BACKGROUND AND OBJECTIVES

Updated guidelines continue to support watchful waiting as an option for uncomplicated acute otitis media (AOM) and provide explicit diagnostic criteria. To determine treatment prevalence and associated determinants of watchful waiting for AOM in commercially insured pediatric patients.

METHODS

This was a retrospective cohort study using IBM Marketscan Commercial Claims Databases (2005 to 2019) of patients 1 to 12 years old with AOM, without otitis-related complications within 6 months prior, with no tympanostomy tubes, and no other infections around index diagnosis of AOM. We examined monthly antibiotic treatment prevalence (defined as pharmacy dispensing within 3 days of AOM diagnosis) and used multivariable logistic regression models to examine determinants of watchful waiting.

RESULTS

Among 2 176 617 AOM episodes, 77.8% were treated within 3 days. Whereas some clinical characteristics were moderate determinants for watchful waiting, clinician antibiotic prescribing volume and specialty were strong determinants. Low-volume antibiotic prescribers (≥80% of AOM episodes managed with watchful waiting) had 11.61 (95% confidence interval 10.66–12.64) higher odds of using watchful waiting for the index AOM episode than high-volume antibiotic prescribers (≥80% treated). Otolaryngologists were more likely to adopt watchful waiting (odds ratio 5.45, 95% CI 5.21–5.70) than pediatricians, whereas other specialties deferred more commonly to antibiotics.

CONCLUSIONS

Adoption of watchful waiting for management of uncomplicated, nonrecurrent AOM was limited and stagnant across the study period and driven by clinician rather than patient factors. Future work should assess motivators for prescribing and evaluate patient outcomes among clinicians who generally prefer versus reject watchful waiting approaches to guide clinical decision-making.

What’s Known on This Subject

The most recent guidelines for uncomplicated acute otitis media support the option of watchful waiting as a management approach. Research has shown that previous guidelines did not significantly lead to adoption of a watchful waiting approach.

What This Study Adds

Examining 2 176 617 uncomplicated, pediatric acute otitis media episodes, the proportion of treated episodes was around 80% across the study period. The strongest predictors for watchful waiting were clinician specialty and prescribing tendency. Patient clinical and sociodemographic characteristics had limited impact.

It is widely recognized that antibiotics are overprescribed in children. Almost 67 million pediatric antibiotic prescriptions were written in 2013 in the United States with children in the South being more likely to receive an antibiotic compared with those in the West (952 versus 555 prescriptions per 1000 children).1  As many as half of acute respiratory infections are unnecessarily treated with antibiotics.2  Among children, acute otitis media (AOM) is the most common condition for which antibiotics are prescribed.2  Antibiotic therapy for AOM in children yields limited benefit,35  carries a risk of adverse events6  and contributes to the growth of antibiotic resistance.79 

There has been growing support for watchful waiting approaches in the management of AOM. Watchful waiting occurs when a clinician chooses to observe a patient for 2 to 3 days after AOM diagnosis to determine the need for antibiotics. The 2004 American Academy of Pediatrics (AAP) and the American Academy of Family Physicians practice guideline was among the first to promote watchful waiting as a treatment option for AOM in children.10  Similarly, many European AOM guidelines stress a watchful waiting approach.11  Watchful waiting has been shown to decrease antibiotic prescribing rates and caregivers appear to be satisfied with this approach if it is adequately described to them.5,12,13 

Multiple retrospective cohort studies have evaluated the impact of the 2004 guidelines and found no change in antibiotic prescribing in the United States, with up to 85% of cases receiving antibiotics.1417  Similarly, European studies have found that over 80% of AOM episodes are initially treated with antibiotics.1820  Suggested reasons for such high rates of antibiotic use include parental pressure,21,22  differences in clinician training and experience,2325  patient race,26  age, misdiagnosis of AOM,27  and clinicians’ desire to prevent complications of untreated AOM.28 

The most recent AAP AOM treatment guideline published in 2013 was more explicit than the 2004 guideline as to who should receive immediate antibiotics.29  Specifically, the 2013 guideline defined AOM and excluded previous criteria of signs and symptoms that may have resulted in misclassification of upper respiratory tract infections as AOM.30 

The recommendations emphasized 2 landmark studies that used strict diagnostic criteria for AOM in younger children and compared treatment with amoxicillin-clavulanate against placebo.31,32  Hoberman 2011 found no significant difference in initial resolution of symptoms between the 2 groups, whereas Tahtinen 2011 found a significant decrease in treatment failure (defined as no improvement in overall condition, worsening symptoms, or other complications) in the antibiotic group compared with placebo (hazard ratio [HR] 0.38, 95% confidence interval [CI] 0.25–0.59). Both studies also found an increased risk of adverse reactions for the treatment group compared with the placebo group.

Whether the new AOM guidelines resulted in a change in antibiotic prescribing for AOM is unknown. This study aimed to determine the treatment trends of uncomplicated, nonrecurrent AOM in a commercially insured pediatric population in the United States. Moreover, we evaluated determinants of watchful waiting, including clinician prescribing tendency to elucidate what drives AOM treatment decisions.

We established patient cohorts from billing and enrollment records from the IBM MarketScan Commercial Claims Research Databases (2005 to 2019). MarketScan provides longitudinal information on healthcare utilization of a national sample of privately insured employees, retirees, and their dependents in the United States. Data include diagnoses and procedures associated with in- and outpatient encounters as well as outpatient pharmacy medication dispensing claims. This study was reviewed by the University of Florida Institutional Review Board and approved as exempt because of use of deidentified data.

We identified AOM episodes based on the principal diagnosis on outpatient encounters with International Classification of Diseases, Ninth Revision, Clinical Modification (381.0x, 382.0x) or ICD-10-CM (H65.19x, H66.00x). We included AOM episodes of children aged between 1 and 12 years at the time of diagnosis. We required continuous enrollment in comprehensive medical insurance and prescription drug plans for 12 months before and 1 month after each AOM episode. To capture uncomplicated, nonrecurrent AOM episodes, we excluded episodes that were preceded by another encounter with an AOM diagnosis within the previous 6 months. Accordingly, patients could contribute multiple AOM episodes if episodes were spaced more than 6 months apart (Supplemental Fig 3). We also excluded AOM episodes that were preceded by diagnoses of chronic otitis media with effusion, myringotomy, or tympanic membrane perforation in the 6 month lookback period or that were accompanied by a diagnosis of acute otitis externa at the same encounter as the AOM episode or resulted in a prescription fill of a nonoral antibiotic within 7 days. Episodes following tympanostomy tube placement identified via procedure codes in the previous 12 months were also excluded (Supplemental Tables 4 and 5).33,34  Finally, we excluded episodes with a medical in- or outpatient encounter listing an acute infection as a primary or secondary diagnosis within 2 weeks before and 1 week after the index AOM diagnosis to help ensure antibiotic use was for AOM and not another infection (Supplemental Table 6).

Using pharmacy claims, we extracted all oral prescription fills of penicillins, cephalosporins, macrolides, tetracyclines, quinolones, sulfonamides, and other β-lactams within up to 7 days after AOM diagnosis. We grouped episodes into 2 groups based on treatment status. Those with prescription fills within 3 days after AOM diagnosis were assigned to treatment, whereas those with no prescription fills or fills between days 4 to 7 of diagnosis were assigned to watchful waiting. Finally, we excluded any episodes from analysis where a relevant pharmacy claim indicated negative days’ supply, quantity, or copay to ensure accurate classification of each AOM episode as either managed with antibiotics or watchful waiting.

