by A team of researchers from Boston Children’s Hospital is working towards enhancing access to prenatal care services by predicting the number of pregnant individuals who attend the recommended number of visits and identifying those at risk of not attending. This innovative approach can help policymakers allocate resources effectively, ensuring that populations with insufficient prenatal care receive the necessary attention. Ultimately, it has the potential to enhance health outcomes for both mothers and babies.
The study, led by Dr. Grace Chan, analyzed data from rural Amhara, Ethiopia, in order to develop predictive models for accessing prenatal care services in low-resource settings. The findings were recently published in PLOS Global Public Health and JAMA Network Open.
Prenatal care plays a vital role in improving birth outcomes and preventing maternal and newborn deaths. The World Health Organization (WHO) recommends a minimum of eight prenatal care contacts during pregnancy to address potential complications and reduce the likelihood of adverse outcomes such as stillbirths. High-quality prenatal care significantly influences positive birth outcomes. Thus, identifying pregnant women who lack access to such care is crucial for targeting resources and improving their overall healthcare experience.
The research team collected demographic and health data from 16 rural villages through an existing community surveillance program. Pregnant mothers were enrolled in the study upon being identified at health facilities or during community visits. They were then followed through to delivery.
The study revealed that only 28.8% of women attended four or more prenatal care visits, with none of them attending the recommended eight visits. To predict the probability of individuals failing to initiate prenatal care, the researchers built predictive models that incorporated data on education, income source, diet, and previous pregnancy history. These models demonstrated modest performance, providing valuable information for predicting access to prenatal care based on available predictors at various stages of pregnancy.
Several factors were identified as predictors of failure to attend prenatal care visits. These included the use of contraceptives, consumption of fortified foods, knowledge of the distance to the nearest health facility, and a history of babies with congenital disabilities.
It is essential to note that this study does not establish a cause-and-effect relationship, but rather highlights the data necessary for developing more robust predictions regarding an individual’s likelihood of seeking prenatal care. Moving forward, Dr. Chan and her colleagues aim to validate these models using additional study sites and translate their findings into policies and programs that improve access and care for pregnant individuals.
The ability to predict the likelihood of pregnant individuals failing to receive prenatal care is a significant step towards improving healthcare outcomes for both mothers and babies. By identifying populations with limited access to care, policymakers can allocate resources more effectively, ensuring that all pregnant individuals receive the necessary support and medical attention. This research has the potential to significantly enhance the quality of prenatal care and ultimately contribute to better pregnancy outcomes worldwide.
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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
