Analyzing Nationwide Treatment Delays Among Children With Frequent Ear Infections

Introduction: Ear infections are a leading cause of pediatric illness in the US and require prompt attention, yet logistical delays to treating frequent ear infections (FEI) among children are understudied. We used national survey data to study how logistical hurdles like wait times and appointment availability create treatment delays for children with FEI.

Methods: We performed a retrospective analysis of National Health Interview Survey data from 2011-2018. Subjects were children with FEI—defined as having three or more ear infections in one year—whose parents or guardians answered the following questions: “In the last 12 months, have you delayed getting medical care because…” (n=10,941)
1. “…you couldn’t get through on the telephone?”
2. “…you couldn’t get an appointment soon enough?”
3. “…the wait time was too long at the doctor’s office?”
Our exposures were demographic factors including ethnicity, income in relation to federal poverty level, US region, and health status.
We used multivariable logistic regression to calculate associations between demographics and survey responses. Our results are adjusted odds ratios (aOR) with 95% confidence intervals (CI). P-values < .05 were considered statically significant.

Results: Multivariable logistic regression found Hispanic patients delayed care due to long in-office wait times more than white patients (aOR= 2.26, CI 1.80-2.83). Lower-income patients delayed care due to wait times more than higher-income patients (aOR= 1.45, CI 1.17-1.79). Patients in the Southern (aOR= 1.62, CI 1.22-2.16) and Western (aOR= 2.03 CI 1.48-2.78) US delayed care due to lack of appointment availability more than those in the Northeast. Those with “Poor to Fair” health status delayed care due to lack of appointment availability more than those in “Good to Excellent” health (aOR= 1.93, CI= 1.41-2.64).

Conclusions: Children who were Hispanic, lower income, from the Southern and Western US, or had Poor to Fair health status delayed care due to long wait times and difficulty scheduling appointments more than their counterparts. Targeted interventions can reduce disparities in treatment and outcomes.