AI Will Drive Proactive and Predictive Healthcare by 2030

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AI Will Drive Proactive and Predictive Healthcare by 2030

Projections say AI-powered healthcare systems will enhance patient experience and deliver predictive and connected care by 2030.

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AI-powered predictive care is expected to take a front seat by 2030. With the help of AI and predictive analytics, the healthcare system will be able to learn more about several factors such as the kind of food people consume, what are the air pollution levels in the city, if people have access to safe housing, and more. These factors are called the social determinants of health” (SDOH) by the World Health Organization. As per WHO, by 2020, chronic diseases will account for 75% of all deaths worldwide.

By 2030, artificial intelligence will be able to access multiple sources of data that were trapped in medical records to reveal patterns in disease and aid treatment. A risk regarding a particular disease will be predicted, and preventive measures will also be suggested for the same by the healthcare systems.

By that time,  healthcare systems will also be equipped to predict the risk of chronic disease and suggest preventative measures at the right time. The development of this tool has shown success and this is already being used, resulting in a decline in the rates of diabetes, congestive heart failure, and COPD (chronic obstructive heart disease), which are all strongly influenced by SDOH.

Connected care will see significant growth in 2030 as hospitals would focus on acute illnesses and highly complex procedures. Meanwhile, relatively less urgent cases would be treated via smaller hubs including retail clinics, same-day surgery centers, as well as specialist treatment clinics.  AI can help in removing bottlenecks in the system and ensure that patients and healthcare professionals are directed to where they are most needed.

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Finally, artificial intelligence-powered predictive healthcare networks will help reduce wait times for patients and improve staff workflows. In the case of areas such as surgery and diagnosis, surgeons will trust AI more to augment their skills for surgery as well as diagnosis. AI will help doctors and clinicians learn from every patient, every diagnosis, and every procedure. This will improve health outcomes, reduce clinician shortages and also, allow the system to be financially sustainable.

However, the vision for healthcare in 2030 still has a long way to go. Rigid technologies, IT, and data systems still hinder staff workflows and affect the continuity of care in areas like diagnosis, treatment, and prevention and cure of diseases. Governments, healthcare systems, and companies need to work in sync to ensure that AI systems are fully interoperable. With healthcare pushing boundaries, the need for international standards that protect how AI uses personal data will become an urgent priority in 2020 and beyond.

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Sneha Bokil is a Senior Editor with OnDot Media. She writes editorials on an array of topics ranging from IoT, AI, ML, and cloud computing, among others. She has over 9 years of experience in the field of content creation, where she has written on technology, both enterprise and consumer, and finance.