Utility of administrative and clinical data for cardiac surgery research: A case-based approach to guide choice

Risk Stratification for Congenital Heart Surgery for ICD-10 Administrative Data (RACHS-2)

BACKGROUND

As the cardiac community strives to improve outcomes, accurate methods of risk stratification are imperative. Since adoption of International Classification of Disease-10th Revision (ICD-10) in 2015, there is no published method for congenital heart surgery risk stratification for administrative data.

OBJECTIVES

This study sought to develop an empirically derived, publicly available Risk Stratification for Congenital Heart Surgery (RACHS-2) tool for ICD-10 administrative data.

METHODS

The RACHS-2 stratification system was iteratively and empirically refined in a training dataset of Pediatric Health Information Systems claims to optimize sensitivity and specificity compared with corresponding locally held Society of Thoracic Surgeons-Congenital Heart Surgery (STS-CHS) clinical registry data. The tool was validated in a second administrative data source: New York State Medicaid claims. Logistic regression was used to compare the ability of RACHS-2 in administrative data to predict operative mortality vs STAT Mortality Categories in registry data.

RESULTS

The RACHS-2 system captured 99.6% of total congenital heart surgery registry cases, with 1.0% false positives. RACHS-2 predicted operative mortality in both training and validation administrative datasets similarly to STAT Mortality Categories in registry data. C-statistics for models for operative mortality in training and validation administrative datasets-adjusted for RACHS-2-were 0.76 and 0.84 (95% CI: 0.72-0.80 and 0.80-0.89); C-statistics for models for operative mortality-adjusted for STAT Mortality Categories-in corresponding clinical registry data were 0.75 and 0.84 (95% CI: 0.71-0.79 and 0.79-0.89).

CONCLUSIONS

RACHS-2 is a risk stratification system for pediatric cardiac surgery for ICD-10 administrative data, validated in 2 administrative-registry-linked datasets. Statistical code is publicly available upon request.

Widening our Focus: Characterizing Socioeconomic and Racial Disparities in Congenital Heart Disease

BACKGROUND

Socioeconomic and racial (SER) disparities among congenital heart disease (CHD) patients may limit access to high-quality care. We characterized national SER landscape, its relationship to early outcomes, and identified interactions among determinants mitigating adverse outcome.

METHODS

The Pediatric Health Information System (PHIS) database queried patients (age < 26 years) with CHD between 2016-2018. ICD-10 codes were mapped to diagnostic categories for complexity adjustment. Correlational and hierarchical regression analyses identified risk-factors and characterized interactions.

RESULTS

N=166,599 unique admissions from 52 hospitals were identified, 58,395 having interventions. Median age was 0 years (IQR=4 years). Race/Ethnicity was predominantly White (59%), Hispanic (20%), and Black (16%). Median neighborhood household income (NHI) was $41,082, and varied among hospitals. Patient NHI had a parabolic relationship with mortality, with both higher and lower values having increased risk. Black patients had significantly higher mortality, and this relationship was potentiated by lower NHI and complexity. Length of hospital stay (LOS) was longer among Black neonates (median 51 days; IQR 93) compared to neonates of other ethnic groups (median 32 days; IQR 71), P<0.0001. Care pathways including permanent feeding tubes were also more prevalent among Black neonates (17.8%) compared to White neonates (15%), P=0.02.

CONCLUSIONS

Interactions among SER disparities modify CHD outcomes. Specific hospitals have more SER fragile patients, but may have developed care pathways that prolong LOS to mitigate risk among Black neonates. Adverse outcomes among SER disadvantaged patients are magnified in complex CHD, suggesting tangible benefits to targeted resource allocation and population health initiatives.