Dr Harpreet Singh, CEO, Oxyent
In India alone, 23 percent (>3.5 million) of preterm births are annually reported. These babies are extremely vulnerable and usually die due to several birth complications, acquired infections, and damage to their brain, lungs, or eyes.
Globally 15 million babies are born preterm every year, that is more than 1 in 10 babies is born preterm. In India alone, 23 percent (>3.5 million) of preterm births are annually reported. These babies are extremely vulnerable and usually die due to several birth complications, acquired infections, and damage to their brain, lungs, or eyes. Preterm birth complications account for 0.748 million deaths per year in India which is 26 percent of the world's neonatal deaths. Preterm babies who are able to survive would remain immune challenged and are highly prone to learning, hearing, and visual disabilities. Neonates born in <32 weeks of gestation are grouped under the critical care group and need to be maintained in intensive care units specialized in the care of ill or premature newborn infants, termed as neonatal intensive care unit (NICU). Based on the criticality of the newborns, there are three defined levels of NICU: Level I stabilizes sick newborns and low-birth weight babies. Level II is equipped to support sick newborns other than those who need ventilator support and surgical care. The level III units are the NICUs.
NICU devices produce humongous amount of proprietary data each second and store the information for a maximum of 72 hours. For example, single ECG produces 86.4 million readings, impedance measurement by ECG leads result in 5.4 million data points, blood oxygen saturation reading gives 0.08 million data points per day for a single patient. Processing of this high frequency voluminous physiological data streams is still a big challenge but could yield significant insights to provide the quality care of neonates. Recent literature showed that physiological markers can provide early insights before the clinical signs become apparent. For example, HeRo score based on the heart rate variability with decelerations can be used as an indicator of early onset of sepsis. It has also been seen that the clinical signs alone are sometimes subtle for example, apnea and feeding intolerance alone cannot be considered as clear indicators of sepsis. Thus, inclusion of physiological markers along with neonatal score and clinical signs could help in identifying the actual prognostic and/or diagnostic markers for various neonatal indications. Introduction of longitudinal translational informatics with careful workflow design incumbent with predictive algorithms could integrate manifolds of data from biomedical devices (physiological parameters), clinical documents, laboratory reports, pharmacy reports, and diagnosis codes, to help in early prognosis, prevention, and diagnosis of preterm babies. However, collating diverse types of data from multiple sources itself poses few issues such as: cost, processing, storage, network bandwidth, confidentiality which could be readily addressed in the current ICT setup. Thus, automation of NICU workflow by a robust big data infrastructure could facilitate monitoring and storage of the physiological and clinical phenotype parameters at various timeframes, and also help in clinical markers discovery process. This data collection can help in training semiskilled trained manpower and improving clinical protocols in providing care to neonates in emerging countries like India.
For achieving these goals recent innovations like iNICU (integrated Neonatal Intensive Care Unit) uses cloud, IoT, and data analytics based software solution. It acts as a comprehensive integrated platform especially designed to address all current issues of NICU such as tedious workflow, integration of the data generated by multiple devices, automatic drug/nutrition calculator, auto-discharge summary, complete assessment sheets for all critical biological systems of newborns, digitalized prescription, laboratory reports, nursing notes, prenatal data, notifications/alerts to the doctor, parent engagement, predictive analytics, and NICU management. Solution allows concurrent real time access of multiple infants to clinical experts and thus, improves the care time. Technology improves care time, fills skill gap, remote monitoring of rural regions by experts, early identification of disease, and reduction in neonatal mortality.