Earlier this month, my colleague wrote about a new method that can help predict health outcomes in premature babies and that outperformed the Apgar score, a simple visual checklist now used at birth, in a study.
In a recent article, San Francisco Chronicle writer Erin Allday explained why the tool, called PhysiScore, appears to work so well:
Part of the reason for the increased accuracy may be the new scoring system's use of a computer algorithm to assess raw electronic data.
The PhysiScore uses vital signs like a newborn's heart rate and oxygen saturation, as well as how those vital signs change over time. These are all numbers that have long been available to doctors, but it's been impossible for medical staff to constantly process all of the information and evaluate every infant based on the data collected.
In other words, for years hospitals have been collecting useful medical information on infants, but not taking full advantage of it, said Daphne Koller, a computer science professor in the Stanford University School of Engineering, who helped design the scoring system.
Allday also reports that the researchers think that similar scoring methods could be applied to other patients, such as people who have had heart attacks.