title: Analysis of the use of multiple technologies in neonatal care.
abstract: The use of 53 different technologies was studied in 82 patients in a neonatal intensive care unit. Using a coefficient of similarity based on the utilization pattern of these technologies, it was possible to identify five clusters of patients that can be correlated with the primary diagnostic groups and such other variables as birth weight (BW), gestational age, length of stay (LOS), and weight gain. Four interdependent models were identified by multiple regression analysis. The number of different therapeutic technologies applied to these patients can be explained (r = 0.67) by their Apgar scores, gestational age, and an index of severity of illness based on the diagnostic group. The number of different diagnostic technologies used is directly related to the number of therapies delivered (r = 0.63) and, jointly with BW, determines LOS (r = 0.73). Finally, weight gain is explained by LOS and BW (r = 0.65).
authors.affiliation: COPPE/Federal University of Rio de Janeiro.
authors.forename: R T
authors.initials: RT
authors.lastname: Almeida
authors.forename: R B
authors.initials: RB
authors.lastname: Panerai
authors.forename: M
authors.initials: M
authors.lastname: de Carvalho
authors.forename: J M
authors.initials: JM
authors.lastname: Lopes
mesh_terms: D016000:Cluster Analysis; D003625:Data Collection; D003906:Developing Countries; D007363:Intensive Care Units, Neonatal / Q000379:methods* / Q000706:statistics & numerical data; D015233:Models, Statistical; D012044:Regression Analysis; D013673:Technology Assessment, Biomedical / Q000379:methods*