We examined the effect of both patient-level and clinician characteristics on AOM treatment decisions. For patients, we measured age at AOM diagnosis, gender, geographic region, concurrent fever diagnosis at index episode, conditions associated with more severe AOM episodes,3537  insurance plan type (Supplemental Tables 7 and 8), month and year of diagnosis, and healthcare quality ranking of the state of residence. For the latter, we used a healthcare quality variable extracted from the US News Portal (https://www.usnews.com/news/best-states/rankings/health-care) to assign patients to the top 10, bottom 10, or middle state healthcare quality ranking (Supplemental Table 9).38 

Information about the clinician's specialty was ascertained from the medical encounter defining the index AOM episode. We defined clinician prescribing tendency using 2 different methods. First, we restricted the study cohort to AOM episodes that were diagnosed by clinicians with at least 30 AOM episodes in the database. Clinicians who treated at least 80% of all their AOM episodes (excluding the index AOM episode) were considered as high-volume antibiotic prescribers, whereas clinicians whose AOM episodes resulted in 20% or fewer antibiotic prescription fills within 3 days of diagnosis were classified as low-volume antibiotic prescribers.39  Second, to expand our analysis to clinicians with less frequent AOM encounters in the database, we captured each clinician’s previous treatment decision within the identified cohort based on diagnosis date to characterize clinician prescribing tendency, eg, a clinician who treated the previous episode was considered as having a tendency to treat.40 

We plotted the proportion of patients with an AOM episode who filled an antibiotic prescription within 3 days across the study months, where an episode was assigned to a month based on its diagnosis encounter date. We also reported the prevalence of AOM episodes among pediatric patients 1 to 12 years old in each study month to provide context for the overall impact of AOM treatment. Finally, we used multivariable logistic regression models to examine all measured determinants of watchful waiting.

To assess the impact of bilateral infections, we conducted a sensitivity analysis using AOM episodes diagnosed in the ICD-10 era that have more granular ear-specific diagnosis codes (Supplemental Table 10). We then reran our multivariable logistic regression model to examine determinants of watchful waiting, adding this new covariate. All data analyses and management were completed using SAS Version 9.4 (Cary, NC). The secular trend graph was created with R version 4.0.3.

We identified 2 176 617 primary AOM episodes of which 1 693 690 (77.8%) episodes were followed by a prescription fill within 3 days (Fig 1). Among clinical criteria for AOM episode exclusion, history of AOM in the 6-month look-back period was the most common, resulting in exclusion of a third of all episodes (1 618 125, 34.0%). The average age of children contributing an episode was 4 years, and the largest proportion resided in the Southern region of the United States and was enrolled in a restrictive health plan. About two-thirds of episodes were diagnosed by a pediatrician (Table 1). Compared with other clinician types, otolaryngologists were the only clinician type with a distinctly different representation across the treatment groups with 72.2% of episodes assigned to the watchful waiting group. Throughout the study period, we identified 51 637 unique clinicians who treated at least 1 AOM episode and 20 259 clinicians who treated at least 2. Among episodes managed by clinicians who treated the preceding episode within the cohort of AOM episodes in this analysis, 81.6% were treated, whereas only 66.8% were treated when managed by clinicians who had not treated the preceding episode.

FIGURE 1

AOM episode selection.

FIGURE 1

AOM episode selection.

Close modal
TABLE 1

Patient and Clinician Characteristics for AOM Episodes

CharacteristicTreatment, n (%)Watchful Waiting, n (%)
N = 1 693 690N = 482 927
Age in years, mean (SD) 4.6 (3.1) 4.5 (3.1) 
Male gender 871 610 (51.5) 251 564 (52.1) 
Age, y   
 1 310.402 (18.3) 100 433 (20.8) 
 2 244 778 (14.5) 70 924 (14.7) 
 3 218 222 (12.9) 60 658 (12.6) 
 4–6 497 091 (29.4) 131 835 (27.3) 
 7–12 423 197 (25.0) 119 077 (24.7) 
Asthma 38 157 (2.3) 10 297 (2.1) 
Atopic dermatitis 17 901 (1.1) 5388 (1.1) 
Diabetes 922 (0.1) 242 (0.1) 
Failure to thrive 2301 (0.1) 832 (0.2) 
Immune deficiency 1261 (0.1) 464 (0.1) 
Cancer 140 (0.0) 37 (0.0) 
Concurrent fever diagnosis 30 524 (1.8) 4909 (1.0) 
State healthcare quality rank   
 High 215 857 (13.3) 58 498 (12.6) 
 Middle 1 101 181 (67.7) 322 335 (69.3) 
 Low 308 955 (19.0) 84 610 (18.2) 
Region   
 Northeast 305 211 (18.0) 85 521 (17.7) 
 North central 403 210 (23.8) 120 728 (25.0) 
 South 729 199 (43.1) 207 150 (42.9) 
 West 235 500 (13.9) 63 641 (13.2) 
Plan type   
 Restrictive 1 232 517 (75.1) 352 947 (75.5) 
 High deductible 387 615 (23.6) 108 047 (23.1) 
 Comprehensive 21 670 (1.3) 6573 (1.4) 
Clinician type   
 Internal medicine 27 075 (1.8) 6521 (1.5) 
 Emergency medicine 25 445 (1.7) 5936 (1.4) 
 Family practice 188 662 (12.6) 42 911 (9.9) 
 Otolaryngology 16 843 (1.1) 43 798 (10.1) 
 Pediatrics 1 064 665 (70.9) 292 296 (67.3) 
 Clinician, not specified 178 770 (10.5) 43 131 (8.9) 
Episodes restricted to those diagnosed by clinicians who treated ≥1 previous AOM episode 604 718 167 103 
 Episodes managed by clinician who treated previous episode 493 169 (81.6) 111 549 (66.8) 
 Episodes managed by clinician who managed previous episode with watchful waiting 111 549 (18.5) 55 554 (33.2) 
Episodes restricted to those with diagnosing clinicians who managed ≥30 AOM episodes during study period 496 479 129 097 
 Episodes managed by clinicians who treated ≥80% of episodes (high-volume prescriber) 318 441 (64.1) 53 905 (41.8) 
 Episodes managed by clinicians who treated 21% to 79% of episodes (middle-volume prescriber) 177 226 (35.7) 69 268 (53.7) 
 Episodes managed by clinicians who managed ≥80% of episodes with watchful waiting (low-volume prescriber) 812 (0.2) 5924 (4.6) 
CharacteristicTreatment, n (%)Watchful Waiting, n (%)
N = 1 693 690N = 482 927
Age in years, mean (SD) 4.6 (3.1) 4.5 (3.1) 
Male gender 871 610 (51.5) 251 564 (52.1) 
Age, y   
 1 310.402 (18.3) 100 433 (20.8) 
 2 244 778 (14.5) 70 924 (14.7) 
 3 218 222 (12.9) 60 658 (12.6) 
 4–6 497 091 (29.4) 131 835 (27.3) 
 7–12 423 197 (25.0) 119 077 (24.7) 
Asthma 38 157 (2.3) 10 297 (2.1) 
Atopic dermatitis 17 901 (1.1) 5388 (1.1) 
Diabetes 922 (0.1) 242 (0.1) 
Failure to thrive 2301 (0.1) 832 (0.2) 
Immune deficiency 1261 (0.1) 464 (0.1) 
Cancer 140 (0.0) 37 (0.0) 
Concurrent fever diagnosis 30 524 (1.8) 4909 (1.0) 
State healthcare quality rank   
 High 215 857 (13.3) 58 498 (12.6) 
 Middle 1 101 181 (67.7) 322 335 (69.3) 
 Low 308 955 (19.0) 84 610 (18.2) 
Region   
 Northeast 305 211 (18.0) 85 521 (17.7) 
 North central 403 210 (23.8) 120 728 (25.0) 
 South 729 199 (43.1) 207 150 (42.9) 
 West 235 500 (13.9) 63 641 (13.2) 
Plan type   
 Restrictive 1 232 517 (75.1) 352 947 (75.5) 
 High deductible 387 615 (23.6) 108 047 (23.1) 
 Comprehensive 21 670 (1.3) 6573 (1.4) 
Clinician type   
 Internal medicine 27 075 (1.8) 6521 (1.5) 
 Emergency medicine 25 445 (1.7) 5936 (1.4) 
 Family practice 188 662 (12.6) 42 911 (9.9) 
 Otolaryngology 16 843 (1.1) 43 798 (10.1) 
 Pediatrics 1 064 665 (70.9) 292 296 (67.3) 
 Clinician, not specified 178 770 (10.5) 43 131 (8.9) 
Episodes restricted to those diagnosed by clinicians who treated ≥1 previous AOM episode 604 718 167 103 
 Episodes managed by clinician who treated previous episode 493 169 (81.6) 111 549 (66.8) 
 Episodes managed by clinician who managed previous episode with watchful waiting 111 549 (18.5) 55 554 (33.2) 
Episodes restricted to those with diagnosing clinicians who managed ≥30 AOM episodes during study period 496 479 129 097 
 Episodes managed by clinicians who treated ≥80% of episodes (high-volume prescriber) 318 441 (64.1) 53 905 (41.8) 
 Episodes managed by clinicians who treated 21% to 79% of episodes (middle-volume prescriber) 177 226 (35.7) 69 268 (53.7) 
 Episodes managed by clinicians who managed ≥80% of episodes with watchful waiting (low-volume prescriber) 812 (0.2) 5924 (4.6) 

