The Greatest Challenge to Using AI/ML for Primary Health Care: Mindset or Datasets?

Abstract

The global vision for primary health care (PHC) is defined by regular access to quality care for comprehensive services throughout the course of life. However, this is not what typically happens, especially in low-and middle-income countries, where many people access the formal health system only for emergent needs. Yet, even episodic care is nearly impossible to attain due to infrastructure barriers, critical shortages of health care providers, and low-quality care. Artificial intelligence and machine learning (AI/ML) can help us revolutionize the current reality of health care into the vision of continuous health care that promotes individuals to maintain a constant healthy state. AI/ML can deliver precise recommendations to the individual, transforming patients from a passive receiver of health services into an active participant of their own care. By accounting for each individual, AI/ML can also ensure equitable coverage for entire populations with an ongoing data exchange between personal health, genomic data, public health, and environmental factors. The greatest challenge to enlisting AI/ML in the quest toward the PHC vision will be instilling a sense of responsibility with global citizens to recognize health data for the global good while prioritizing protected, individually owned data sets. Only when individuals start taking a collective approach to health data, shifting the mindset toward the goal of prevention, will the potential of AI/ML for PHC be realized. Until we overcome this challenge, the paradigm shift of the global community away from our ad hoc, reactive health system culture will not be achieved.

Harnessing the Power of Artificial Intelligence in Otolaryngology and the Communication Sciences

“…Constructive approaches for bridging the divide of course include recognition of the problem and acting on it. That and other, more-specific approaches are presented in Jones et al (2017), Mollura et al (2020), Troncoso (2020, Chakravorti (2021), Lesica et al (2021), Saeed and Masters (2021), Wasmann et al (2021, and at https://www.youtube.com/watch?v=fzokRz1pgb0 (a TEDx talk by Jim Sevier on "Bridging the digital divide") and https://www.youtube.com/watch?v=IdBemHBN7xQ (a TEDx talk by Prashant Shukla on "Transforming 34 rural India using AI and digital technology"). Indeed, AI and machine learning when applied properly and respectfully (collaboratively) can greatly empower healthcare in LMICs and for other populations such as indigenous populations or populations that are far from tertiary care hospitals (including the sparsely populated regions in high-income countries), e.g., with accurate diagnoses from images or other data obtained via telemedicine where internet or smartphone access exists, as mentioned by Andrés Bur and his coauthors, and by Jonathan Cohen, in their sections in this Review.…”

A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data

“…Primary health care (PHC) is considered the gatekeeper, where health education and promotion are provided, non-life-threatening health conditions are diagnosed and treated, and chronic diseases are managed [1]. This form of health maintenance, which aims to provide constant access to high-quality care and comprehensive services, is defined and called for by the World Health Organization (WHO) global vision for PHC [2]. Clinicians' skills and experience and the further continuing professional development are fundamental to achieve these PHC aims [3].…”

A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data

“…Primary health care (PHC) is considered the gatekeeper, where health education and promotion are provided, non-life-threatening health conditions are diagnosed and treated, and chronic diseases are managed [1]. This form of health maintenance, which aims to provide constant access to high-quality care and comprehensive services, is defined and called for by the WHO global vision for PHC [2]. To achieve these PHC care aims, common health disorders require risk prediction for primary prevention, early diagnosis, follow-up, and timely interventions to avoid diseases exacerbations and complications, all of which are the core practice of PHC [3].…”