The Impact of Diagnosis Complexity,Age,Race,and Socioeconomic Factors in Microtia Reconstruction: An Analysis of Over 1000 Surgical Cases From the Pediatric Health Information System Database

Abstract

Background:

Microtia, a congenital difference of the external ear, requires complex, specialized care. Access to care and the influencing factors for microtia reconstruction have not been comprehensively evaluated. This study uses the PHIS database to assess how age, race, and socioeconomic factors (Child Opportunity Index [COI]) influence access for microtia reconstruction, regardless of surgical approach, in the United States.

Methods:

A PHIS database query was conducted from 2016 to 2024. Patients with a diagnosis of microtia and related procedures were identified. Key variables, including age, race, gender, COI, and payor type, were statistically analyzed.

Results:

Only index procedures for both autologous and alloplastic-based reconstruction were evaluated, and the final sample size consisted of 1,072 procedures. The average age at surgery was 10.5 years, with most procedures performed in late childhood and the majority of patients identifying as Hispanic and publicly insured. Among microtia patients with complex chronic conditions, females were significantly older at surgery than males. Among publicly insured patients, White patients had surgery earlier than their non-White peers, a trend that was opposite in privately insured patients. Patients who underwent alloplastic-based reconstruction were, on average, younger than those who underwent autologous-based reconstruction.

Conclusion:

Timing of index microtia reconstruction and reconstructive approach varied across patient subgroups, highlighting potential differences in access to care and treatment patterns in this population. Future studies should determine whether these differences are associated with downstream clinical or psychosocial outcomes.

Keywords

microtia anotia pediatric surgical outcomes pediatric health information system childhood opportunity index healthcare disparities

Introduction

Microtia is a congenital malformation resulting from the incomplete development of the external ear. The prevalence of microtia varies globally from 0.8 to 17.4 per 10 000 births, with U.S. estimates varying from 1.0 to 3.8 per 10 000 births.^1-4 Factors such as region, race, maternal health, and environmental conditions can influence prevalence.^1,5-9 Studies highlight race as a key determinant of microtia, indicating higher rates of isolated and non-isolated microtia among Hispanic and Asian individuals.³ Socioeconomic factors have also been associated with increased risk for congenital ear anomalies.^3,10

Surgical intervention for microtia reconstruction aims to restore both function and aesthetics and is arguably one of the most complex reconstructive procedures in pediatric plastic surgery.¹¹ The timing of surgery typically ranges from age 4 to 10.¹¹ A key driver of surgery includes the psychosocial challenges that can be experienced with microtia.¹¹ Additionally, treatment decisions are often shaped by socioeconomic factors such as family income, insurance status, and healthcare access.¹² Despite the many factors involved in determining the best treatment for microtia, most studies agree that treatment improves patients’ quality of life.¹³ While race is a well-established determinant of microtia prevalence, there are limited data on how socioeconomic factors and microtia patient comorbidity influence surgical access and patterns of care in the U.S. Microtia patient complexity—often driven by the presence of multiple chronic comorbidities—can affect both the timing and type of reconstructive intervention. Socioeconomic factors may delay surgery by limiting access to specialty care and introducing compounding logistical challenges for families navigating the healthcare system.

To address this gap, we used the Pediatric Health Information System (PHIS) database to evaluate how age, race, and socioeconomic factors, measured using the Childhood Opportunity Index (COI), are associated with the timing of index reconstruction and reconstructive approach in microtia patients. COI is a well-established index that offers a detailed understanding of vulnerability and healthy childhood development.^14,15 This study aims to evaluate associations between socioeconomic context and patterns of surgical access for microtia patients, providing insights to guide equitable healthcare delivery at the time of a patient’s index procedure.

