CCC EQUATE (Equitable Quantification And Task Evaluation) - Project Summary/Abstract Children with medical complexity (CMC) are an extremely vulnerable population with significant morbidity and mortality risk. To facilitate the study of CMC, Complex Chronic Conditions (CCCs) were defined in 2000 as a set of ICD-9-CM codes specified as “CCCs” with categories (such as neurologic, cardiovascular, metabolic, and other congenital or genetic defect). Three important concerns regarding the widely used CCC system motivate this proposal. First, the CCC system is now used “off-label” for different tasks including adjustment of health status in studies not specifically focused on CMC, and for the identification of children who might benefit from comprehensive complex care services. Accordingly, the CCC system needs to be evaluated regarding performance accuracy for various tasks. Second, the CCC system needs to be assessed for potential embedded associations between ICD codes and patients’ socioeconomic status (which, for historical reasons, is associated with the structural bias markers of race and ethnicity), arising from differential access to healthcare and diagnostic testing, as well as genetic conditions related to genetic ancestry. Embedded associations might bias the aggregated CCC system, affecting the identification of or adjustment for medical complexity. Third, these two concerns must be considered jointly: the CCC system might be accurate but, due to any embedded associations, perpetuates disparities. To address these concerns, we propose the CCC EQUATE (Equitable Quantification And Task Evaluation) project. We will create scenarios using two data sources, Medicaid claims data and 52 children’s hospitals inpatient data. We will focus on the representative outcomes of hospitalizations (including readmissions) and mortality (specifically, inpatient mortality). Specifically, we aim to: Aim 1. Evaluate the performance of the CCC system across settings for these specific outcomes. Aim 2. Quantify the degree of embedded associations between ICD codes and patients’ race and ethnicity. Aim 3. Quantify potential perpetuation of bias in CCC system performance due to embedded associations in ICD codes. In sum, this project will safeguard against the CCC system having subpar task performance in certain settings for specific outcomes, and from inadvertently perpetuating bias. Furthermore, the methods and findings will be generalizable to all ICD-code based classification systems. Ultimately, the project will enhance equity, enable future research, and help improve care for CMC and their families.
