Use of technology as an evaluation tool of clinical care in preterm newborns.

OBJECTIVE To assess the use of the Neonatal Therapeutic Intervention Scoring System (NTISS) as a tool to quantify the use of technology in neonatal intensive care units, in order to detect discrepancies in the care provided to high-risk newborn infants. METHODS Prospective, descriptive, observational study about the use of technology in two neonatal intensive care units (one public and one private). The NTISS was calculated on a daily basis up to the discharge or death of preterm newborns with gestational age equal to or less than 32 weeks. We gathered data about prenatal clinical conditions, birth characteristics, and conditions on admission to the intensive care unit, as well as about the morbidities developed during the hospital stay. The risks of preterm newborns were adjusted by means of the Score for Neonatal Acute Physiology, Perinatal Extension, Version II (SNAPPE-II). Student's t test, chi-square test, Fisher's exact test, and the Mann-Whitney/Wilcoxon's test were used for the descriptive analysis. The study was approved by the local Research and Ethics Committee. RESULTS We assessed 44 newborn infants from the public intensive care unit and 52 from the private one. On admission, the severity score (SNAPPE-II) and the overall NTISS were statistically similar in both care units. The curve for the use of technology showed a gradual and progressive decreasing pattern in both care units up to the 31st day. Thereafter, there was a continuous downward trend in the private care unit, but a significant increase in the overall NTISS in the public care unit. The patients from the public care unit developed more morbidities than those from the private unit. CONCLUSION Patients with similar clinical pictures can be treated with different levels of technological resources. This may have a direct impact on morbidities and on healthcare costs. The NTISS allowed monitoring healthcare and proved efficient in detecting discrepancies in practices that could influence clinical outcomes and operating costs.