Growth is poor in preterm infants, partly due to difficulty identifying when growth is slow. The investigators will examine the use of a computer program to try and identify periods of growth slowing in preterm babies, and compare those results to the usual assessments made on patient care rounds.
We wish to examine the use of a mathematical modeling system to see if it can detect poor growth better (and more quickly) than we can clinically. To do this, we need to know what the clinical team think about a baby's growth day-to-day. However, after rounds the fellow or NNP with fill in a sheet to say what the team thought about the baby's growth (was it okay, too slow, too fast etc.), and whether any changes were made to improve the baby's growth (e.g. increased feed volume, change in composition of feeds etc.). After the baby is discharged home, weight data from the EMR will be entered into the program to try and identify times where growth slowed (or where growth was faster than expected). We will compare the results of the computer program and the record of the clinical teams thoughts on the ward round, to see if the computer program identified growth slowing more quickly than the clinical team did.
Study Type
OBSERVATIONAL
Enrollment
48
NICU, University of California, Davis
Sacramento, California, United States
Identification of growth slowing
At time of hospital discharge retrospectively collected data on daily weights (from the EMR) will be entered in to a computer program, to identify times where weight gain slowed significantly. This will be compared to the clinical assessment of the baby's growth made at the time (and recorded prospectively)
Time frame: Between birth and hospital discharge, an average of 10weeks
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.