Traditional healthcare processes are being transformed by new and existing players who seek to harness innovative technologies to give patients greater control, and deliver care that is high quality and patient centered.
A report by ABI Research June 2018 report highlighted a significant rise in patient monitoring devices, including AI for home-based preventative healthcare and predictive analytics, which could save hospitals around $52bn by 2021.
Accenture’s Digital Health Technology Vision 2018 report also claims that 85% of health executives in the US believe that every human will be directly impacted on a daily basis by an AI-based decision within the next three years.
Utilising big data generated by clinical information and research can reveal clusters and patterns which can benefit all aspects of healthcare, leading patient care to become increasingly strategic.
With this in mind, Signify Research has recently released its findings surrounding global demands for machine learning and medical imaging, encompassing software for automated detection, quantification, decision support and diagnosis. Demands will lead AI in medical imaging to surpass $2bn by 2023, boosting productivity, accuracy and efficiency, as well as pave the way for personalised care plans for all.
New technologies will also seek to address a widening gap of health professionals across a multitude of specialisms, such as radiology, who are facing a global shortage.
Combining data with market insights and feedback from professionals across the health and technology sectors, Signify Research has found that the world market for AI-based medical image analysis software continues to rise, particularly in areas such as neurology and cardiovascular diseases.
The technology will work to vastly improve clinical outcomes and deliver a significant return on investment to healthcare providers. Nonetheless, regulatory barriers remain in place, where the industry is presently grappling to keep afloat as new technologies continue to flood the market.
“The results from AI-based image analysis tools need to be fully integrated into radiologists’ workflows and presented at the time of the primary read. Algorithm developers need to partner with imaging IT vendors to ensure their solutions are tightly integrated,” the company has stated.
Healthcare providers are also increasingly wary of the cost of new digital tools.
“Convincing insurance companies to fund such technologies does not always come easily,” explains Sanjay Shah, Executive Vice President at pioneering healthcare organisation, Fakeeh Care.
“When introducing robotic surgery, we had countless battles with insurance companies to get it recognised. Insurance companies were asking for evidence, and we had to go to the US to find it.
“Insurance companies have a role to play in terms of seeing that this is beneficial and improvement and efficiency will come over time, as opposed just right at the starting point.”
Additionally, healthcare providers have adopted bespoke software, leading to increased silos and fragmented care planning. Integration and implementation challenges continue to challenge the industry, where algorithm developers will need to increasingly establish effective routes to market, promote data sharing and enhance the patient journey.