Beyond barriers to AI, a payoff for healthcare providers and patients

Chris Nerney
Chris Nerney, Contributing Writer |
Beyond barriers to AI, a payoff for healthcare providers and patients

Artificial intelligence (AI) is expected to transform healthcare by offering providers data-driven insights into patient care and population health management.
 
“Unlike legacy technologies that are only algorithms/tools that complement a human, health AI today can truly augment human activity—taking over tasks that range from medical imaging to risk analysis to diagnosing health conditions,” consulting firm Accenture wrote in a research report.
 
AI already is being deployed in some medical facilities in the form of robot-assisted surgery, virtual nursing assistants, and administrative workflow assistance.
 
The results have been promising: Robot-assisted surgery reduces patient length of stay by 21 percent because recovery time is faster, while the use of AI to remotely monitor patient systems saves registered nurses 20 percent of their time through a reduction in unnecessary hospital visits, Accenture said.
 
But AI healthcare faces barriers to adoption and implementation, according to Forbes Technology Council member Elad Walach, founder and CEO of Aidoc, a startup developing AI-based radiology technology. One of those barriers, he says, is provider resistance.
 
“Contrary to widespread fears, increasingly sophisticated AI capabilities won’t replace medical professionals,” Walach writes. “Although medical professionals need AI to better manage their increasingly unsustainable workloads, medical practitioners will still need to handle complex matters like making crucial treatment decisions requiring clinical context awareness, assessing unusual clinical conditions and engaging in cross-disciplinary clinical consultations.”
 
Access to data is another obstacle to effective use of AI in healthcare. AI, by definition, is data-driven, yet health data too frequently is siloed and thus inaccessible. Beyond that, providers must ensure patient data is de-identified and secured as cyberattacks on hospitals and medical research organizations increase.
 
To meet these data management requirements, Walach says, healthcare AI vendors “must develop secure infrastructure in their platforms for processing patient data with the highest level of privacy standards and in compliance with the strictest security standards.”
 
Connectivity also is critical to AI success in healthcare, argues a report released earlier this year at the request of the Office of the National Coordinator for Health Information Technology (ONC) and the Agency for Healthcare Research and Quality.
 
“In the future, AI and smart devices will become increasingly interdependent, including in health-related fields,” according to JASON, an independent group of scientists and academics. “On one hand, AI will be used to power many health-related mobile monitoring devices and apps. On the other hand, mobile devices will create massive datasets that, in theory, could open new possibilities in the development of AI-based health and health care tools.”
 
Overcoming the barriers to AI won’t be easy, Walach says, but the payoff will be worth it.
 
“Providers who latch on to the transformative power of AI technology today will find themselves best-positioned to withstand the challenges health care systems are sure to confront in the coming decades,” he says.