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March 2016 Affiliated with Columbia University College of Physicians and Surgeons and Weill Cornell Medical College
Spotting Patterns, Predicting Illness With Neonatal Data Capture

Physiologic monitoring captures a wealth of information on neonates, such as their heart rate, respiratory rate and blood pressure. Most of that information goes unnoticed, except when the readings at a given point in time are noted during a routine check or when an alarm sounds to indicate a potential emergency.

But in the neonatal unit of NewYork-Presbyterian/Morgan Stanley Children’s Hospital at Columbia University Medical Center, in New York City, Rakesh Sahni, MD, Co-Director, Infant Physiology Laboratory and Professor of Pediatrics, and others are working to exploit physiologic monitoring to its fullest potential.

“A monitor can provide two things—real-time information and the patient’s state,” Dr. Sahni said. “And if you’re monitor-savvy, you can go back and look at what happened to the patient over a period of time,” but only, he added, if that period of time is not more than 24 hours.

“Come the 25th hour, that data is wiped out,” Dr. Sahni said. “Imagine if all the data were stored away instead—if you had data from when you weren’t watching the monitor. There would be a million questions you could ask.”

A Deep Data Mine

Not content to imagine, Dr. Sahni and his colleagues are creating just such a database. The neonatal unit at NYP/Morgan Stanley Children's is “wired completely,” Dr. Sahni said, with hardware and software that capture and store all of the physiologic monitoring data on remote hard drives.

“The BedMaster Ex system [Excel Medical] is able to capture all of the waveforms, all of the numbers, all of the trends, the changes from minute to minute and all of the alarms,” Dr. Sahni said. “I can be sitting in my office, open up the software and look up the data for any baby in real time.”

Dr. Sahni emphasized that the actual looking is the key. “You can have the software put in, but unless someone goes and digs into the data, there’s no point in having it.”

To that end, NYP/Morgan Stanley Children’s has more than 10 ongoing projects that seek to mine the data for all it contains. Among the questions that Dr. Sahni and his colleagues are asking is whether physiologic monitoring data can be used to predict infections in neonates before clinicians notice any overt symptoms. Neonatal specialists at NYP/Morgan Stanley Children's are collaborating with researchers at the University of Virginia to answer that question and to develop indices that could be used for early detection of sepsis and necrotizing enterocolitis (NEC), a rotting infection of the abdominal tissue that Dr. Sahni described as “a big burden” for neonates.

“A baby with NEC can lose a lot of tissue in their gut, which we then have to go in and remove,” Dr. Sahni said. “It’s a lifelong insult. So trying to find these things before they happen is very important.”

Dr. Sahni and his colleagues are also capturing data on the amount of oxygen that babies are receiving on a second-by-second basis, making NYP/Morgan Stanley Children's “one of very few” centers in the country that is collecting that information. “Adults are fine breathing whatever oxygen is around, but babies need a certain level of oxygen,” he said. “Premature babies can get eye disease if they don’t have enough oxygen; or if we overshoot and give them too much oxygen, they can go blind.”

The system is also being used to track the number of alarms that sound from the monitors every day, to aid NYP/Morgan Stanley Children's in reducing the alarm burden, in compliance with guidelines released in early 2014 by the Joint Commission that accredits health care organizations.

Whether tracking alarms, oxygen, indicators of infection or any other stream of data, Dr. Sahni said, the system effectively functions like a more capacious version of a bedside monitor.

“We have a system in place right now where every morning at 5 am, the database is tapped and a summary is generated,” Dr. Sahni said. “It’s similar to what you can do at the bedside looking at trends over the last 24 hours, but the beauty of this system is that you can go back as many 24-hour periods as you like.”

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