Document Detail


Does the use of automated fetal biometry improve clinical work flow efficiency?
MedLine Citation:
PMID:  23620327     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
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:
Jimmy Espinoza; Sara Good; Evie Russell; Wesley Lee
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine     Volume:  32     ISSN:  1550-9613     ISO Abbreviation:  J Ultrasound Med     Publication Date:  2013 May 
Date Detail:
Created Date:  2013-04-26     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8211547     Medline TA:  J Ultrasound Med     Country:  United States    
Other Details:
Languages:  eng     Pagination:  847-50     Citation Subset:  IM    
Affiliation:
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, Baylor College of Medicine, Texas Children's Hospital Pavilion for Women, 6651 Main St, Suite 1020, Houston TX 77030 USA. jimmy.espinoza@bcm.edu.
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