title: Does the use of automated fetal biometry improve clinical work flow efficiency?
abstract: This study was designed to compare the work flow efficiency of manual measurements of 5 fetal parameters with a novel technique that automatically measures these parameters from 2-dimensional sonograms. This prospective study included 200 singleton pregnancies between 15 and 40 weeks' gestation. Patients were randomly allocated to either manual (n = 100) or automatic (n = 100) fetal biometry. The automatic measurement was performed using a commercially available software application. A digital video recorder captured all on-screen activity associated with the sonographic examination. The examination time and number of steps required to obtain fetal measurements were compared between manual and automatic methods. The mean time required to obtain the biometric measurements was significantly shorter using the automated technique than the manual approach (P < .001 for all comparisons). Similarly, the mean number of steps required to perform these measurements was significantly fewer with automatic measurements compared to the manual technique (P < .001). In summary, automated biometry reduced the examination time required for standard fetal measurements. This approach may improve work flow efficiency in busy obstetric sonography practices.
authors.affiliation: Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine, Texas Children's Hospital Pavilion for Women, Houston, TX 77030, USA. jimmy.espinoza@bcm.edu
authors.forename: Jimmy
authors.initials: J
authors.lastname: Espinoza
authors.forename: Sara
authors.initials: S
authors.lastname: Good
authors.forename: Evie
authors.initials: E
authors.lastname: Russell
authors.forename: Wesley
authors.initials: W
authors.lastname: Lee
mesh_terms: D001699:Biometry; D049628:Body Size / Q000502:physiology*; D017598:Efficiency, Organizational / Q000706:statistics & numerical data; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013781:Texas; D016216:Ultrasonography, Prenatal / Q000379:methods* / Q000706:statistics & numerical data*; D057188:Workflow; D016526:Workload / Q000706:statistics & numerical data*