- Kailash Chandra Bhakta
I am trying to build a feasible solution to the problem of very high cardiovascular diseases(CVD) rates in rural India's public health and their high-risk factors.
Those CVD disorders are completely preventable by identifying them through changes in patient's ECG readings at a very early stage, and undergoing normal medications.
But faces major challenges specific to rural India because of:-
(1). High complexity and cost of the medical ECG machine and predictive models, those are not at all accessible by rural public health centers. Challenge is to make them affordable and accessible.
(2). Due to the absence of the digital clinical record/data of the rural patients, this major cohort is missed out in the process of predictive model development. Which deteriorates the performance of those models. Challenge is to develop simple and accessible technology to acquired those clinical data in digital format.
(3). Challenge is to optimize predictive models(With the application of AI). To predict those CVD disorders at a very early stage precisely.
"People in low- and middle-income countries often do not have the benefit of integrated primary health care programs for early detection and treatment of people with risk factors compared to people in high-income countries."
--WHO (World Health Organisation)
The rural/remote location people push themselves to high-risk factors due to lack of awareness.
Ex:- Major people consume tobacco and unhealthy diet, even if while facing early-stage CVD. Because due to lack of early-stage diagnostic armamentarium and access to proper primary health care. They are unaware of the fact that themself promoting the deadliest disease in them.
We have to develop a feasible tech and business solution to improve the functioning of primary health care. By making them accessible to diagnostic devices.