Similarity of expert clinicians’ rank order of differential diagnoses in a newborn resuscitation context

BACKGROUND: We tested principles that could lead to a future cognitive aid that offers an interpretation of the newborn’s physiological state during resuscitation after birth. Using concordance among experts’ interpretations of newborn vital sign patterns as an approximation for an algorithm that could provide an interpretation of the newborn’s state, we explored the reliability and generalisability of experts’ interpretations. METHODS: Twelve neonatal experts viewed eight pairs of graphical trajectories showing newborns’ heart rate and oxygen saturation records supplemented with differential diagnoses elicited previously from other experts. Each pair of trajectories included one trajectory on which the original differential diagnoses had been based, and a similar but novel trajectory to which the original differential diagnoses were now generalised. For each trajectory, experts ranked the differential diagnoses according to their likelihood. We calculated how similar the new experts’ ranking was to the original experts’ ranking for both original and novel trajectories. We used descriptive categories to interpret the strength of the similarity. RESULTS: For the original and novel trajectories, the experts’ rank ordering of differential diagnoses was mostly moderately to substantially similar to the original rank ordering by the original participants. There were mostly small differences in similarity scores between the paired original and novel trajectories; fewer than 25% of the participants suggested an alternative differential diagnosis. CONCLUSIONS: The concordance of experts’ interpretations could serve as an approximation of the newborn’s physiological state, and the interpretations could be generalised. The results may justify pursuing an algorithm to underpin a cognitive aid.