Methods

The PHIS database was queried between 2016 and 2024. The PHIS database contains clinical data from children’s hospitals across 49 US states, encompassing patient demographics, diagnosis codes, and treatment details.^16-18 Patients under the age of 21 who were diagnosed with microtia (Q17.2) and underwent surgical reconstruction for microtia within this timeframe were included. Patients who did not have a diagnosis of microtia or had a diagnosis but had not yet undergone surgical reconstruction were excluded. Microtia reconstruction via autologous costal cartilage-based reconstruction and alloplastic means were identified based on ICD procedure codes (Supplemental Table 1) and PHIS-based query assessment. Given the variability in surgical approach to microtia, only the index procedure for microtia reconstruction was analyzed per identified patient. Given this limitation, surgical outcomes such as revision burden, functional and aesthetic outcomes, and psychosocial outcomes were not evaluated.

Characteristics of the study population were described by number and percentage with defined traits. Chi-square test or Fisher’s exact test for expected cell counts less than 5, and independent t-tests for age comparisons by event status were calculated. To analyze the socioeconomic status of our patient population, COI was utilized. The COI is a validated, census-tract–level composite measure of neighborhood resources associated with healthy child development. It integrates 29 indicators across 3 domains: education, health and environment, and social and economic opportunity, each standardized and aggregated into domain and overall z-scores.^14,15 Lower COI scores represent neighborhoods with fewer educational and health-promoting resources and thus greater socioeconomic disadvantage, while higher COI scores correspond to areas with greater opportunity and access. The COI is stratified into 5 categories—very low, low, moderate, high, and very high—allowing comparison across patient populations and regions.^14,15

Furthermore, patient complexity was defined using the Complex Chronic Conditions (CCC) classification system, which is integrated into the PHIS database, identifying patients with significant comorbidities requiring specialized care.^18,19 This system identifies children with serious, often multisystem conditions—such as cardiovascular, respiratory, or neuromuscular anomalies—that require ongoing, specialized care and was used to identify microtia patients with complex comorbidities. To assess the risk associated with patient characteristics and the COI (COI 2.0)²⁰ for surgical delay (defined as age at surgery), we utilized a generalized linear mixed modeling (GLMM) framework. The average age at surgery was modeled using a linear distribution. A random intercept term was included to account for clustering of patients within hospitals. Bivariate GLMM analyses were utilized to assess the unadjusted association between each covariate and the respective outcome. Adjacent or contextually related categories that did not significantly differ within a factor were combined in the multivariable analyses. Factors were retained in the final model for each outcome if their main effect was statistically significant at the 0.05 level. Random intercepts for both hospitals and patients nested within hospitals were included in the adjusted models analyzing each outcome based on the intra-class correlation coefficients (ICC). All analyses were performed using SPSS v29.0.

Results

Overall Characteristics of the Study Population

This study included 1,072 patients, 57.1% male and 57.6% identifying as Hispanic. The mean age at surgery was 10.5 years (95% CI: 10.0, 10.9), with most procedures performed during late childhood (77.0% between 5 and 12 years of age), Table 1. The remaining racial distributions included White (20.8%), Asian (6.2%), Black (5.2%), Other (7.0%), and Unknown (3.3%). Most patients were covered by public health insurance (91.2%) and approximately one in four had one or more CCC (27.6%). Over one-third of patients (35.3%) resided in neighborhoods with very low overall childhood opportunity, as determined by factors related to socioeconomic status, health and environment, and education. An additional 21.0% lived in low-opportunity areas, while the remaining patients were distributed across moderate (16.0%), high (14.5%), and very high (13.3%) COI categories.

Table 1.

Overall Characteristics of the Study Population, Described in Relation to Average Age at Surgery, Bivariate,^a n = 1,072.

