Artificial intelligence promises to make numerous contributions to the future of healthcare, but it can actually make a lot of contributions right now.
That’s one way of summing up a recent commentary by Terry Walby, founder and CEO of Thoughtonomy, an automation technology provider, who argues “the fact is that AI technology has already reached a level of maturity where it can deliver huge value to the healthcare industry and across social care and all public services.”
Indeed, he points out, given the fact that healthcare is “suffering the consequences of monumental budgetary and staffing challenges on a daily basis, it’s simply not enough to be looking 10 years down the road” for dramatic fixes to the system from futuristic technology. Rather, it’s critical for healthcare stakeholders across the board to realize that “where AI has been adopted, it is delivering game-changing improvements in terms of cost savings, staff capacity and productivity, and patient outcomes.”
As he sees it in more practical terms, the starting point for adopting AI in healthcare should be in streamlining administrative workflows, “speeding up and optimizing processes which are often still manual, repetitive and paper-based, held back by legacy technology, fragmented branches of delivery and a lack of joined-up thinking.”
AI can solve these problems, he explains, by acting as the “integration layer” between people and systems.
To be sure, Walby notes, there are plenty of places where the future of AI is perhaps particularly bright, for example in areas such as robot-assisted surgery, preventive medical intervention and virtual nursing assistants.
But “rather than fixating on the big picture,” Walby insists, “healthcare providers need to embrace a new mindset when it comes to AI, focusing on where AI can deliver immediate results and prove its value now. A ‘start small and build-up’ approach to AI is far more manageable for healthcare organizations, enabling them to build a business case for deployment within a specific process or function, to get a feel for the technology, to learn throughout the implementation project and to be able to easily track and evaluate the outcomes.”
Moving forward from that “small” starting point, he says, “operators can build momentum, picking off ‘the low hanging fruit’ to deliver rapid ROI, and re-deploying these AI ‘building blocks’ to scale across other parts of the organization.”
One advantage to this approach is that it will enable healthcare providers “to instill the necessary skills and culture within their workforces over time to pave the way for further AI deployment.”
In the end, says Walby, “we cannot continue to think about AI as something that will transform public services in 10 years’ time.” On the contrary, that transformation should be happening now.