Strategic application of AI has the potential to radically change the way healthcare is delivered through evidence-driven insights. Phanikishore Burre, SVP and Global Delivery Head – Networks, Cloud, Infrastructure and Security Services, CSS Corp shares his insights on how with AI, healthcare sector has shifted its focus from merely treating, to prediction, and subsequently prevention
There’s a kind of physician whose name doesn’t bear the initials MBBS or MD. Artificial Intelligence (AI) is in the spotlight through its niche role in medical research, image analyses, predictive diagnostics, early detection, patient triage and decision support at a high degree of accuracy and efficiency. The democratisation of AI saves time and costs for stakeholders in an industry facing a shortage of physicians and allied professionals.
What’s different in India?
Unlike the rest of the world, India faces many issues in the distribution of healthcare. Problems include the dearth of clinicians, inadequate infrastructure and insufficient government investment, high-treatment costs, weak doctor-patient ratio, late diagnosis, overscheduled doctors, ailment unawareness, and the like. However, in an Indian healthcare market that is conducive for digital transformations, the times are changing as the government is showing enthusiasm for innovation and sustainable projects. Tech adoption, in general, is slow, and the Indian government and private players have much groundwork to cover if they are to catch up with their Western and European counterparts known for tech advancements, medical innovation and research and development (R&D). In India, AI can compensate for a host of problems mentioned above.
AI augmentation is happening across medical research, hospital operations and robotic surgeries.
AI fastracks biomedical research. Take the case of viral culturing in laboratories; scientists are fleshing out quicker insights by accelerating simulation time between the interaction and reaction of compounds and virals. AI-based simulation is so useful in a testing environment where viral and bacteria strains take on polymorphic identities. AI’s deep learning dives into knowledge repositories to learn from use-cases and help patients.
In India, there’re plenty of disorganised data in silos. Integrating AI into patient management systems of hospitals, pharmacies, blood banks and clinical labs, provides a 360-degree view of the patients’ history. The US, with its EHR (Electronic Health Record), is at a vantage point in integrating AI into their applications. In India, digitisation starting from a patient’s check-in, appointment, prescription to records, diagnosis and imaging is necessary. From an operational and transactional standpoint, AI transforms patient journeys by reducing costs, waiting times and dropouts.
The cutting-edge work of AI is underway in remote robotic surgeries where doctors at any location can treat patients located at any place in the world with the help of other supporting technologies like AR and 5G.
With AI as an aide, it frees medicos to devote time and energy towards prescribing the right antidote to patients, instead of studying and diagnosing symptoms. During times of fatigue, doctors inadvertently oversee critical parameters or information about the patient. AI steps in to check the crucial factors of patients and their ailments.
Adoption in Indian healthcare
In India, large-scale AI implementation is on the anvil through startups and tech firms. Google and Microsoft are working with hospitals to integrate AI. Tech behemoths and life science players are also fleshing out AI-based platforms, smartphone apps and co-bots for the medical industry. Startups are collaborating with hospitals for early detection, recurrence and treatment. AI is transforming diagnosis and treatments across autism, cardiology, ophthalmology, dementia, various cancers, plus the psychiatric world of bipolar disorders, Post-Traumatic Stress Disorder (PTSD) and schizophrenia. Various factors such as large-scale datasets of a burgeoning population, hyperconnectivity and digitalisation present a conducive environment with many a proof-of-concept for AI pilot projects to expand.