A prick on the heel is sure to prompt a few wails from a newborn. But the blood samples that poke yields are well worth the discomfort: Newborn screenings can alert doctors to serious genetic conditions, allowing them to promptly treat vulnerable infants and prevent developmental delays or, in some cases, deaths.
Of course, that’s assuming those blood samples make it to the state laboratory for testing in a timely fashion, which doesn’t always happen—despite a U.S. Department of Health and Human Services recommendation that samples should arrive at a lab within 24 hours of collection.
In fact, a 2013 investigative report from the Milwaukee Journal Sentinel exposed widespread delays in the handling of newborn screening blood samples across the country.
He and his collaborators have developed a web-based app that allows hospitals to test how changing variables in the screening and delivery process can impact arrival time at the lab.
Getting blood samples to the lab seems straightforward enough, but hospitals must consider a number of steps in establishing a process, such as the time distribution of births, pickup schedules, transit time to the lab, and lab hours.
“The hospital can input its characteristics,” says Zayas-Caban, whose research draws on mathematical queueing models to improve workflow in healthcare settings. “And then it can test out what different strategies it could implement to reduce delays. If you change the hours of the state lab, for example, how much will that improve timeliness?”
The app grew out of a 2018 paper in Maternal and Child Health Journal in which Zayas-Caban and his collaborators found that adjusting the sample pickup time at hospitals could significantly boost the number of specimens arriving at the lab in a target time range.
The project is part of a larger grant from the Health Resources and Services Administration in the Department of Health and Human Services. Zayas-Caban worked with Beth Tarini, associate director of the Center for Translational Research in the Children’s National Health System and associate professor at George Washington University, and Amy Cochran, an assistant scientist in biostatistics and medical informatics at UW-Madison.
Author: Tom Ziemer