title: Automated ongoing data validation and quality control of multi-institutional studies.
abstract: This paper addresses the problem of ensuring the validity and quality of data in ongoing multi-disciplinary studies where data acquisition spans several geographical sites. It describes an automated validation and quality control procedure that requires no user supervision and monitors data acquired from different locations before analysis. The procedure is illustrated for the Automated Prediction of Extubation readiness (APEX) project in preterm infants, where acquisition of clinical and cardiorespiratory data occurs at 6 sites using different equipment and personnel. We have identified more than 40 problems with clinical information and 25 possible problems with the cardiorespiratory signals. Our validation and quality control procedure identifies these problems in an ongoing manner so that they can be timely addressed and corrected throughout this long-term collaborative study.
authors.forename: Lara J
authors.initials: LJ
authors.lastname: Kanbar
authors.forename: Wissam
authors.initials: W
authors.lastname: Shalish
authors.forename: Doina
authors.initials: D
authors.lastname: Precup
authors.forename: Karen
authors.initials: K
authors.lastname: Brown
authors.forename: Guilherme M
authors.initials: GM
authors.lastname: Sant'Anna
authors.forename: Robert E
authors.initials: RE
authors.lastname: Kearney
mesh_terms: D060666:Airway Extubation; D001331:Automation; D000068598:Data Accuracy; D005544:Forecasting; D006268:Health Facilities; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature; D015337:Multicenter Studies as Topic; D011786:Quality Control