Can Technology Be Used to Help Combat Maternal Mortality?

Maitreyi Chitale · Sarah Mohamed · Louvere Walker-Hannon

[ Abstract ] [ Website ]
Tue 7 Dec 8 p.m. PST — 9:30 p.m. PST


Women in the United States are more likely to die from childbirth or pregnancy-related causes than other women in the developed world” according to the Public Health Grand Rounds podcast by the Centers for Disease Control. Although, maternal mortality is a global issue the focus will be on maternal mortality in the United States due to familiarity with domestic practices related to this topic. For instance, in 2015 the maternal mortality rate in Finland was 3 deaths/100,000 live births versus in the United States which had 14 deaths/100,000 live births according to the World Factbook from the Central Intelligence Agency. The reason that the number is high for the United States is due to the number of black women that have died and continue to die in the US, due to maternal mortality. “Black women have a maternal mortality rate three times higher than that of white women” according to National Geographic. A question that may arise from many when learning of this data is: why are these deaths occurring at such high rates? A next question for many may be: are these deaths preventable? ". The Public Health Grand Rounds podcast by the Centers for Disease Control podcast further states "research suggests half of these deaths are preventable". Research suggests that there are patterns that could be identified preventing death.

AI could be a pathway forward for preventing maternal mortality. We as a community have a unique opportunity to brainstorm and discuss strategies for combating maternal mortality. The discussion will highlight the United States as a test case and the obtained insights could also be used in other parts of the world. The current idea for a proposed workflow for using AI to address this issue entails using wearable devices that could monitor women for potentially critical periods of time after childbirth and take certain measurements. The collected data could be analyzed using Machine or Deep Learning, and classifications from this data could be used to alert members of a medical care team.

During this session through conversation, dedicated reflection time, and creation of action plans we as a community will have an opportunity to explore what are ways that AI in conjunction with other resources can be used to address this ongoing and worsening issue.

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