Global Health Interventions And Artificial Intelligence
ANSWERS
The World Health Organization and other organizations are considering Artificial Intelligence (AI) as a technology that could address some health system gaps, particularly in reducing global health inequalities in low- and middle-income countries (LMICs). However, because most AI-based health applications are developed and implemented in high-income countries, their use in low- and middle-income countries is relatively new, and there is a lack of robust local evaluations to guide decision-making in low-resource settings. We propose five building blocks to guide the development and implementation of more responsible, sustainable, and inclusive AI healthcare technologies in LMICs after discussing the potential benefits, risks, and challenges of AI-based healthcare.
Because AI-based health applications are still in their early stages in LMICs, there are few robust and contextualized evaluations to guide informed decision-making in these settings. As a result, there is a significant risk of unintended negative consequences. Though their use in health care services is still poorly documented, we can identify several significant risks and challenges unique to LMICs that should be carefully considered.
In terms of the quality and safety of AI-based health applications, a lack of governance may allow companies to commercialize solutions in low- and middle-income countries that would not receive regulatory approval in high-income countries. Some may argue that because access to health care can be difficult in some LMICs, quality and safety standards should not be a barrier, which may justify a new type of “medicine for the poor.” As a result, a “good enough for them” logic may be the source of new large-scale public health issues. It should be noted that 70 to 90% of medical equipment donated to LMICs fails or does not function properly due to breakdowns (e.g., broken fuses, discharged batteries, a lack of spare parts), a lack of user manuals, or a lack of appropriate training for local staff. The question of who will maintain and update AI-based health applications and with what resources becomes critical, especially if there is a policy gap. Given AI’s high costs and investments, some countries may be unable to adopt these technologies beyond the pilot stage. Furthermore, because informal medical care is standard in some LMICs, non-compliant AI applications could quickly spread. Because some people consider themselves “lucky” or “privileged” to access health care, they may be unable to challenge or express concerns about the quality and safety of the services they receive.
Aside from the fragility of their healthcare systems, some LMICs face the additional challenge of implementing and coordinating healthcare services delivered or overseen by international development agencies and non-governmental organizations (NGOs). These agencies and organizations support specific vertical programs, such as malaria control, HIV/AIDS prevention, and maternal health. As a result, their proclivity to use AI-based health applications in silos and without a holistic view of other health needs risks further fragmenting and disrupting already fragile health systems, mainly by ignoring other severe and urgent problems. Failure to consider the realities of local health systems may jeopardize well-functioning professional, organizational, and community dynamics and practices. For example, AI-based health applications could medicalize specific issues that could be addressed more effectively through poverty reduction, health education, promotion, and prevention programs. As a result, there is a risk that the AI budget will divert overall health and social budget and resources. Increased reliance on AI may also deteriorate clinical skills, critical thinking skills, and local practice skills, such as community health practices. As a result, new problems are likely emerging due to an overreliance on AI.
QUESTION
Global Health Interventions And Artificial Intelligence
n this module you read an article about offering clinical judgment using data and predictive analytics. Throughout the course, you have read and been exposed to a multitude of resources on global health and how artificial intelligence, machine learning, and predictive analytics can be used. Using these resources and your understanding of the subject, address the questions below in your post.
READ: The attached
- What are the pros and cons in the use of artificial intelligence in global health interventions?
- What questions or concerns do you have about the use of artificial intelligence in global health interventions?