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ISSN 2063-5346
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Using Lean Six Sigma and Artificial Intelligence for improving medical support during maternity

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Rihab EL SABROUTY, Abdelmajid ELOUADI
» doi: 10.48047/ecb/2023.12.si7.457

Abstract

During pregnancy, women are often confronted with health problems that require follow-up or even medical treatment to reduce the risk of malformations that can lead to the loss of the baby and the mother. According to the WHO, 2.8 million pregnant women and newborns die each year, one every 11 seconds, mostly from preventable causes. In 2017, 290 000 women died during or after pregnancy. [1] With the emergence of COVID 19, the danger of a severe course of this virus with an increased risk of intensive care admission, intubation, and mortality is significantly higher in pregnant women than in non-pregnant women of the identical age. When it’s the first pregnancy, the lady worries at the slightest sign that seems abnormal, so she goes to her midwife or gynecologist, but within the case that the appointment is complicated to make, she goes to the ER, except that this will increase the workload of the emergency room, therefore, increase the waiting time which will be dramatic in some cases. To overcome these difficulties, this work aims to measure the maternity in serenity with more comfort and support from health professionals through a decision-making tool that adapts to the state of each woman. For this, the trail taken from the announcement of the pregnancy to the postpartum period is modeled with BMNP. Then the model will be analyzed to identify areas for improvement. Finally, a simulation is going to be established to visualize the course of follow-up during the pregnancy and the set of interactions between the parturient and the medical staff which will simplify the decision making and intervene efficiently in case of complication while integrating the choices and the desires of the parturient

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