Accepted for/Published in: JMIR Research Protocols
Date Submitted: Dec 4, 2021
Date Accepted: Sep 30, 2022
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Artificial Intelligence guided citizen-centric approach to enhance uptake of maternal health services among pregnant women living in urban slum settings in India.
ABSTRACT
Background:
Pregnant women are considered to be a “high risk” group with limited access to health facilities in urban slums. Barriers to utilization of health services may lead to maternal and child mortality, morbidity, low birth weight, and children with stunted growth. Application of artificial intelligence (AI) can provide substantial improvements in all areas of healthcare from diagnostics to treatment. There have been several technological advances within the field of AI, however, AI not merely driven by what is technically feasible, but by what is humanly desirable is the need of the hour.
Objective:
The objective of our study is to develop and evaluate the AI guided citizen centric platform to enhance the uptake of maternal health services (antenatal care) amongst the pregnant women living in urban slum settings.
Methods:
A cross-sectional mixed method approach employed to collect data among pregnant women, aged 18-44 years, living in urban slums of South Delhi. A convenience sampling used to recruit 225 participants at the Anganwadi centres (AWC) after obtaining consent from the eligible participants. Inclusion criteria includes pregnant individuals residing in urban slums for more than 3 months, having smartphones, visiting AWC for seeking antenatal care. Quantitative and qualitative data will be collected electronically using Open Data Kit (ODK) based opensource tool from eligible participants. Data will be collected on clinical as well as socio-demographic parameters (based on existing literature). We aim to develop an innovative AI guided citizen centric decision support platform to effectively manage pregnancy and its outcomes among urban poor populations. The proposed research will help policymakers to prioritize resource planning, resource allocation and development of programs and policies to enhance maternal health outcomes.
Results:
The AI guided citizen centric decision support platform will be designed, developed, implemented and evaluated using principles of human centred design and findings of the study will be reported to diverse stakeholders. The tested and revised platform will be deployed for use across various stakeholders such as pregnant women, healthcare professionals, frontline workers, and policymakers.
Conclusions:
With the understanding, use and adoption of emerging and innovative technologies such as AI, maternal health informatics can be at the forefront to help pregnant women in crisis. The proposed platform will potentially be scaled up to different geographic locations for adoption for similar and other health conditions.
Citation
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