Restricting AOM episodes to those diagnosed by clinicians who managed at least 30 episodes (n = 4377) during the study period resulted in about a fourth (625 576) of all eligible AOM episodes available for analysis. A total of 2261 (51.7%) of these clinicians were categorized as high-volume antibiotic prescribers (ie, treatment of ≥80% of episodes), and 90 (2.1%) were categorized as low-volume antibiotic prescribers (ie, treatment of <20% of episodes). Among episodes assigned to the former clinician prescribing group, 318 441 (85.3%) were treated, whereas this proportion dropped for episodes managed by clinicians with low-volume antibiotic prescribing (71.9% and 12.1% for episodes managed by clinicians who treated between 21% to 79% or 20% or less episodes, respectively).

Treatment prevalence remained consistent throughout the study period with 77.8% and 84.1% of AOM episodes treated in the first and last study month, respectively (Fig 2). Treatment patterns showed some seasonality with a reduced prevalence of antibiotic use during the warmer months. These results were consistent across clinician specialties with otolaryngologists showing less use of antibiotics across the study period (Supplemental Fig 4). AOM episode prevalence showed strong seasonality, but remained similar across the study period, with 49 and 60 episodes per 10 000 pediatric enrollees in February 2006 and 2019, respectively.

FIGURE 2

Trends for AOM episode and treatment prevalence. The monthly prevalence of AOM episodes among all enrolled children aged 1 to 12 years old and the percentage of treated episodes among all uncomplicated AOM episodes between 2006 and 2019 is shown. The vertical dotted lines mark important time points in AOM research and guideline release.

FIGURE 2

Trends for AOM episode and treatment prevalence. The monthly prevalence of AOM episodes among all enrolled children aged 1 to 12 years old and the percentage of treated episodes among all uncomplicated AOM episodes between 2006 and 2019 is shown. The vertical dotted lines mark important time points in AOM research and guideline release.

Close modal

Amoxicillin, cephalosporins, and amoxicillin/clavulanate were the most common antibiotics used for both the treatment group, as well as the small proportion of episodes (2.8%) managed with watchful waiting that resulted in a prescription fill between days 4 and 7 of the AOM diagnosis. Amoxicillin was used more commonly in the treated group (52.6% versus 31.3% in the watchful waiting-treated group). In the treatment group, 1 638 651 (96.8%) episodes had the antibiotic prescription filled on the same day as the AOM diagnosis. To examine whether caregivers may have filled prescriptions immediately even if following watchful waiting recommendations, we assumed that caregivers would be reluctant to pay for a medication that is eventually not needed. We found that most prescriptions did require a copay and the median copay for the watchful waiting-treated group was similar to that for the treatment group (Table 2).

TABLE 2

Characteristics of Treated Episodes

CharacteristicsTreatment, n (%)Watchful Waiting-Treated Between Days 4 and 7 (2.8% of watchful waiting group), n (%)
N = 1 693 690N = 13 506
Amoxicillin 889 991 (52.6) 4232 (31.3) 
Amoxicillin/clavulanate 254 781 (15.0) 2665 (19.7) 
Cephalosporins 362 757 (21.4) 3886 (28.8) 
Macrolides 169 665 (10.0) 2002 (14.8) 
Sulfonamides 16 017 (0.9) 676 (5.0) 
Copay, $, median (IQR) 5.00 (10.00) 6.00 (10.00) 
Zero copay 495 282 (29.2) 3402 (25.2) 
Days’ supply, mean (SD) 9.7 (4.0) 9.6 (3.5) 
CharacteristicsTreatment, n (%)Watchful Waiting-Treated Between Days 4 and 7 (2.8% of watchful waiting group), n (%)
N = 1 693 690N = 13 506
Amoxicillin 889 991 (52.6) 4232 (31.3) 
Amoxicillin/clavulanate 254 781 (15.0) 2665 (19.7) 
Cephalosporins 362 757 (21.4) 3886 (28.8) 
Macrolides 169 665 (10.0) 2002 (14.8) 
Sulfonamides 16 017 (0.9) 676 (5.0) 
Copay, $, median (IQR) 5.00 (10.00) 6.00 (10.00) 
Zero copay 495 282 (29.2) 3402 (25.2) 
Days’ supply, mean (SD) 9.7 (4.0) 9.6 (3.5) 

In our main multivariable analysis restricted to AOM episodes that were managed by clinicians with at least 30 episodes in our datasets, we found that a diagnosis of failure to thrive (odds ratio [OR] 1.47, 95% CI 1.24–1.74) and atopic dermatitis (OR 1.09, 95% CI 1.02–1.16) increased the odds for AOM watchful waiting (Table 3). AOM episodes with a concurrent fever diagnosis were less likely to be managed with watchful waiting than those without (OR 0.63, 95% CI 0.59–0.68) as were those with cancer. Patients seen by otolaryngologists were highly likely to undergo watchful waiting compared with those seen by a pediatrician (OR 5.45, 95% CI 5.21–5.710). Other clinicians were less likely to use watchful waiting compared with pediatricians (internal medicine, OR 0.89 [95% CI 0.83–0.96]; emergency medicine, OR 0.80 [95% CI 0.74–0.87]; or family practice, OR 0.84 [95% CI 0.81–0.86]). Summer month episodes were more likely to result in watchful waiting (Table 3). Looking at yearly trends, we found a lower propensity for watchful waiting for each year between 2014 and 2019 compared with 2006 (eg, for the comparison of 2019 to 2006 OR 0.76, 95% CI 0.73–0.79). Finally, clinicians who treated less than 20% of their episodes (low-volume antibiotic prescribers) were highly likely to use watchful waiting for the evaluated AOM episode when compared with clinicians who treated 80% or more (OR 11.61, 95% 10.66–12.64).