Patient characteristics	Overall (n = 1,072)	Age at surgery	P-value^a
Patient characteristics	Overall (n = 1,072)	Mean (95% CI)^a	P-value^a
Age at surgery		10.5 (10.0, 10.9)	—
5-9 y	521 (48.6%)
10-12 y	304 (28.4%)
13-17 y	221 (20.6%)
18-21 y	26 (2.4%)
Sex			.016*
Male	612 (57.1%)	10.3 (9.8, 10.8)
Female	460 (42.9%)	10.7 (10.2, 11.3)
Ethnicity/Race			.156
Hispanic	617 (57.6%)	10.6 (10.0, 11.1)
Asian	66 (6.2%)	10.6 (9.7, 11.5)
Black	56 (5.2%)	10.6 (9.7, 11.6)
White	223 (20.8%)	10.0 (9.4, 10.6)
Other^b	75 (7.0%)	11.2 (10.3, 12.1)
Unknown	35 (3.3%)	10.3 (9.1, 11.5)
Payor			.319
Private	66 (6.2%)	10.4 (9.3, 11.5)
Public	978 (91.2%)	10.5 (10.0, 11.0)
Other	28 (2.6%)	9.5 (8.2, 10.8)
Procedure type			.183
Autologous	621 (57.9%)	10.6 (10.1, 11.1)
Synthetic/non-autologous	166 (15.5%)	10.1 (9.4, 10.8)
Unknown	285 (26.6%)	10.3 (9.7, 10.9)
Complex microtia			.711
Non-complex	776 (72.4%)	10.5 (10.0, 11.0)
Complex	296 (27.6%)	10.4 (9.8, 11.0)
COI overall (v2.0)^c			.998
Very low	375 (35.3%)	10.5 (9.9, 11.0)
Low	223 (21.0%)	10.4 (9.8, 11.1)
Moderate	170 (16.0%)	10.5 (9.9, 11.2)
High	154 (14.5%)	10.4 (9.7, 11.1)
Very high	141 (13.3%)	10.4 (9.7, 11.2)

Average values (95 CI%) and difference across factor levels determined in GLMM model with main effect term for factor and random intercept terms for hospital and patients nested within hospital.

n = 16 in ‘other’ category identified as multiracial.

COI scores unknown in 9 patients.

P < .05.

Age at Index Reconstructive Procedure

In the bivariate analysis for age at surgery, a statistically significant difference in age at surgery was observed by sex, with females being slightly older than males at index reconstructive procedure (mean age = 10.7 years, 95% CI: 10.2, 11.3 vs mean age = 10.3 years, 95% CI: 9.8, 10.8, respectively, P = .016), Table 1. No significant differences were observed in age at index procedure based on race and ethnicity, payor type, microtia patient complexity or COI categories, Table 1. However, the adjusted analysis unveiled significant differences between race and ethnicity and payor type (P < .05), Table 2. Among publicly insured patients, White patients had their index reconstructive procedures at an average younger age than other races (9.94 vs 10.72 years, respectively; P = .004), Table 2. Conversely, among privately insured patients, White patients underwent index procedures at an older age compared to other races (mean difference = −3.26 years, P = .040), Table 2. These findings should be interpreted with caution given the relatively small privately insured subgroup (n = 66, 6.2%). Additionally, an interaction between sex and microtia patient complexity approached significance (P = .084); among microtia patients with complex comorbidities, females underwent index procedures at an older age than their male counterparts (10.86 vs 9.83 years, respectively; P = .007), Table 2. This difference was not seen in the non-complex microtia patients (average age difference at index procedure was 0.30 years, P = .209), Table 2.

Table 2.

Characteristics Associated With Average Age at Surgery, Adjusted.^a

Patient characteristic	Age at surgery	Contrast estimate (age difference)	P-value^a
Patient characteristic	Mean (95% CI)^a	Contrast estimate (age difference)	P-value^a
Payor × Ethnicity/Race^a			.042*
Public
White	9.94 (9.34, 10.54)
Other	10.72 (10.22, 11.21)	0.78 (0.26, 1.30)	.004*
Private
White	13.40 (10.42, 16.39)
Other	10.15 (9.03, 11.27)	−3.26 (−6.37, −0.14)	.040*
Other
White	9.37 (4.91, 13.83)
Other	9.67 (8.25, 11.09)	0.30 (−4.31, 4.91)	.898
Complex microtia × Sex			.084
Complex microtia
Male	9.83 (9.18, 10.49)
Female	10.86 (10.15, 11.57)	1.03 (0.28, 1.78)	.007*
Non-complex microtia
Male	10.19 (9.66, 10.72)
Female	10.49 (9.93, 11.05)	0.30 (−0.17, 0.77)	.209

