Cost-effectiveness of early compared to late inhaled nitric oxide therapy in near-term infants

Objective: The purpose of this study was to determine the cost-effectiveness of early versus late inhaled nitric oxide (INO) therapy in neonates with hypoxic respiratory failure initially managed on conventional mechanical ventilation. Research design: A decision analytic model was created to compare the use of early INO compared to delayed INO for neonates receiving mechanical ventilation due to hypoxic respiratory failure. The perspective of the model was that of a hospital. Patients who did not respond to either early or delayed INO were assumed to have been treated with extracorporeal membrane oxygenation (ECMO). The effectiveness measure was defined as a neonate discharged alive without requiring ECMO therapy. A Monte Carlo simulation of 10,000 cases was conducted using first and second order probabilistic analysis. Direct medical costs that differed between early versus delayed INO treatment were estimated until time to hospital discharge. The proportion of successfully treated patients and costs were determined from the probabilistic sensitivity analysis. Results: The mean (±SD) effectiveness rate for early INO was 0.75 (±0.08) and 0.61 (±0.09) for delayed INO. The mean hospital cost for early INO was $21,462 (±$2695) and $27,226 (±$3532) for delayed INO. In 87 of scenarios, early INO dominated delayed INO by being both more effective and less costly. The acceptability curve between products demonstrated that early INO had over a 90 probability of being the most cost-effective treatment across a wide range of willingness to pay values. Conclusions: This analysis indicated that early INO therapy was cost-effective in neonates with hypoxic respiratory failure requiring mechanical ventilation compared to delayed INO by reducing the probability of developing severe hypoxic respiratory failure. There was a 90 or higher probability that early INO was more cost-effective than delayed INO across a wide range of willingness to pay values in this analysis.