Currently accepted at: JMIR Public Health and Surveillance
Date Submitted: Nov 18, 2019
Open Peer Review Period: Nov 14, 2019 - Jan 9, 2020
Date Accepted: May 4, 2020
(closed for review but you can still tweet)
A childbirth monitoring algorithm with fewer variables than the modified WHO partograph: design and expert validation.
After determining the key childbirth monitoring items from experts in childbirth, we designed an algorithm to represent the experts’ suggestions and we validated it.
In this paper we describe the abridged algorithm for labour and delivery (LaD) management and use theoretical case to compare its performance to human childbirth experts.
The LaD algorithm encompasses the tracking of six of the 12 childbirth parameters monitored using the World Health Organisation partograph. It has recommendations on how to manage a patient when parameters are outside the normal ranges. We validated the algorithm with purposively selected experts selecting actions for a stratified sample of patient case scenarios. The experts’ selections were compared to get pairwise sensitivity and false positive rates (FPR) between them and the algorithm.
The mean weighted pairwise sensitivity among experts was 68.2% (StD. 6.95; CI. 59.6, 76.8) while that between the experts and LaD algorithm was 69.4% (StD. 17.95; CI. 47.1, 91.7). The pairwise FPR amongst the experts ranged from 12% to 33% with a mean of 23.9% (CI. 12.6, 35.2) and that between the experts and the algorithm ranged from 18% to 43% (mean 26.3%; CI. 13.3, 39.3). The was a correlation (mean of 0.67) in the actions selected by the expert pairs for the different patient cases with a reliability coefficient 0.91.
The LaD algorithm and the childbirth experts were not statistically different. An electronic tool for childbirth monitoring with fewer than WHO-recommended parameters may not be inferior to human experts in labour and delivery clinical decision support.
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