Abstract 228: A Cost-effectiveness Analysis Of Universal Pulse Oximetry Screening To Detect Critical Congenital Heart Disease In U.s. Newborns

Abstract

Background and objective: In 2011, critical congenital heart disease (CCHD) was added to the Recommended Uniform Screening Panel for newborns. Most state legislatures have not yet mandated pulse oximetry screening to detect CCHD, and evidence that the screening is cost-effective might be influential in these decisions. This study aimed to estimate the cost-effectiveness of universal newborn pulse oximetry screening for CCHD in the U.S. from the hospital system perspective. Methods: A model was developed to estimate the direct medical costs and health effects of screening all newborns. The health benefits were the number of timely (prior to birth hospital discharge) detected CCHD and life-years saved with the screening compared to existing practice. The analysis focused on ductal-dependent CCHD lesions amenable to pulse oximetry detection. The time horizon was the neonatal period. Costs were not discounted, though future life-years were discounted at 3%. Model inputs related to the epidemiology of CCHD, treatment outcomes, and efficacy of pulse oximetry screening to detect CCHD were derived from published literature. Results: The cost of screening was an estimated $3.83 per newborn, with an incremental cost of $4,693 per life year gained as a result of the screening. Using current U.S. hospital-based births, it was estimated that 248 more cases of CCHD would be identified at birth hospitals and 110 infant deaths averted annually with universal screening. Conclusion: Pulse oximetry screening is a life-saving program and is cost-effective by usual standards of health economic evaluation. The results of this analysis might contribute to policymakers’ decisions on universal pulse oximetry screening and may inform other stakeholders, including health care systems and payers, about likely budget impacts. Further analyses of CCHD hospitalization and screening costs can improve these model estimates.