TABLE 3

Factors Associated With Watchful Waiting Versus Immediate Antibiotic Treatment in AOM Management With and Without Consideration of Clinician Prescribing Tendency

All AOM EpisodesRestricted to Episodes Managed by Clinicians With ≥30 Episodes in the Analysis (4377 clinicians)Restricted to Episodes Managed by Clinicians With ≥1 Previous Episode in the Analysis (20 259 clinicians)
CharacteristicOR (95% CI), N = 1 797 681OR (95% CI), N = 542 598OR (95% CI), N = 664 355
Age, y 0.987 (0.986–0.988) 0.987 (0.985–0.989) 0.989 (0.987–0.990) 
Male 1.004 (0.997–1.011) 1.00 (0.98–1.01) 1.00 (0.99–1.01) 
Concurrent rever diagnosis 0.66 (0.63–0.68) 0.63 (0.59–0.68) 0.65 (0.62–0.69) 
Comorbidities    
 Asthma 0.98 (0.96–1.01) 0.95 (0.91–1.00) 0.99 (0.95–1.03) 
 Atopic dermatitis 1.10 (1.07–1.14) 1.09 (1.02–1.16) 1.10 (1.04–1.16) 
 Diabetes 1.08 (0.92–1.27) 0.88 (0.62–1.25) 1.05 (0.80–1.39) 
 Failure to thrive 1.27 (1.16–1.39) 1.47 (1.24–1.74) 1.29 (1.11–1.50) 
 Immune deficiency 1.29 (1.14–1.46) 1.21 (0.96–1.52) 1.29 (1.05–1.59) 
 Cancer 0.69 (0.43–1.09) 0.38 (0.12–1.15) 0.26 (0.08–0.79) 
State healthcare quality ranking    
 High 0.94 (0.93–0.96) 0.98 (0.95–1.01) 0.95 (0.93–0.97) 
 Middle 1.05 (1.04–1.07) 1.01 (0.99–1.03) 1.03 (1.02–1.05) 
 Low Reference Reference Reference 
Region    
 Northeast Reference Reference Reference 
 North Central 1.05 (1.04–1.07) 0.97 (0.95–0.99) 0.96 (0.94–0.98) 
 South 1.00 (0.99–1.01) 0.98 (0.96–1.00) 0.94 (0.92–0.96) 
 West 0.97 (0.96–0.99) 0.97 (0.94–0.99) 0.93 (0.91–0.95) 
Insurance type    
 Comprehensive Reference Reference Reference 
 Restrictive 0.94 (0.91–0.97) 1.01 (0.91–1.12) 0.93 (0.86–1.02) 
 High deductible 0.98 (0.95–1.01) 1.10 (0.99–1.22) 1.01 (0.92–1.10) 
Physician specialty    
 Pediatrician Reference Reference Reference 
 Internal medicine 0.87 (0.84–0.89) 0.89 (0.83–0.96) 0.84 (0.79–0.88) 
 Emergency medicine 0.79 (0.76–0.82) 0.80 (0.74–0.87) 0.77 (0.72–0.82) 
 Family practice 0.80 (0.79–0.81) 0.84 (0.81–0.86) 0.77 (0.76–0.79) 
 Otolaryngology 9.16 (8.99–9.34) 5.45 (5.21–5.70) 7.77 (7.53–8.03) 
 Clinician, not specified 0.87 (0.86–0.88) 0.89 (0.87–0.91) 0.89 (0.87–0.90) 
Month    
 January Reference Reference Reference 
 February 0.93 (0.92–0.95) 0.94 (0.91–0.97) 0.94 (0.92–0.96) 
 March 1.02 (1.01–1.04) 1.03 (1.00–1.06) 1.03 (1.01–1.06) 
 April 1.08 (1.07–1.10) 1.08 (1.05–1.12) 1.10 (1.07–1.13) 
 May 1.10 (1.08–1.12) 1.11 (1.07–1.14) 1.12 (1.08–1.15) 
 June 1.25 (1.23–1.27) 1.23 (1.19–1.27) 1.25 (1.21–1.29) 
 July 1.36 (1.33–1.38) 1.37 (1.32–1.42) 1.36 (1.32–1.41) 
 August 1.22 (1.19–1.24) 1.23 (1.19–1.28) 1.23 (1.20–1.27) 
 September 1.05 (1.03–1.07) 1.06 (1.02–1.09) 1.06 (1.03–1.10) 
 October 1.01 (0.99–1.02) 1.00 (0.97–1.03) 1.02 (0.99–1.05) 
 November 0.93 (0.91–0.94) 0.92 (0.89–0.95) 0.95 (0.92–0.97) 
 December 0.88 (0.87–0.90) 0.88 (0.85–0.91) 0.90 (0.87–0.92) 
Year    
 2006 Reference Reference Reference 
 2007 1.04 (1.02–1.06) 1.05 (1.01–1.09) 1.06 (1.02–1.09) 
 2008 1.05 (1.03–1.07) 1.04 (1.01–1.08) 1.01 (0.98–1.04) 
 2009 1.04 (1.02–1.06) 1.01 (0.98–1.04) 0.98 (0.95–1.01) 
 2010 1.08 (1.06–1.10) 1.06 (1.02–1.10) 1.03 (1.00–1.06) 
 2011 1.06 (1.04–1.08) 1.03 (1.00–1.07) 1.00 (0.97–1.03) 
 2012 1.04 (1.02–1.06) 0.99 (0.96–1.03) 0.98 (0.95–1.01) 
 2013 1.00 (0.98–1.02) 0.98 (0.94–1.02) 0.95 (0.92–0.98) 
 2014 0.90 (0.88–0.92) 0.85 (0.81–0.88) 0.83 (0.80–0.86) 
 2015 0.82 (0.80–0.84) 0.81 (0.78–0.85) 0.81 (0.78–0.84) 
 2016 0.78 (0.76–0.79) 0.80 (0.78–0.83) 0.79 (0.77–0.82) 
 2017 0.74 (0.73–0.76) 0.76 (0.73–0.79) 0.75 (0.72–0.77) 
 2018 0.76 (0.74–0.78) 0.76 (0.73–0.79) 0.76 (0.73–0.79) 
 2019 0.77 (0.75–0.78) 0.76 (0.73–0.79) 0.76 (0.73–0.78) 
Prescribing tendency definition    
 ≤20% treated (low-volume prescriber) — 11.61 (10.66–12.64) — 
 21% to 79% treated (middle-volume prescriber) — 2.10 (2.07–2.12) — 
 ≥80% treated (high-volume prescriber) — Reference — 
 Preceding episode not treated versus treated — — 1.83 (1.80–1.85) 
All AOM EpisodesRestricted to Episodes Managed by Clinicians With ≥30 Episodes in the Analysis (4377 clinicians)Restricted to Episodes Managed by Clinicians With ≥1 Previous Episode in the Analysis (20 259 clinicians)
CharacteristicOR (95% CI), N = 1 797 681OR (95% CI), N = 542 598OR (95% CI), N = 664 355
Age, y 0.987 (0.986–0.988) 0.987 (0.985–0.989) 0.989 (0.987–0.990) 
Male 1.004 (0.997–1.011) 1.00 (0.98–1.01) 1.00 (0.99–1.01) 
Concurrent rever diagnosis 0.66 (0.63–0.68) 0.63 (0.59–0.68) 0.65 (0.62–0.69) 
Comorbidities    
 Asthma 0.98 (0.96–1.01) 0.95 (0.91–1.00) 0.99 (0.95–1.03) 
 Atopic dermatitis 1.10 (1.07–1.14) 1.09 (1.02–1.16) 1.10 (1.04–1.16) 
 Diabetes 1.08 (0.92–1.27) 0.88 (0.62–1.25) 1.05 (0.80–1.39) 
 Failure to thrive 1.27 (1.16–1.39) 1.47 (1.24–1.74) 1.29 (1.11–1.50) 
 Immune deficiency 1.29 (1.14–1.46) 1.21 (0.96–1.52) 1.29 (1.05–1.59) 
 Cancer 0.69 (0.43–1.09) 0.38 (0.12–1.15) 0.26 (0.08–0.79) 
State healthcare quality ranking    
 High 0.94 (0.93–0.96) 0.98 (0.95–1.01) 0.95 (0.93–0.97) 
 Middle 1.05 (1.04–1.07) 1.01 (0.99–1.03) 1.03 (1.02–1.05) 
 Low Reference Reference Reference 
Region    
 Northeast Reference Reference Reference 
 North Central 1.05 (1.04–1.07) 0.97 (0.95–0.99) 0.96 (0.94–0.98) 
 South 1.00 (0.99–1.01) 0.98 (0.96–1.00) 0.94 (0.92–0.96) 
 West 0.97 (0.96–0.99) 0.97 (0.94–0.99) 0.93 (0.91–0.95) 
Insurance type    
 Comprehensive Reference Reference Reference 
 Restrictive 0.94 (0.91–0.97) 1.01 (0.91–1.12) 0.93 (0.86–1.02) 
 High deductible 0.98 (0.95–1.01) 1.10 (0.99–1.22) 1.01 (0.92–1.10) 
Physician specialty    
 Pediatrician Reference Reference Reference 
 Internal medicine 0.87 (0.84–0.89) 0.89 (0.83–0.96) 0.84 (0.79–0.88) 
 Emergency medicine 0.79 (0.76–0.82) 0.80 (0.74–0.87) 0.77 (0.72–0.82) 
 Family practice 0.80 (0.79–0.81) 0.84 (0.81–0.86) 0.77 (0.76–0.79) 
 Otolaryngology 9.16 (8.99–9.34) 5.45 (5.21–5.70) 7.77 (7.53–8.03) 
 Clinician, not specified 0.87 (0.86–0.88) 0.89 (0.87–0.91) 0.89 (0.87–0.90) 
Month    
 January Reference Reference Reference 
 February 0.93 (0.92–0.95) 0.94 (0.91–0.97) 0.94 (0.92–0.96) 
 March 1.02 (1.01–1.04) 1.03 (1.00–1.06) 1.03 (1.01–1.06) 
 April 1.08 (1.07–1.10) 1.08 (1.05–1.12) 1.10 (1.07–1.13) 
 May 1.10 (1.08–1.12) 1.11 (1.07–1.14) 1.12 (1.08–1.15) 
 June 1.25 (1.23–1.27) 1.23 (1.19–1.27) 1.25 (1.21–1.29) 
 July 1.36 (1.33–1.38) 1.37 (1.32–1.42) 1.36 (1.32–1.41) 
 August 1.22 (1.19–1.24) 1.23 (1.19–1.28) 1.23 (1.20–1.27) 
 September 1.05 (1.03–1.07) 1.06 (1.02–1.09) 1.06 (1.03–1.10) 
 October 1.01 (0.99–1.02) 1.00 (0.97–1.03) 1.02 (0.99–1.05) 
 November 0.93 (0.91–0.94) 0.92 (0.89–0.95) 0.95 (0.92–0.97) 
 December 0.88 (0.87–0.90) 0.88 (0.85–0.91) 0.90 (0.87–0.92) 
Year    
 2006 Reference Reference Reference 
 2007 1.04 (1.02–1.06) 1.05 (1.01–1.09) 1.06 (1.02–1.09) 
 2008 1.05 (1.03–1.07) 1.04 (1.01–1.08) 1.01 (0.98–1.04) 
 2009 1.04 (1.02–1.06) 1.01 (0.98–1.04) 0.98 (0.95–1.01) 
 2010 1.08 (1.06–1.10) 1.06 (1.02–1.10) 1.03 (1.00–1.06) 
 2011 1.06 (1.04–1.08) 1.03 (1.00–1.07) 1.00 (0.97–1.03) 
 2012 1.04 (1.02–1.06) 0.99 (0.96–1.03) 0.98 (0.95–1.01) 
 2013 1.00 (0.98–1.02) 0.98 (0.94–1.02) 0.95 (0.92–0.98) 
 2014 0.90 (0.88–0.92) 0.85 (0.81–0.88) 0.83 (0.80–0.86) 
 2015 0.82 (0.80–0.84) 0.81 (0.78–0.85) 0.81 (0.78–0.84) 
 2016 0.78 (0.76–0.79) 0.80 (0.78–0.83) 0.79 (0.77–0.82) 
 2017 0.74 (0.73–0.76) 0.76 (0.73–0.79) 0.75 (0.72–0.77) 
 2018 0.76 (0.74–0.78) 0.76 (0.73–0.79) 0.76 (0.73–0.79) 
 2019 0.77 (0.75–0.78) 0.76 (0.73–0.79) 0.76 (0.73–0.78) 
Prescribing tendency definition    
 ≤20% treated (low-volume prescriber) — 11.61 (10.66–12.64) — 
 21% to 79% treated (middle-volume prescriber) — 2.10 (2.07–2.12) — 
 ≥80% treated (high-volume prescriber) — Reference — 
 Preceding episode not treated versus treated — — 1.83 (1.80–1.85) 

