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Data is the life blood of the healthcare system. It has the enormous potential to address societal and economic health challenges like early the early detection, screening and monitoring of non-communicable diseases, like Parkinson’s.
To maximise the potential of AI in the treatment of non-communicable diseases (NCDs), there’s an urgent need to transform the healthcare system by opening access to data collected during healthcare interventions.
iKure is a primary healthcare provider with focus on addressing the issues of accessibility, availability, affordability and trust when it comes to connecting patients with healthcare services. Use of technology is an integral part of iKure’s business model and operations, and it has a proprietary medical collaboration platform called Wireless Health Incident Monitoring Systems (WHIMS) that presents unprecedented potential in diffusion of clinical, preventive and diagnostic insights. Utilising data analytics and artificial intelligence, iKure’s technology application is attuned for mapping diseases pattern and aligns clinical decision with actions to improve better health outcomes.
Through this discussion, we want to bring attention and interest to the small-scale local health data source can serve as a high value open data repository with enormous potential to address non-communicable disease, like hypertension. While big data can provide dramatic advances in the treatment of NCDs, local data – despite its inherent challenges and limitations – in data collection stands as a potentially rich resource in treatment efficacy and health-based studies.
We will focus on opportunities in data privacy through open data platforms, and challenges that persist in collecting high quality data to find insights of the locally derived relationship between culture, behaviour and clinical information, which may bring shift in care delivery model to better serve the stakeholders in the entire health ecosystem.
About the speakers
Tirumala Santra Mandal, PhD, is a Senior Research and Communication Analyst at iKure. She has authored and edited publications for various peer-reviewed journals.
Anindita Dey is a data analyst and machine learning enthusiast at iKure.