Note. Adjusted P-values are calculated using the least significant difference method within the Generalized Linear Mixed Model (GLMM) framework. This model incorporates main effect terms that are involved in the interaction effects detailed in the table. Additionally, it includes random intercept terms to accurately account for the clustering of patients within hospitals. Final model terms: sex (F vs M), P = .002, ethnicity/race (non-Hispanic White vs Other), P = .444, complex microtia (P = .974), payor (public, private, other) P = .169, sex × complex (P = .084), payor × race (P = .042). AIC in model with versus without interaction term of Sex × Complex Microtia (5367 vs 5371) indicating more predictive model by inclusion of sex × complex. (Excluded 35 patients with unknown ethnicity/race).

Payor and procedure type were highly related: all synthetic/non-autologous procedures were performed only in patients with public insurance (n = 166); autologous procedures (n = 62 private, n = 540 public, n = 19 unknown); procedure type indeterminable (n = 4 private, n = 272 public, n = 9 other). Procedure type not considered in adjusted model due to this dependency and high proportion indeterminable.

COI = Child Opportunity Index: High (High or very high) versus lower (very low, low, or moderate).

Statistically significant at the 0.05 level.

Differences Across Autologous and Alloplastic-based Reconstruction

Among 787 patients with known reconstructive type, 621 patients underwent autologous-based reconstruction while 166 underwent alloplastic-based reconstruction, Table 3. There were no significant differences in sex distribution between the patients who received autologous or alloplastic reconstruction (P = .834), Table 3. Likewise, microtia patient complexity did not impact surgical type (27.1% alloplastic vs 29.3% autologous; P = .579), Table 3. Patients with alloplastic reconstruction were significantly younger at the time of their index reconstructive surgery compared to the autologous group (mean age 8.6 ± 3.8 years vs 10.2 ± 3.6 years, respectively; P < .001), Table 3. The alloplastic group had a higher proportion of Hispanic patients (62.7% vs 57.8%), and a lower representation of Asian patients (0.6% vs 8.1%) compared to the autologous group. All patients who received alloplastic reconstruction were publicly insured, whereas a small proportion (10.0%) of patients who received autologous reconstruction had private insurance (P < .001), Table 3. Additionally, COI categories differed significantly between groups (P = .03), with patients in the alloplastic group being more likely to fall into the very low COI category (44.8%) compared to autologous patients (32.3%), Table 3. Also, fewer alloplastic patients fell into the high and very high COI categories (21.8%).

Table 3.

Subset Analysis of 787 Patients With Known Reconstruction Type.

Patient characteristic	Alloplastic	Autologous	P-value
Patient characteristic	N = 166	N = 621	P-value
Age at surgery	8.6 (SD = 3.8)	10.2 (SD = 3.6)	<.001*
5-9 y	94 (56.6%)	287 (46.2%)
10-12 y	42 (25.3%)	188 (30.3%)
13-17 y	27 (16.3%)	127 (20.5%)
18-21 y	3 (1.8%)	19 (3.1%)
Sex			.834
Male	98 (59.0%)	361 (58.1%)
Female	68 (41.0%)	260 (41.9%)
Ethnicity/Race			<.001*
Hispanic	104 (62.7%)	359 (57.8%)
Non-Hispanic
Asian	1 (0.6%)	50 (8.1%)
Black	8 (4.8%)	28 (4.5%)
White	35 (21.1%)	119 (19.2%)
Other	7 (4.2%)	52 (8.4%)
Unknown	11 (6.6%)	13 (2.1%)
Payor			<.001*
Private	0 (—)	62 (10.0%)
Public	166 (100%)	540 (87.0%)
Other	0 (—)	19 (3.1%)
Complex microtia:			.579
Non-complex	121 (72.9%)	439 (70.7%)
Complex	45 (27.1%)	182 (29.3%)
COI overall (v2.0)			.030*
Very low	74 (44.8%)	199 (32.3%)
Low	34 (20.6%)	131 (21.2%)
Moderate	21 (12.7%)	105 (17.0%)
High	21 (12.7%)	93 (15.1%)
Very high	15 (9.1%)	89 (14.4%)

Statistically significant at the 0.05 level.