—, not applicable; Reference, reference level within each categorical variable in the regression model.

Defining prescribing tendency based on only the treatment decision for the preceding AOM episode within the cohort yielded similar results, including the seasonal nature of treatment as well as retention of prescribing tendency as the strongest predictor for watchful waiting when comparing clinicians who did not treat the previous episode to clinicians who did (OR 1.83, 95% CI 1.80–1.85, Table 3). When using all available AOM episodes for our analysis, omitting clinician prescribing tendency as a covariate, the effect of clinician specialty increased, indicating an association between specialty and prescribing tendency.Otolaryngologists when compared with pediatricians were highly likely to use watchful waiting (OR 9.16, 95% 8.99–9.34). Other clinicians were less likely to adopt watchful waiting compared with pediatricians (internal medicine, OR 0.87 [95% CI 0.84–0.89]; emergency medicine, OR 0.79 [95% CI 0.76–0.82]; or family practice, OR 0.80 [95% CI 0.79–0.81]). Our sensitivity analysis yielded similar results for prescribing tendency and clinician specialty (specifically otolaryngology) as the strongest predictors of watchful waiting (Supplemental Table 11). Compared with AOM episodes explicitly diagnosed as unilateral, bilateral infections were more commonly managed with watchful waiting (OR 1.29, 95% CI 1.25–1.33), as were AOM infections with unspecific coding (OR 1.92, 95% CI 1.81–2.04).

