However, because this measure reflects prescribing activity rather than verified use and may capture prescriptions for conditions unrelated to the index procedure, it may overestimate the absolute incidence of persistent opioid use. Additionally, opioid prescriptions written in the 2 weeks preceding surgery may represent treatment of preexisting pain rather than anticipatory postoperative prescribing. This distinction cannot be reliably differentiated within the TriNetX platform and may introduce limited exposure misclassification; however, prescriptions within this narrow preoperative window are unlikely to meaningfully influence overall effect estimates.
TriNetX does not include information on prescription dosage, quantity, or duration, which limits assessment of prescribing intensity. The platform also does not capture prescriber specialty, and residual confounding is likely despite robust PSM, as data on pain severity, functional status, socioeconomic factors, insurance coverage, and family history of substance use disorders were not available. Moreover, the platform does not support multivariable regression or time‐to‐event analyses, restricting more detailed modeling.
While patients with subsequent surgeries were excluded, some opioid prescriptions may have been intended for unrelated diagnoses or undocumented procedures, introducing outcome misclassification. Lastly, this study draws exclusively from US‐based healthcare systems, and the findings may not be generalizable to health systems with different prescribing practices, regulatory environments, or access to nonopioid analgesia. Despite these limitations, the study leverages a large, nationally representative dataset and rigorous matching methodology to provide important insights into procedure‐specific opioid prescribing and the risk of persistent use following common otolaryngological surgeries.
Conclusion
This study highlights the incidence of persistent opioid use following common otolaryngological procedures and underscores the critical need for targeted interventions to mitigate this risk. By prioritizing multimodal analgesia, improving patient education on postoperative pain expectations, and adopting thoughtful opioid stewardship practices, otolaryngologists can substantially reduce unnecessary opioid exposure and its associated harms. These findings contribute to the growing evidence base on the risks of perioperative opioid prescribing and provide a foundation for procedure‐specific guidelines aimed at improving patient outcomes in otolaryngology.
Author Contributions
Michael Liu: contributed to study conception, study design, data collection, data analysis, drafting, and revising the manuscript; Austin Lee: contributed to study design, data collection, drafting, and revising the manuscript; Salim Hayek: contributed to study conception, oversight of the project, interpretation of results, and revising the manuscript; Shawn Li: contributed to study conception, oversight of the project, interpretation of results, and revising the manuscript.
Disclosures
This research was presented at the Triological Society Annual Meeting at COSM, New Orleans, Louisiana, USA, May 15‐16, 2025, where it received the First Place Poster in General Otolaryngology Award.
Competing interests
None.
Funding source
None.
Supporting information
Supplementary Table 1: Codes used for cohort building.
Supplementary Table 2. Characteristics of tonsillectomy patients who received perioperative opioids and tonsillectomy patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 3. Characteristics of parotidectomy patients who received perioperative opioids and parotidectomy patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 4. Characteristics of tympanoplasty patients who received perioperative opioids and tympanoplasty patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 5. Characteristics of septoplasty patients who received perioperative opioids and septoplasty patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 6. Characteristics of parathyroidectomy patients who received perioperative opioids and parathyroidectomy patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 7. Characteristics of rhinoplasty patients who received perioperative opioids and rhinoplasty patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 8. Characteristics of sinus surgery patients who received perioperative opioids and sinus surgery patients who did not receive perioperative opioids before and after propensity‐score matching.
Acknowledgments
The authors have nothing to report.
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Associated Data
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Supplementary Materials
Supplementary Table 1: Codes used for cohort building.
Supplementary Table 2. Characteristics of tonsillectomy patients who received perioperative opioids and tonsillectomy patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 3. Characteristics of parotidectomy patients who received perioperative opioids and parotidectomy patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 4. Characteristics of tympanoplasty patients who received perioperative opioids and tympanoplasty patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 5. Characteristics of septoplasty patients who received perioperative opioids and septoplasty patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 6. Characteristics of parathyroidectomy patients who received perioperative opioids and parathyroidectomy patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 7. Characteristics of rhinoplasty patients who received perioperative opioids and rhinoplasty patients who did not receive perioperative opioids before and after propensity‐score matching.
Supplementary Table 8. Characteristics of sinus surgery patients who received perioperative opioids and sinus surgery patients who did not receive perioperative opioids before and after propensity‐score matching.