Discussion

The impact of factors such as age, race, and SES on microtia surgical outcomes remains underexplored, with previous studies noting that most existing literature on disparities in craniofacial and pediatric plastic surgery focuses primarily on patients with cleft-related differences.²¹ This study examines the differences in timing of index reconstruction and reconstructive approach among patients with microtia using socioeconomic measures, and suggests that race, age, and socioeconomic context may influence patterns of surgical access in the pediatric population.

The suggested age for reconstructive surgery is highly debated.^11,22,23 A survey of 334 American Society of Plastic Surgeons (ASPS) members found that surgeons who perform microtia reconstruction prefer starting at 7 years of age, although some delay reconstruction for cartilage availability.¹¹ Others recommend reconstruction between ages 4 and 6 to reduce psychosocial impact.¹¹ Our findings revealed differences in age at index reconstruction among patient subgroups within our cohort. Specifically, White patients with public insurance underwent surgery at an earlier age compared to patients of other races. However, these findings should be interpreted cautiously and require further inquiry, as age at reconstruction may reflect multiple factors beyond access to care alone, including reconstructive approach, surgeon and family preference, referral patterns and institutional practice variation. Differences in care access and timing among minority patients with cleft and craniofacial abnormalities are well-documented; however, research on microtia-specific outcomes remains limited.^21,24,25 Although modest, these differences may have potential clinical implications; however, the clinical significance of small differences in surgical timing remains uncertain and was not directly evaluated in this study. Prior studies have shown that Black, Hispanic, and Asian children experience delayed surgical reconstruction compared to White patients, with fewer delays observed in higher-income areas.^15,24 A recent PHIS study analyzing socioeconomic trends in microtia care found that non-White patients presenting at older ages, were more likely to reside in urban areas and more frequently came from lower-income households compared to their counterparts, though not all differences reached statistical significance.²⁶ Similarly, Liu et al²⁷ reported that non-White pediatric patients underwent significantly more reconstructive surgeries and interventions than White patients, even after adjusting for comorbidities, underscoring that disparities in microtia care extend beyond timing to overall treatment burden. Further studies are warranted to evaluate these differences in patient care.

Patient comorbidities, surgical experience, and hospital standards affect the type of reconstruction and postoperative outcomes for craniofacial patients.²⁸ Our findings mirror those of Varagur et al²⁹ who showed that autologous reconstruction remains the most common approach nationally, though alloplastic use has grown slightly over time. The authors also noted significantly higher secondary procedure rates with autologous reconstruction²⁹—an outcome not captured in our PHIS analysis, which was limited to index procedures. Autologous reconstruction was more common in our patient cohort and patients undergoing alloplastic reconstruction were significantly younger than those undergoing autologous reconstruction, which is in line with existing data.^29,30 This may reflect the feasibility of earlier alloplastic repair, whereas autologous reconstruction requires sufficient cartilage maturity for harvesting, thus delaying reconstruction until later in childhood. We also found that patients from lower COI categories were more likely to have alloplastic compared to autologous reconstruction. These findings complement those in prior studies,³¹ and suggest that socioeconomic context may influence treatment patterns and access to reconstructive options. A recent analysis using the NIS database publicized how institutional and insurance-related factors impact surgical cost and length of stay, particularly for patients on Medicaid and those treated at government institutions.²⁸ These financial and logistical factors may contribute to the differences observed in reconstruction type, reinforcing the need to evaluate equity in access to reconstructive options for microtia patients. While socioeconomic and insurance factors may influence surgical technique, surgeon preference may remain the primary driver of reconstructive technique selection, reflecting differences in training, institutional practice patterns and product availability. Cadaveric cartilage has recently emerged as an alternative framework material for microtia reconstruction, offering the advantage of avoiding donor-site morbidity associated with autologous rib harvest.^32-34 While this approach cannot be reliably distinguished within PHIS due to coding limitations, it may further influence reconstructive decision-making and access patterns in the future.

