SBIR Phase II: An Integrated Biomedical Platform and Custom Algorithm to Optimize Feeding Protocols for Preterm Infants

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project addresses the economic burdens of healthcare for preterm infants in Neonatal Intensive Care Units (NICUs) across the US by lowering expenses through cost effective technology. On average 400,000 preterm infants are born in the US each year and 49% experience difficulty feeding after discharge. Preterm infants who cannot successfully feed are at increased risk of hospital readmission resulting in significant financial and emotional burdens for their families. In the US the average length of stay for an infant born less than 32 weeks gestation is 13.2 days. The current practice is for babies to remain longer in the NICU at an average cost of $7,000 per day and a national cost of more than $26 billion a year. An estimated 2-day reduction in length of stay with this biomedical device will lower the financial cost of overall neonatal healthcare expenditure by $8.9 billion annually and will reduce the need for future medical interventions because infants are discharged with a stronger early-stage health baseline. Once this product is commonly used in US hospitals, it can be distributed globally to meet demand and benefit infants worldwide. This Small Business Innovation Research (SBIR) Phase II project can save hospitals thousands of dollars while delivering better care and positive patient outcomes. For infants admitted to the NICU, successful oral feeding is a prerequisite for discharge home, but preterm infants often struggle with oral feeding skills largely due to problems coordinating swallowing with breathing. Achieving safe and efficient oral feeding in preterm infants is challenging because of these neurodevelopmental immaturities. Feeding progress is therefore limited by difficulties in maintaining cardiorespiratory stability. This biomedical platform and clinical algorithm interface use big data based on breathing patterns to quantify the synchronization of breathing and swallowing. A precise method of measuring infant breathing patterns during feeding gives clinicians a diagnostic tool to better inform decisions related to feeding advancement. This device provides objective metrics of feeding success and discharge readiness and may result in decreased readmissions for failure to thrive, substantially reducing healthcare utilizations and post-discharge expenditures. Creating technology that helps infants feed better so they can go home sooner promotes improved parent-infant interactions and optimizes infant development. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.