This study provides updated evidence on the treatment of AOM relevant to national efforts to curtail unnecessary antibiotic prescribing, including the possible impact of AAP’s AOM guideline that was released in 2013. This guideline updated diagnostic criteria for AOM and provided explicit criteria for immediate antibiotic treatment of AOM in children. For nonsevere cases, the guideline gave the option of watchful waiting as a treatment approach as long as follow-up care can be provided, analgesics are offered for pain management, and there is shared decision making with caregivers.30  These recommendations were based on various clinical trials with strict diagnostic criteria for AOM that compared antibiotics to placebo and that revealed a modest benefit of antibiotics for symptom resolution and an increased risk of adverse reactions.31,32  Subsequent studies and meta-analyses have also shown minimal benefit with immediate treatment of AOM.41,42 

Three key findings of our study are noteworthy: First, we found a small increase in treatment prevalence across the study period, with 84.1% of uncomplicated, nonrecurrent AOM episodes followed by an antibiotic prescription fill within 3 days in the last study month. Second, the strongest predictors for watchful waiting were clinician specialty and clinician prescribing tendency, even if tendency was loosely defined as the most recent preceding treatment decision. In contrast, patient demographics and clinical characteristics played a minor role. Third, only a small portion of patients (2.8%) who appeared to be managed with a watchful waiting approach filled an antibiotic prescription after the first 3 days of diagnosis.

This third finding strongly supports the self-limited nature of most AOM episodes and is consistent with an Italian study that reported 5.6% of patients fill a prescription after the watchful waiting period.20  Other studies have similarly concluded that the majority of treated AOM episodes could have been managed with watchful waiting.4,5,4346  When patients in our watchful waiting group ultimately filled an antibiotic prescription, it was less often the first-line agent, amoxicillin, than patients who received immediate antibiotic therapy. We suspect that second-line agents were more often favored in this select group as the episodes were de facto not self-limited.

Our findings regarding the persistent tendency for immediate antibiotic treatment are consistent with previous studies, which have shown no effect of previously released guidelines.19,20  Recent studies from Europe and Israel have reported up to 80% of AOM episodes are treated immediately with antibiotics, comparable to our findings.18,19,4749  Although certain clinical scenarios might have justified immediate antibiotic treatment, we intentionally excluded a broad range of risk factors for AOM recurrence and complications. This should have biased the study population to those with less need for immediate antibiotic treatment, resulting in an underestimate of the tendency for immediate antibiotic prescribing in actual practice. Our study, considered alone and jointly with reports from other countries, suggests that current guidelines need to be revisited to effectively reduce unnecessary antibiotic use in AOM.

Patient factors dictate the considerations for AOM management in the AAP guideline and the clinical trials from which it is derived. However, patient factors appeared to not be the primary drivers of antibiotic prescribing for nonrecurrent uncomplicated AOM in our study. For example, fever and bilateral AOM were stressed in the AAP guideline as criteria to support treatment with antibiotics. Though fever was associated with a greater likelihood for antibiotic treatment, bilaterality was associated with a greater chance of watchful waiting. Similarly, failure to thrive, immune deficiencies, and many comorbidities that might exacerbate AOM severity were either associated with a greater chance of watchful waiting or had little influence on whether an AOM episode was treated with antibiotics.

In contrast, factors not directly related to the patient were tightly linked to treatment tendency. For example, AOM in the summer months was much more likely to be treated with watchful waiting, despite the lack of association between season and AOM severity. The impact of clinician factors, both specialty and clinician prescribing tendency, was remarkable because of how much stronger these factors were than patient factors. The severity of a prior AOM case should not predict AOM severity in a subsequent patient or the need for antibiotic treatment. Thus, clinician practice patterns tend to drive nonsevere AOM management more than patient factors. In other words, a patient’s probability to receive antibiotics is more dependent on which clinician they see rather than the patient’s clinical characteristics.

Practice patterns, particularly for upper respiratory tract infections, are well-known to differ by specialty.2,5052  Both otolaryngologists and pediatricians may have more experience evaluating children’s ears than other primary care providers, which could explain their more judicious use of antibiotics and is consistent with previous reports.23,24  The diverse prescribing practices across clinical specialties may also indicate that the AAP guidelines have not been sufficiently disseminated to all clinicians who regularly treat AOM episodes. Up to 40% of identified AOM episodes were managed by specialties other than pediatricians. This may require broader dissemination of best practices that have successfully reduced antibiotic use.5356 

Parental factors, concerns about complications, and necessary follow-up care have been reported as major barriers to adopting watchful waiting.28  Further research should evaluate what factors determine the adoption of watchful waiting, especially among those clinicians who appear to manage the majority of cases with this approach. Importantly, comparison of AOM management outcomes between clinicians who tend to prefer versus reject watchful waiting in real-world clinical practice would deliver critical evidence that, if supportive, may offer the necessary reassurance that watchful waiting carries acceptable risk-benefit.

We acknowledge several limitations. First, the study cohort, drawn from a nationally representative sample of commercially insured patients in the United States, is not generalizable to publicly insured patients who may be seen by different clinicians and have different AOM risk profiles. Second, our attempt to focus on patients with uncomplicated AOM may have been overly restrictive. For example, recurrent uncomplicated AOM (commonly defined as 3 episodes within 6 months) is common and not an indication for treatment on its own, but such cases were excluded in this study to focus on the greatest opportunities to implement watchful waiting. On the other hand, we may not have been able to capture all risk factor constellations (eg, overall disease history and AOM presentation or socio-demographic factors, including parental pressure28 ) that a clinician may have considered to justify treatment. Third, our results rely on the assumption that the diagnosing clinician also wrote the prescription, which we consider probable because we eliminated AOM episodes that overlapped with other acute infections. We also rely on caregivers following instructions to wait to fill the prescription if it was written within a watchful waiting approach. One study found 27% of parents report noncompliance with watchful waiting when a prescription is provided at diagnosis57 ; therefore, our reported prevalence of immediate treatment may be an overestimate. However, we found that most patients paid out of pocket for their prescription, which may reduce caregivers’ willingness to obtain a medication that may not be needed. Additionally, we were unable to account for patients who received their prescriptions for a discounted price without charging their insurance, which may not be captured in claims data. Fourth, our database did not allow distinction between observation as the medical practice that defines watchful waiting and delayed prescribing or delayed prescription fills, which may occur for other reasons. Finally, this study was not aimed at assessing the impact of the new AOM guidelines on diagnostic accuracy. Assessment of diagnostic accuracy would require more clinical detail than available in claims data and assessment of trends need to consider overall secular changes in infectious disease epidemiology and other factors, such as increased uptake of pneumococcal vaccination.58,59 

We found no impact of the 2013 AAP guidelines on the management of uncomplicated, nonrecurrent AOM, which supports the option of watchful waiting before an antibiotic is used. The strongest predictor of watchful waiting was clinician prescribing tendency and clinician specialty, with limited impact of examined patient characteristics on treatment decisions. Given our findings, further research is needed to understand what motivates clinicians to adopt watchful awaiting approaches and how their patient outcomes compare with those who defer to antibiotic use.

We thank Shailina Keshwani for her assistance with data visualization.

Dr Smolinski conceptualized and designed the study, conducted the analyses, interpreted the data, and drafted the initial manuscript; Drs Winterstein and Antonelli conceptualized and designed the study, interpreted the data, and critically reviewed the manuscript for important intellectual content; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

CONFLICT OF INTEREST DISCLOSURES: Dr Winterstein has received research funding from Merck, Sharpe and Dohme, the National Institute of Health, AHRQ, PCORI, the US Food and Drug Administration, and the state of Florida and received honoraria of consultant from Arbor Pharmaceuticals and Genentech Inc, none of which is related to this work; Dr Antonelli has received research funding from Next Science, unrelated to this work; and Dr Smolinski has no conflicts of interest to disclose.

