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South Asia is currently undergoing an epidemiological transition with significantly increasing prevalence rates of both communicable and non-communicable diseases (NCDs). India is the most significant contributor to the NCD burden.
Several studies conducted over the last two decades have highlighted the high overall burden of diabetes, hypertension and dyslipidaemia in India.
According to Lancet estimates, 11.4% of the Indian population was living with diabetes in 2023, and 15.3% were prediabetic.
An example case design that will be sketched for the proof of concept is that for diabetes.
Evidence shows that patient-centred PHC, in line with a chronic care model, ensures optimal diabetes self-management support and improves long-term clinical and health outcomes in diabetes patients. While public PHC in India provides free services to patients, it lacks patient-centred care. This undermines diabetes self-management education and support.
In addition, factors such as patients' lack of knowledge about diabetes, suboptimal medication adherence, persistent clinical inertia and lack of data for monitoring and evaluation through clinical trials deteriorate the standards of diabetes care in India's PHC. Establishing guidelines, supporting health care professionals´ knowledge and skills in prediabetes and diabetes care, and implementing interprofessional referral pathways can enhance prediabetes detection and care precedence in primary health care. AI tools Deep learning models can support healthcare professionals with these tasks.
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