Challenges of Artificial Intelligence Adoption in Healthcare

15Feb - by aiuniverse - 0 - In Artificial Intelligence


February 14, 2020 – Artificial Intelligence (AI) adoption is gradually becoming more prominent in health systems, but 75 percent of healthcare insiders are concerned that AI could threaten the security and privacy of patient data, according to a recent survey from KPMG.  

Although 91 percent of healthcare respondents believe that AI implementation is increasing patient access to care, the survey of 751 US business decision makers uncovered. The survey explored the barriers and challenges that have the potential to hamper the integration of AI technologies in healthcare organizations.

Healthcare security is a top concern for insiders with 75 percent responding that they believe AI could threaten patient data privacy. But 86 percent of respondents said their organizations are taking steps to protect patient privacy as it implements AI. 

Organizations believe that a broad understanding of AI and talent in the space are musts to ensure success, but many insiders reported major challenges in these areas. 

Despite this, only 47 percent of healthcare insiders responded that their organizations offer AI training courses to employees. While only 67 percent said their employees support AI adoption, the lowest ranking of any industry. 

“Comprehending the full range of AI technology, and how best to apply it in a healthcare setting, is a learned skill that grows out of pilots and tests. Building an AI-ready workforce requires a wholesale change in the approach to training and how to acquire talent. Having people who understand how AI can solve big, complex problems is critical,” Melissa Edwards, managing director and digital enablement at KPMG said in the survey. 

Cost is a major barrier for organizations as well. Successful AI implementation requires a large investment, which means that organizations who are already feeling budget-burned may be slower to fund AI. 

Thirty-seven percent of healthcare industry executives reported that the pace in which they are implementing AI is too slow. 

But Edwards highlighted that the pace has actually greatly increased in the past few years. 

“The pace with which hospital systems have adopted AI and automation programs has dramatically increased since 2017,” she said.” Virtually, all major healthcare providers are moving ahead with pilots or programs in these areas. The medical literature is showing support of AI’s power as a tool to help clinicians.”

Fifty-four percent of executives voiced that to date, AI has increased the overall cost of healthcare. “The question is, ‘Where do I put my AI efforts to get the greatest gain for the business? Trying to assess what ROI will look like is a very relevant point as they embark on their AI journey,” Edward said. 

Last year, The White House called for more transparency and “explainability” in healthcare AI through the National Artificial Intelligence Research and Development Strategic Plan: 2019 Update. 

The plan identified eight strategic priorities for federally-funded AI research including to prioritize investments in the next generation of AI that will drive discovery and insight and enable the US to remain a leader in AI and develop effective methods for human-AI collaboration. 

The plan also included:  

  • Addressing the ethical, legal, and societal implications of AI
  • Ensuring the safety and security of AI systems
  • Developing shared public datasets and environments for AI training and testing
  • Evaluating AI technologies using standards and benchmarks
  • Understanding the national AI R&D workforce needs
  • Expanding public-private partnerships to accelerate advances in AI

“AI technologies are critical for addressing a range of long-term challenges, such as constructing advanced healthcare systems, a robust intelligent transportation system, and resilient energy and telecommunication networks,” the plan concluded.

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