     
  • AAP

    American Academy of Pediatrics

  •  
  • AOM

    acute otitis media

1
Fleming-Dutra
KE
,
Demirjian
A
,
Bartoces
M
,
Roberts
RM
,
Taylor
TH
,
Hicks
LA
.
Variations in antibiotic and azithromycin prescribing for children by geography and specialty—United States, 2013
.
The Pediatr Infect Dis J
.
2018
;
37
(
1
):
52
58
2
Fleming-Dutra
KE
,
Hersh
AL
,
Shapiro
DJ
, et al
.
Prevalence of inappropriate antibiotic prescriptions among US ambulatory care visits, 2010-2011
.
JAMA
.
2016
;
315
(
17
):
1864
1873
3
McCormick
DP
,
Chonmaitree
T
,
Pittman
C
, et al
.
Nonsevere acute otitis media: a clinical trial comparing outcomes of watchful waiting versus immediate antibiotic treatment
.
Pediatrics
.
2005
;
115
(
6
):
1455
1465
4
Little
P
,
Gould
C
,
Williamson
I
,
Moore
M
,
Warner
G
,
Dunleavey
J
.
Pragmatic randomised controlled trial of two prescribing strategies for childhood acute otitis media
.
BMJ
.
2001
;
322
(
7282
):
336
342
5
Chao
JH
,
Kunkov
S
,
Reyes
LB
,
Lichten
S
,
Crain
EF
.
Comparison of two approaches to observation therapy for acute otitis media in the emergency department
.
Pediatrics
.
2008
;
121
(
5
):
e1352
e1356
6
Gerber
JS
,
Ross
RK
,
Bryan
M
, et al
.
Association of broad- vs narrow-spectrum antibiotics with treatment failure, adverse events, and quality of life in children with acute respiratory tract infections
.
JAMA
.
2017
;
318
(
23
):
2325
2336
7
Shehab
N
,
Patel
PR
,
Srinivasan
A
,
Budnitz
DS
.
Emergency department visits for antibiotic-associated adverse events
.
Clin Infect Dis
.
2008
;
47
(
6
):
735
743
8
Costelloe
C
,
Metcalfe
C
,
Lovering
A
,
Mant
D
,
Hay
AD
.
Effect of antibiotic prescribing in primary care on antimicrobial resistance in individual patients: systematic review and meta-analysis
.
BMJ
.
2010
;
340
:
c2096
9
Cohen
AL
,
Budnitz
DS
,
Weidenbach
KN
, et al
.
National surveillance of emergency department visits for outpatient adverse drug events in children and adolescents
.
The Journal of Pediatrics
.
2008
;
152
(
3
):
416
421
10
American Academy of Pediatrics Subcommittee on Management of Acute O
.
Diagnosis and management of acute otitis media
.
Pediatrics
.
2004
;
113
(
5
):
1451
1465
11
Suzuki
HG
,
Dewez
JE
,
Nijman
RG
,
Yeung
S
.
Clinical practice guidelines for acute otitis media in children: a systematic review and appraisal of European national guidelines
.
BMJ Open
.
2020
;
10
(
5
):
e035343
12
Finkelstein
J
,
Stille
C
,
Rifas-Shiman
S
,
Goldmann
D
.
Watchful waiting for acute otitis media: are parents and physicians ready?
Pediatrics
.
2005
;
115
(
6
):
1466
1473
13
Merenstein
D
,
Diener-West
M
,
Krist
A
,
Pinneger
M
,
Cooper
LA
.
An assessment of the shared-decision model in parents of children with acute otitis media
.
Pediatrics
.
2005
;
116
(
6
):
1267
1275
14
Coco
A
,
Vernacchio
L
,
Horst
M
,
Anderson
A
.
Management of acute otitis media after publication of the 2004 AAP and AAFP clinical practice guideline
.
Pediatrics
.
2010
;
125
(
2
):
214
220
15
Vernacchio
L
,
Vezina
RM
,
Mitchell
AA
.
Knowledge and practices relating to the 2004 acute otitis media clinical practice guideline: a survey of practicing physicians
.
Pediatr Infect Dis J
.
2006
;
25
(
5
):
385
389
16
Vernacchio
L
,
Vezina
RM
,
Mitchell
AA
.
Management of acute otitis media by primary care physicians: trends since the release of the 2004 American Academy of Pediatrics/American Academy of Family Physicians clinical practice guideline
.
Pediatrics
.
2007
;
120
(
2
):
281
287
17
McGrath
LJ
,
Becker-Dreps
S
,
Pate
V
,
Brookhart
MA
.
Trends in antibiotic treatment of acute otitis media and treatment failure in children, 2000–2011
.
PLoS One
.
2013
;
8
(
12
):
e81210
18
Levy
C
,
Pereira
M
,
Guedj
R
, et al
.
Impact of 2011 French guidelines on antibiotic prescription for acute otitis media in infants
.
Med Mal Infect
.
2014
;
44
(
3
):
102
106
19
Palma
S
,
Rosafio
C
,
Del Giovane
C
, et al
.
The impact of the Italian guidelines on antibiotic prescription practices for acute otitis media in a paediatric emergency setting
.
Ital J Pediatr
.
2015
;
41
:
37
20
Barbieri
E
,
Donà
D
,
Cantarutti
A
, et al
.
Antibiotic prescriptions in acute otitis media and pharyngitis in Italian pediatric outpatients
.
Ital J Pediatr
.
2019
;
45
(
1
):
103
21
Coxeter
PD
,
Mar
CD
,
Hoffmann
TC
.
Parents' expectations and experiences of antibiotics for acute respiratory infections in primary care
.
Ann Fam Med
.
2017
;
15
(
2
):
149
154
22
Hansen
MP
,
Howlett
J
,
Del Mar
C
,
Hoffmann
TC
.
Parents' beliefs and knowledge about the management of acute otitis media: a qualitative study
.
BMC Fam Pract
.
2015
;
16
:
82
23
Nadeem Ahmed
M
,
Muyot
MM
,
Begum
S
,
Smith
P
,
Little
C
,
Windemuller
FJ
.
Antibiotic prescription pattern for viral respiratory illness in emergency room and ambulatory care settings
.
Clin Pediatr (Phila)
.
2010
;
49
(
6
):
542
547
24
Frost
HM
,
McLean
HQ
,
Chow
BDW
.
Variability in antibiotic prescribing for upper respiratory illnesses by provider specialty
.
J Pediatr
.
2018
;
203
:
76
85.e78
25
Pulcini
C
,
Lions
C
,
Ventelou
B
,
Verger
P
.
Indicators show differences in antibiotic use between general practitioners and paediatricians
.
Eur J Clinl Microbiol Infect Dis
.
2013
;
32
(
7
):
929
935
26
Gerber
JS
,
Prasad
PA
,
Localio
AR
, et al
.
Racial differences in antibiotic prescribing by primary care pediatricians
.
Pediatrics
.
2013
;
131
(
4
):
677
684
27
Sundvall
P-D
,
Papachristodoulou
CE
,
Nordeman
L
.
Diagnostic methods for acute otitis media in 1 to 12 year old children: a cross sectional study in primary health care
.
BMC Fam Pract
.
2019
;
20
(
1
):
127
28
Bourgeois
T
,
Griffith
C
,
Johnson
E-C
,
Leblanc
B
,
Melancon
B
.
Barriers to current guidelines in the management of pediatric acute otitis media
.
Journal of Pediatrics and Pediatric Medicine
.
2019
;
3
(
3
)
