The power of data and technology in helping to reduce the global maternal mortality ratio

The other day, while discussing the power of data and technology-driven innovations, I was pleasantly surprised to stumble upon the news article about the Maltese Humanity 2.0 Lab.

The Lab is one of the examples of an non-governmental effort aiming to bring data, technology and people together through the creation of scalable model for removal of impediments in the objective of reaching the Sustainable Development health goal to reduce the global maternal mortality ratio to less than 70 per 100,000 live births by 2030.

The UN - Sustainable Development Solutions Network looks at the maternal mortality ratio indicator and rate as appropriate to address this objective: “The maternal mortality ratio is the annual number of maternal deaths from any cause related to or aggravated by pregnancy or its management (excluding accidental or incidental causes) during pregnancy, childbirth, or within 42 days of termination of pregnancy, per 100,000 live births per year.”

99% of such deaths occur in developing countries, reflecting inequities in access to health services, continuous educational opportunities of healthcare professionals, and social economics. Over 50% of these deaths occur in sub-Saharan Africa and 1/3 - in South Asia. However data is also shocking in richer economies: 1 in 10 women in the EU still have no access to maternal health services in the first months of pregnancy. This percentage of vulnerable women increases due to growing rate of refugees and migrants.

Several main causes are identified as key:

• poverty
• access due to distance
• awareness
• inadequate services due to insufficient training of HCPs
• cultural practices

According to UNICEF’s report of this year, across South Asia, three times as many rich women receive four or more antenatal care visits than women from poorer families. The increase in coverage of health personnel has been minimal in the poorest countries where maternal and neonatal mortality levels were the highest. From 2010 to 2017, coverage grew from 4 to 5 health workers per 10,000 people in Mozambique, and from 3 to 9 in Ethiopia. In Norway that number increased from 213 to 228 health personnel per 10,000 people over the same period.

Last year, the Guttmacher Institute estimated that just over half of women in Africa will give birth in a health center, compared with more than 90% in Latin America. Meanwhile in Tanzania UNFPA supports training for healthcare providers at the renovated facilities to build their capacities to deliver quality healthcare and ultimately improve maternal, newborn and child health outcomes. Still, only three of the facilities have an ambulance to strengthen referral systems and reduce the delays for pregnant women to access appropriate care. 

According to 2010 data, health service access and characteristics in Indonesia account for 23% of the difference in maternal mortality ratios between high and low-performing provinces. Crucial role play the number of doctors working at the community health centers, the number of doctors in the village/town and distance to the nearest hospital.

Last but not least cultural and social norms play their role. According to the Guardian, in developing countries, about 214 million women and girls aged 15-49 who don’t want to get pregnant are not using a modern form of contraception because they are unable to access it, or because their partners or communities frown on contraceptive use. The largest proportion of women without access to modern contraception is in sub-Saharan Africa.

What opportunities do Data-powered digital solutions hold?

Social platforms

Digital hubs like Humanity 2.0 Lab promise to create a strong collaborative platform enabling the distribution of rich information, services and the development of healthier environments for the family ecosystem. They also create opportunities for prevention and continuous awareness building, while providing tailored content to relevant groups and having access to instant emergency support services. Last but not least, they enable the dialogue in a private, and potentially anonymized virtual social setup.

AI

AI can be taught to process and learn from data such as fetal heart rate signals, contractions and vital signs - in real time. Predictive analytics and machine learning have the potential to identify mothers at risk of becoming sick during the intrapartum and post-partum periods. AI could be trained to recognize concerning trends quickly, while improving its models over time, and potentially – proposing courses of actions.

Open data

Last but not least, the role of open data sets is crucial. Data from public health agencies, medical associations, patient associations and women’s health initiatives can help to faster gather patient and care delivery-specific variables needed to predict at-risk mothers.

Mobile Solutions

In 2018 the social enterprise HelpMum won the Google Impact Challenge Africa award. The startup provides healthcare service that will tackle the maternity problem by using low-cost innovations and the power of mobile technology. It focuses in rural African areas where women are more susceptible to death due to bad road networks that make them inaccessible, and the use of midwives and traditional birth attendants who lack the resources to cater to their needs. They provide basic WHO clean birth kits to women, which can be bought online. These include surgical blades, delivery mats, and other things needed for a safe home delivery to avoid infections that may lead to the death of pregnant women. They deliver health information to pregnant women on their mobile phones such as antenatal care date, immunization sessions reminders, zoonosis awareness and vaccination schedules for the newborn babies.

According to a recent study in Ghana Mobile health interventions and decision support mHealth or Telehealth can provide a point of care guidance to the grass root level neonatal care providers. The mHealth emergency neonatal protocols for frontline health workers included phone calls, text messaging, access to the internet, and access to an unstructured supplementary service data.

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With the continuously accelerating speed of technology, innovation can come in many shapes and forms. Which one do you think will make the difference?

*All views, thoughts, and opinions expressed in this article belong solely to the author.

References

https://www.ncbi.nlm.nih.gov/pubmed/31158243

https://timesofmalta.com/articles/view/maternal-health-for-future-generations-discussed.715836

https://humanity2-0.org/about/

https://www.himss.org/library/predicting-severe-maternal-morbidity-and-mortality-informatics-opportunity

https://www.beckershospitalreview.com/healthcare-information-technology/how-ai-driven-health-it-can-help-solve-the-maternal-mortality-and-morbidity-crisis.html

https://helpmum.org/

https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(19)30098-7/fulltext

#health #WHO #SustainableDevelopmentGoal #meternalmorbidity #publichealth #healthcare #technology #AI #data #mobile #innovation