AI to be used to improve maternal and child health in India

Although the development of Artificial Intelligence (AI) and other digital technologies in this field is still in its early stages, there is potential for these tools to support maternal and neonatal healthcare in low-resource settings. AI has the potential to transform maternal and child health in low and middle-income countries by supplementing traditional practises with advanced technology, improving diagnostic accuracy, expanding access to care, and ultimately saving lives.

The SDGs (Sustainable Development Goals) aim to

  • The SDGs aim to eliminate preventable deaths of newborns and children under the age of five by 2030, with a specific goal of lowering neonatal mortality (NMR) to a minimum of 12 deaths per 1,000 live births and under-five mortality (U5MR) to a minimum of 25 deaths per 1,000 live births across all nations.

India’s Maternal and Child Health Challenges and Current Situation

  • One of the most serious problems is the high maternal and infant mortality rates: According to the most recent SRS Bulletin, India’s maternal mortality rate (MMR) in 2018-2020 was 97 deaths per 100,000 live births, and the infant mortality rate (IMR) was 35.2 deaths per 1,000 live births in 2019-21.
  • The rates exceed the SDG targets: The NMR and U5MR in India are 24.9 and 41.9, respectively, according to the most recent National Family Health Survey (NFHS) data. These rates exceed the SDG targets and are cause for concern.
  • Many women and children in India lack access to healthcare: Many rural and remote areas lack basic healthcare facilities, and even when they do exist, they may be understaffed with qualified healthcare providers. Furthermore, cultural and societal barriers can make it difficult for women and children to access healthcare.
  • Malnutrition: Malnutrition is a major contributor to India’s high maternal, neonatal, and infant mortality rates, accounting for approximately 68 percent of child deaths.
  • Low birth weight is a leading cause of death in the first month of life in low- and middle-income countries such as India. Prematurity and low birth weight account for 45.5 percent of newborn deaths in India during the first 29 days. Currently, 18.2 percent of children have reported having a low birth weight.

In recent years, there have been some positive developments in maternal and child health in India

  • Maternal and infant mortality reduction programmes and policies: The government has implemented several programmes and policies aimed at reducing maternal and infant mortality, such as the Janani Suraksha Yojana (JSY) and the Pradhan Mantri Surakshit Matritva Abhiyan (PMSMA), which provide cash incentives and free health check-ups to pregnant women, respectively.
  • Efforts to improve access to and the quality of health-care facilities: There have also been efforts to increase the number of healthcare facilities in rural and remote areas, as well as to improve the quality of care provided at these facilities.
  • Using Technology in Healthcare: India has also been working to improve maternal and child health through the use of technology.
  • Telemedicine, for example, has been implemented in remote areas, and the government has also launched RCH ANMOL, an application for tracking pregnant women, infants, and children’s health, vaccination, and nutrition status. The Draft Health Data Management Policy, Health Data Retention Policy, Unified Health Interface, and Health Facility Registry are among the other digital initiatives.

AI’s potential applications

  • Risk factor prediction modelling: AI algorithms can identify risk factors for maternal and foetal complications and predict the likelihood of certain outcomes by analyzing large amounts of medical data. This can assist healthcare providers in identifying high-risk pregnancies early on and taking precautionary measures.
  • Predicting birth weights for a more effective nutrition programme: Malnutrition reduces newborn immunity to infections and diseases. Predicting newborn birth weight can help doctors and parents take preventative measures, such as making better use of Nutrition Rehabilitation Centers (NRCs).
  • One area where AI can have a significant impact is in the detection of foetal abnormalities: Access to ultrasound technology is often limited in LMICs, and image quality may be poor. By using AI to analyse ultrasound images, healthcare providers can improve diagnosis accuracy and detect abnormalities that would otherwise go undetected.
  • AI can also be used to improve healthcare access: Virtual care technologies, such as AI-powered chatbots and virtual assistants, can provide information and support to expectant mothers in low-income countries. It has been shown that sending personalised, timed pregnancy voice messages via mobile phone can have a positive impact on maternal healthcare practises and improve maternal health outcomes.
  • Manage and analyse massive amounts of medical data: Healthcare providers can make more informed decisions and improve outcomes for mothers and children by identifying trends and patterns in this data.

The Difficulties of Using AI to Improve Maternal and Child Health in India

  • One of the most significant challenges is data availability and quality: AI relies on large amounts of data to train models, but there is a lack of data on maternal and child health in India, and the data that is available may be of poor quality. This can make developing accurate and dependable AI-based solutions difficult.
  • Infrastructure is scarce: Many parts of India lack basic infrastructure, such as electricity and internet connectivity, making AI-based solutions difficult to implement. This is especially problematic in rural areas, where access to healthcare is already limited.
  • Concerns about ethics: AI-based solutions raise a number of ethical concerns, including privacy, bias, and accountability. It is critical to address these concerns in order to ensure that AI-based solutions are used responsibly and ethically.
  • Language and dialects: India has a diverse range of languages and dialects, which can make developing AI-based solutions that are accessible to all difficult. Due to a lack of data in certain languages or dialects, developing accurate and reliable AI-based solutions tailored to the specific needs of different linguistic communities can be difficult.
  • People living in poverty may not have access to the technology and services provided by AI-based solutions.

@the end

AI has the potential to make a significant difference in maternal and child health in India. However, it is critical to remember that these innovative technologies should not be used as a replacement for traditional healthcare practises, but rather as an additional tool. The best results would be obtained by integrating AI with existing healthcare systems. Involving healthcare providers and local communities in the development and implementation of AI-based solutions is also critical. As a result, the solutions can be made more relevant, accessible, and relevant to the local context, maximising their positive impact.

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