29
Lieberthal
AS
.
Revised AOM guideline emphasizes accurate diagnosis
.
AAP News
.
2013
;
34
(
3
):
4
30
Lieberthal
AS
,
Carroll
AE
,
Chonmaitree
T
, et al
.
The diagnosis and management of acute otitis media
.
Pediatrics
.
2013
;
131
(
3
):
e964
e999
31
Hoberman
A
,
Paradise
JL
,
Rockette
HE
, et al
.
Treatment of acute otitis media in children under 2 years of age
.
N Engl J Med
.
2011
;
364
(
2
):
105
115
32
Tähtinen
PA
,
Laine
MK
,
Huovinen
P
,
Jalava
J
,
Ruuskanen
O
,
Ruohola
A
.
A placebo-controlled trial of antimicrobial treatment for acute otitis media
.
N Engl J Med
.
2011
;
364
(
2
):
116
126
33
Arason
VA
,
Sigurdsson
JA
,
Kristinsson
KG
,
Getz
L
,
Gudmundsson
S
.
Otitis media, tympanostomy tube placement, and use of antibiotics. cross-sectional community study repeated after five years
.
Scand J Prim Health Care
.
2005
;
23
(
3
):
184
191
34
Weigel
MT
,
Parker
MY
,
Goldsmith
MM
,
Postma
DS
,
Pillsbury
HC
.
A prospective randomized study of four commonly used tympanostomy tubes
.
The Laryngoscope
.
1989
;
99
(
3
):
252
256
35
Uhari
M
,
Mäntysaari
K
,
Niemelä
M
.
A meta-analytic review of the risk factors for acute otitis media
.
Clin Infect Dis
.
1996
;
22
(
6
):
1079
1083
36
Yiengprugsawan
V
,
Hogan
A
.
Ear infection and its associated risk factors, comorbidity, and health service use in Australian children
.
Int J Pediatr
.
2013
:
963132
37
Kong
K
,
Coates
HLC
.
Natural history, definitions, risk factors and burden of otitis media
.
Med J of Aust
.
2009
;
191
(
suppl 9
):
S39
S43
38
US News
.
Best states for healthcare, US News best states
.
39
Schneeweiss
S
,
Seeger
JD
,
Landon
J
,
Walker
AM
.
Aprotinin during coronary-artery bypass grafting and risk of death
.
N Engl J Med
.
2008
;
358
(
8
):
771
783
40
Brookhart
MA
,
Wang
PS
,
Solomon
DH
,
Schneeweiss
S
.
Evaluating short-term drug effects using a physician-specific prescribing preference as an instrumental variable
.
Epidemiology
.
2006
;
17
(
3
):
268
275
41
Venekamp
RP
,
Sanders
SL
,
Glasziou
PP
,
Del Mar
CB
,
Rovers
MM
.
Antibiotics for acute otitis media in children
.
Cochrane Database Syst Rev
.
2015
; (
6
):
CD000219
42
Holm
NH
,
Rusan
M
,
Ovesen
T
.
Acute otitis media and antibiotics - a systematic review
.
Dan Med J
.
2020
;
67
(
11
):
A04200272
43
Sun
D
,
McCarthy
TJ
,
Liberman
DB
.
Cost-effectiveness of watchful waiting in acute otitis media
.
Pediatrics
.
2017
;
139
(
4
):
e20163086
44
Herigon
JC
,
Mousseau
S
,
Kimia
A
,
Hatoun
J
,
Vernacchio
L
.
1473. guideline adherence in pediatric ambulatory visits for acute otitis media
.
Open Forum Infect Dis
.
2020
;
7
(
suppl 1
):
S738
45
Siegel
RM
,
Kiely
M
,
Bien
JP
, et al
.
Treatment of otitis media with observation and a safety-net antibiotic prescription
.
Pediatrics
.
2003
;
112
(
3 Pt 1
):
527
531
46
Mas-Dalmau
G
,
Villanueva López
C
,
Gorrotxategi Gorrotxategi
P
, et al
.
Delayed antibiotic prescription for children with respiratory infections: a randomized trial
.
Pediatrics
.
2021
;
147
(
3
):
e20201323
47
Shviro-Roseman
N
,
Reuveni
H
,
Gazala
E
,
Leibovitz
E
.
Adherence to acute otitis media treatment guidelines among primary health care providers in Israel
.
Braz J Infect Dis
.
2014
;
18
(
4
):
355
359
48
Pouwels
KB
,
Dolk
FCK
,
Smith
DRM
,
Robotham
JV
,
Smieszek
T
.
Actual versus 'ideal' antibiotic prescribing for common conditions in English primary care
.
Journal Antimicrob Chemoth
.
2018
;
73
(
suppl_2
):
19
26
49
Célind
J
,
Södermark
L
,
Hjalmarson
O
.
Adherence to treatment guidelines for acute otitis media in children. the necessity of an effective strategy of guideline implementation
.
Int J Pediatr Otorhinolaryngol
.
2014
;
78
(
7
):
1128
1132
50
Newton
L
,
Kotowski
A
,
Grinker
M
,
Chun
R
.
Diagnosis and management of pediatric sinusitis: a survey of primary care, otolaryngology and urgent care providers
.
Int J Pediatr Otorhinolaryngol
.
2018
;
108
:
163
167
51
Ference
EH
,
Min
J-Y
,
Chandra
RK
, et al
.
Antibiotic prescribing by physicians versus nurse practitioners for pediatric upper respiratory infections
.
Ann Oto, Rhinol Laryngol
.
2016
;
125
(
12
):
982
991
52
Smith
SS
,
Kern
RC
,
Chandra
RK
,
Tan
BK
,
Evans
CT
.
Variations in antibiotic prescribing of acute rhinosinusitis in United States ambulatory settings
.
Otolaryngol Head Neck Surg
.
2013
;
148
(
5
):
852
859
53
Norlin
C
,
Fleming-Dutra
K
,
Mapp
J
, et al
.
A learning collaborative to improve antibiotic prescribing in primary care pediatric practices
.
Clin Pediatr (Phila)
.
2021
;
60
(
4–5
):
230
240
54
Frost
HM
,
Monti
JD
,
Andersen
LM
, et al
.
Improving delayed antibiotic prescribing for acute otitis media
.
Pediatrics
.
2021
;
147
(
6
):
e2020026062
55
Sun
D
,
Rivas-Lopez
V
,
Liberman
DB
.
A multifaceted quality improvement intervention to improve watchful waiting in acute otitis media management
.
Pediatr Qual Saf
.
2019
;
4
(
3
):
e177
56
Sanchez
GV
,
Fleming-Dutra
KE
,
Roberts
RM
,
Hicks
LA
.
Core elements of outpatient antibiotic stewardship
.
MMWR Recomm Rep
.
2016
;
65
(
6
):
1
12
57
MacGeorge
EL
,
Caldes
EP
,
Smith
RA
,
Hackman
NM
,
San Jose
A
.
Reducing unwarranted antibiotic use for pediatric acute otitis media: the influence of physicians' explanation and instruction on parent compliance with ‘watchful waiting’
.
Journal of Applied Communication Research
.
2017
;
45
(
3
):
333
345
58
Kaur
R
,
Casey
JR
,
Pichichero
ME
.
Emerging streptococcus pneumoniae strains colonizing the nasopharynx in children after 13-valent pneumococcal conjugate vaccination in comparison to the 7-valent era, 2006-2015
.
Pediatr Infect Dis J
.
2016
;
35
(
8
):
901
906
59
Casey
JR
,
Adlowitz
DG
,
Pichichero
ME
.
New patterns in the otopathogens causing acute otitis media six to eight years after introduction of pneumococcal conjugate vaccine
.
Pediatr Infect Dis J
.
2010
;
29
(
4
):
304
309

Supplementary data