Interestingly, while patient complexity and comorbidities might be thought to influence the reconstructive approach,²⁸ we observed no significant difference between patients with complex chronic conditions and non-complex microtia patients undergoing alloplastic and autologous repair. Furthermore, findings that females with complex comorbidities underwent index reconstructive procedures at an older age compared to males warrants further investigation into gender-specific barriers. One hypothesis for the observed later age at reconstruction among female patients is that social or appearance-related factors may influence the timing of presentation or surgical decision-making.³⁵

Our study is not without limitations. Potential biases in data reporting, documentation, hospital and regional representation, and missing data may affect the reliability of our findings. Additionally, the PHIS database does not fully capture the diversity of the pediatric population. As a result, pediatric patients with microtia represented in PHIS may not accurately reflect the broader microtia population. The PHIS database primarily represents large tertiary pediatric hospitals and may exclude private or small surgical centers, potentially underrepresenting privately insured patients and biasing toward publicly insured populations. Our study also focuses on patients who have only undergone microtia reconstruction, excluding those who have not yet undergone repair. This study evaluated the index procedure for microtia reconstruction and did not evaluate clinical complications, reoperation rates, or aesthetic outcomes, which may differ significantly between autologous and alloplastic techniques. Additionally, access to alloplastic reconstruction may vary by payor, as public insurance and procedure coverage differs by state. Also, the relatively small number of privately insured patients in our cohort limits the stability and interpretability of analyses examining payor type and race interactions. The primary objective of this study was to illustrate the current state of microtia reconstruction using PHIS and the factors that may influence timing and access to care. Future studies should further analyze racial and socioeconomic factors that influence surgical outcomes in microtia reconstruction.

Conclusions

In this PHIS cohort, age at index microtia reconstruction varied by sex and by the interaction between race and insurance type, while reconstructive modality varied by socioeconomic context. These findings suggest differences in timing and treatment patterns across patient subgroups. Because this study did not evaluate postoperative, functional, or psychosocial outcomes, further work is needed to determine whether these differences translate into meaningful differences in patient experience or outcomes. Future efforts should focus on better understanding both hospital-level and patient-level variations in care for this patient population.

Supplemental Material

sj-docx-1-fac-10.1177_27325016261459571 – Supplemental material for The Impact of Diagnosis Complexity, Age, Race, and Socioeconomic Factors in Microtia Reconstruction: An Analysis of Over 1000 Surgical Cases From the Pediatric Health Information System Database

Supplemental material, sj-docx-1-fac-10.1177_27325016261459571 for The Impact of Diagnosis Complexity, Age, Race, and Socioeconomic Factors in Microtia Reconstruction: An Analysis of Over 1000 Surgical Cases From the Pediatric Health Information System Database by James Antongiovanni, Chizoba A. Mosieri, Jalynn Waites, Sierra Willens, Nikhil Shah, Leonardo Alaniz, Tricia Morphew, Kevin Blaine, Raj M. Vyas and Miles J. Pfaff in FACE

Footnotes

Abbreviations

Pediatric Health Information System (PHIS), Childhood Opportunity Index (COI), Complex Chronic Conditions (CCC)

ORCID iDs

Nikhil Shah

Miles J. Pfaff

Ethical Considerations

Institutional Review Board approval was not required.

Consent to Participate

Not applicable. This study utilized a de-identified database and did not constitute human subjects research.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online.

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