The prediction in terms of healthcare artificial intelligence comes from Frost & Sullivan (“Artificial Intelligence Market—Key Application Areas for Growth in Healthcare IT, Forecast to 2022”). The business analyst firm anticipates that artificial intelligence and cognitive computing will also generate savings of over $150 billion for the healthcare sector by 2025.
In terms of what these emerging technologies will be used in healthcare, the primary application is with assisting with the complexity and growth of medical data, such as data from advanced medical imaging or collected data from patients. In terms of examples, as Forbes assesses, the types of benefits of artificial intelligence-enabled solutions include automated disease prediction, personalization of treatment pathways, intuitive claims management.Also featured is real-time supply chain management. Each of these areas not only will improve the treatment of patients; many carry the promise of ensuring higher profitability and sustain competitive advantage for payers, providers and pharmaceutical enterprises.
While there is considerable potential for healthcare artificial intelligence, the report also notes that the rate of uptake in healthcare information technology has been relatively slow, compared with other sectors like finance. This is due to strategic and technological challenges. So far, the survey finds, just 15-20 percent of healthcare-related end users have been actively using artificial intelligence to drive real change in the way healthcare is delivered.
Commenting on this, Koustav Chatterjee, Industry Analyst, Transformational Health stated: “AI in healthcare IT allows many providers to pursue precision medicine approaches based on the real-time integration of a patient’s genomic, clinical, financial, and behavioral data to improve outcomes.”
In terms of delivering the potential, the analyst adds: “For maximum impact, AI algorithms also consider the latest academic research evidence and regulatory guidelines before recommending personalized treatment pathways to high-risk, high-cost patient populations.”
