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首页> 外文期刊>JMIR Medical Informatics >An Algorithm (LaD) for Monitoring Childbirth in Settings Where Tracking All Parameters in the World Health Organization Partograph Is Not Feasible: Design and Expert Validation
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An Algorithm (LaD) for Monitoring Childbirth in Settings Where Tracking All Parameters in the World Health Organization Partograph Is Not Feasible: Design and Expert Validation

机译：用于监测分娩的算法（LAD），其中在世界卫生组织成分中跟踪所有参数的设置不可行：设计和专家验证

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Background After determining the key childbirth monitoring items from experts, we designed an algorithm (LaD) to represent the experts’ suggestions and validated it. In this paper we describe an abridged algorithm for labor and delivery management and use theoretical case to compare its performance with human childbirth experts. Objective The objective of this study was to describe the LaD algorithm, its development, and its validation. In addition, in the validation phase we wanted to assess if the algorithm was inferior, equivalent, or superior to human experts in recommending the necessary clinical actions during childbirth decision making. Methods The LaD algorithm encompasses the tracking of 6 of the 12 childbirth parameters monitored using the World Health Organization (WHO) 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 obtain pairwise sensitivity and false-positive rates (FPRs) between them and the algorithm. Results The mean weighted pairwise sensitivity among experts was 68.2% (SD 6.95; 95% CI 59.6-76.8), whereas that between experts and the LaD algorithm was 69.4% (SD 17.95; 95% CI 47.1-91.7). The pairwise FPR among the experts ranged from 12% to 33% with a mean of 23.9% (SD 9.14; 95% CI 12.6-35.2), whereas that between experts and the algorithm ranged from 18% to 43% (mean 26.3%; SD 10.4; 95% CI 13.3-39.3). The was a correlation (mean 0.67 [SD 0.06]) in the actions selected by the expert pairs for the different patient cases with a reliability coefficient (α) of .91. Conclusions The LaD algorithm was more sensitive, but had a higher FPR than the childbirth experts, although the differences were not statistically significant. An electronic tool for childbirth monitoring with fewer WHO-recommended parameters may not be inferior to human experts in labor and delivery clinical decision support.
机译：背景在确定专家的关键分娩监测项目后，我们设计了一种算法（LAD）来代表专家的建议并验证。在本文中，我们描述了一种用于劳动和交付管理的初始算法，并使用理论案例将其与人类分娩专家的性能进行比较。目的本研究的目的是描述LAD算法，其开发及其验证。此外，在验证阶段，我们希望评估该算法是否劣等，等同或优于人类专家，以推荐分娩期间的必要临床行动。方法LAD算法包括使用世界卫生组织（WHO）Partographer监控的12个分娩参数的6个跟踪。它有关于如何在正常范围内时管理患者的建议。我们用自由选定的专家验证了该算法，从而选择用于患者病例的分层样本的动作。比较专家的选择，以获得它们与算法之间的成对灵敏度和假阳性率（FPRS）。结果专家之间的平均加权成对敏感度为68.2％（SD 6.95; 95％CI 59.6-76.8），而专家和LAD算法之间为69.4％（SD 17.95; 95％CI 47.1-91.7）。专家的成对FPR在12％至33％的范围内，平均值为23.9％（SD 9.14; 95％CI 12.6-35.2），而专家与算法之间的范围从18％到43％（平均26.3％; SD 10.4; 95％CI 13.3-39.3）。在不同患者病例的专家对选择的动作中是一种相关性（平均0.67 [SD 0.06]），用于不同患者病例的可靠系数（α）.91。结论LAD算法更敏感，但比分娩专家更高，但差异没有统计学意义。用于分娩监测的电子工具，具有较少的谁推荐参数可能不逊于劳动力和交付临床决策支持的人类专家。

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