Objective

Despite overall improvements in congenital heart disease outcomes, racial and ethnic disparities have continued. The purpose of this study is to examine the effect of race and ethnicity, as well as other risk factors on congenital heart surgery length of stay and in-hospital mortality.

Design

From the 2012 Healthcare Cost and Utilization Project Kids Inpatient Database (KID), we identified 13 130 records with Risk Adjustment in Congenital Heart Surgery complexity score-eligible procedures. Multivariate logistic and linear regression modeling with survey weights, stratification and clustering was used to examine the relationships between predictor variables and length of stay as well as in-hospital mortality.

Results

No significant mortality differences were found among all race and ethnicity groups across each age group. Black neonates and black infants had a longer length of stay (neonatal estimate = 8.73 days, P = .0034; infant estimate 1.10 days, P = .0253), relative to whites. Government-sponsored insurance was associated with increased odds of neonatal mortality (odds ratio = 1.51, P = .0055), increased length of stay in neonates (estimate = 4.26 days, P = .0009) and infants (estimate = 1.52 days, P = .0181), relative to private insurance. Government-sponsored insurance was associated with increased number of chronic conditions, which were also associated with increased LOS (estimate 8.39 days, P < .001 in neonates; estimate 3.60 days, P < .001 in infants; estimate 1.87 days, P < .001 children).

Conclusions

Racial/ethnic disparities in congenital heart surgical outcomes may be changing compared with previous studies using the KID database. Increased length of stay in children with government-sponsored insurance may reflect expansion of individual states government-sponsored insurance eligibility criteria for children with complex chronic medical conditions. These findings warrant cautious optimism regarding racial and ethnic disparities in congenital heart surgery outcomes.

A neonate presented three days after birth with left-sided unilateral inspiratory wheezing, intermittent respiratory distress, and desaturations. She was found to have a large ductus arteriosus aneurysm that caused compression of her left mainstem bronchus and left pulmonary artery. This lesion was not identified prior to birth on routine prenatal screening, which included fetal ultrasonography. Diagnosis was made on day of life (DOL) 5 by a computed tomography with angiography scan. On DOL 7, she underwent cardiac surgery which included resection of the ductal aneurysm, patch reconstruction of the transverse aortic arch and descending aorta, patent ductus arteriosus excision, and atrial secundum septal defect repair. There were no postoperative complications, and she has been asymptomatic since.

Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials.