Debate on using artificial intelligence for patient safety

Debate on using  artificial  intelligence  for patient  safety

If human intelligence is the capacity to assimilate new information, assess its implications and relative importance and to come to a conclusion that guides decision making, then Artificial Intelligence (AI) is the technology to make machines do the same thing. These technologies include machine learning, natural language processing, computer vision and chatbots. The potential for AI to assist in healthcare decision making is huge; we have barely scratched the surface. While the role of AI in routine diagnosis and treatment is growing steadily, its significance in avoiding medical errors and ensuring patient safety can only be imagined.

According to a January 2019 white paper from the UK’s Academy of Medical Royal Colleges, the question of whether patients will be safer with technology than without it is central to the introduction of AI in healthcare. Those who support AI argue that machines don’t get tired or emotional, are able to process huge amounts of data much faster than humans and make fewer mistakes while doing so. Its critics point towards the need for human judgment as a key component of the clinical process and the absence of a holistic view of the patient, instead of just the disease.

Then there are ethical issues – the possibility that while AI could benefit some patients, it could expose others to unforeseen risks. And who would be held responsible for mistakes committed by an AI mechanism? Would it be the computer programmer, the tech company, the regulator or the clinician? Further, doctors occasionally need to negotiate a compromise between medical advice and the patient’s wishes, something that a machine would be quite incapable of doing!

According to a 2016 survey conducted by the American Medical Association (AMA), almost 31 percent of US physicians appreciated the potential of digital tools to improve patient care and about half of them expressed the view that digital tools would help them to improve efficiency, patient safety, increase diagnostic ability, etc..

In India, AI is being used for a variety of predictive analyses that require the processing of huge amounts of data at a higher speed. The commonest utilization of AI in India is for increasing access of healthcare services in underserved areas to offer health care to economically weaker and geographically challenging sections of the society. Patient safety issues are being addressed indirectly through better and faster diagnosis of common ailments like TB, according to a report produced by the Centre for Internet and Society (CIS). Efforts in AI directed specifically towards patient safety or healthcare quality are not being widely reported in the country. 

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