Categorizing Fetal Heart Rate Variability with and without Visual Aids

Abstract

Analysis of the fetal heart rate (FHR) is important for monitoring fetal wellbeing. Although the NICHD classification system provides a framework for FHR assessment, there is still potential for clinicians to misclassify FHR variability. This can result in the inappropriate operative intervention (i.e., cesarean procedures) and even increase the cost of obstetrics and malpractice insurance. 2,3Keywords ► categorization ► cues ► clinical judgment ► exemplars ► fetal heart rate variability AbstractObjective This study examined the ability of clinicians to correctly categorize images of fetal heart rate (FHR) variability with and without the use of exemplars. Study Design A sample of 33 labor and delivery clinicians inspected static FHR images and categorized them into one of four categories defined by the National Institute of Child Health and Human Development (NICHD) based on the amount of variability within absent, minimal, moderate, or marked ranges. Participants took part in three conditions: two in which they used exemplars representing FHR variability near the center or near the boundaries of each range, and a third control condition with no exemplars. The data gathered from clinicians were compared with those from a previous study using novices.Results Clinicians correctly categorized more images when the FHR variability fell near the center rather than the boundaries of each range, F (1,32) ¼ 71.69, p < 0.001, partial η2 ¼ 0.69. They also correctly categorized more images when exemplars were available, F (2,64) ¼ 5.44, p ¼ 0.007, partial η2 ¼ 0.15. Compared with the novices, the clinicians were more accurate and quicker in their category judgments, but this difference was limited to the condition without exemplars. Conclusion The results suggest that categorizing FHR variability is more difficult when the examples fall near the boundaries of each NICHD-defined range. Thus, clinicians could benefit from training with visual aids to improve judgments about FHR variability and potentially enhance safety in labor and delivery.

Categorizing Fetal Heart Rate Variability with and without Visual Aids

“…The data obtained from university undergraduates reported by Ashdown et al 15 were compared with the data from the clinicians and analyzed using a 2 (experience) × 3 (cue condition) × 2 (image type) ANOVA for a mixed design, with the cue conditions and the image type (prototypical or boundary) as the within-subjects factors and the experience level as the between-subjects factor. Descriptive statistics for both sets of data are shown in Tables 2 and 3 .…”

“…Several researchers recently studied the category judgment process for discriminating among levels of FHR variability. 15 They asked a sample of university students to classify images representing the four NICHD categories of FHR variability: absent, minimal, moderate, and marked. 4 They examined the classification of FHR variability using two types of images.…”