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

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 , reactive health system culture will not be achieved.