Receipt, disparities, and impact of early primary care follow-up after pediatric critical illness

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ABSTRACT Each year in the US, nearly 170,000 children survive critical illness but often face physical, emotional, and cognitive morbidity following Pediatric Intensive Care Unit (PICU) hospitalization. Despite a rising awareness that longitudinal evaluation and support may improve post-PICU outcomes, both current and optimal practice for follow-up after PICU are unclear. Early post-hospital primary care follow-up provides a key opportunity to evaluate for and address new and ongoing health problems, support continued growth and development, and assist in the transition back to home and school. As preventative care is a core tenant of pediatric medicine, some may assume that all children receive timely follow-up after hospitalization, especially after a PICU stay. However, prior studies show this is not the case. Thus, there is an urgent need for better data to guide the timing of follow-up after PICU hospitalization discharge. Using national multi-payer data (commercial insurance & Medicaid), we will measure receipt of early (within 7 days) primary care follow-up after PICU hospitalization and assess for disparities across patient age, comorbidity status, and socioeconomic status. Secondly, we will test whether receipt of post-PICU follow-up is associated with reduced 90-day acute care health care utilization (hospital readmission and emergency department use) using a “target trial emulation”. Target trial emulation incorporates features of a randomized control trial to provide the best possible causal inference from observational data. Our specific aims include: Aim 1: To quantify receipt of early follow-up after PICU hospitalization discharge, and test for variation in the receipt of early post-PICU follow-up across patient subgroups. Aim 2: To measure the association between early post-PICU follow-up and acute care utilization among PICU survivors using a target trial emulation framework. This proposal is innovative in three key ways—we will answer a novel question using an innovative technique and data. No studies, to our knowledge, have described the overarching landscape of post-PICU follow up, nor assessed the impact on subsequent acute health care utilization. We will apply a novel approach to observational causal inference, “target trial emulation”, which leverages features of randomized control trials to make causal inferences from observational data. Our findings will provide needed data about whether early post-PICU follow-up should be standard of care and identify patient groups for whom early follow-up lags. This work will serve as the foundation for future studies to optimize post-hospital care of PICU survivors—a vulnerable and growing population of patients.