Robot clinicians are coming to take over every job that can possibly be automated, warn the naysayers.
copyright by healthitanalytics.com
That might not be such a terrible thing, say the enthusiasts. The sooner the healthcare system can eliminate human error and inefficiency, the safer, happier, and healthier patients will be. In reality, artificial intelligence is still many, many years away from replacing the clinical judgement of a living, thinking person, says Dr. Joe Kimura, Chief Medical Officer at Atrius Health. And it may not ever do so.
While AI and machine learning hold enormous potential to improve the way clinicians practice, AI proponents should try to temper their expectations and cynics worried for their jobs can relax for the moment – there is a great deal of work to be done before providers can or should trust computers to make reliable decisions for them.
No magic bullet, but here to help
“Artificial intelligence is not magic,” Kimura said at the 2017 Boston Value-Based Care Summit . “It’s not an instant panacea, and it’s not a master robot that will come out and replace all your clinicians. We’ve slapped the name of AI on it because it sounds exciting, but what we have at the moment is just a more advanced form of clinical decision support. There’s a misperception about the maturity of AI and what it can actually do. What we need to do is balance expectations with reality.”
Finding sense in data
Vendor enthusiasm and a deeply-seated desire among healthcare organizations to make sense of their big data assets has produced a highly charged environment that is full of lofty promises, the majority of which come with large caveats and lots of fine print. Healthcare organizations are rightly eager to harness the latest and greatest analytics technologies to improve efficiency, safeguard patients, boost revenue, and succeed with population health management. Doing so requires individual clinicians to synthesize vast amounts of information from disparate sources, Kimura explained, and the challenge of analyzing so much data is quickly outpacing providers’ abilities. […]
read more – copyright by healthitanalytics.com
Robot clinicians are coming to take over every job that can possibly be automated, warn the naysayers.
copyright by healthitanalytics.com
While AI and machine learning hold enormous potential to improve the way clinicians practice, AI proponents should try to temper their expectations and cynics worried for their jobs can relax for the moment – there is a great deal of work to be done before providers can or should trust computers to make reliable decisions for them.
No magic bullet, but here to help
“Artificial intelligence is not magic,” Kimura said at the 2017 Boston Value-Based Care Summit . “It’s not an instant panacea, and it’s not a master robot that will come out and replace all your clinicians. We’ve slapped the name of AI on it because it sounds exciting, but what we have at the moment is just a more advanced form of clinical decision support. There’s a misperception about the maturity of AI and what it can actually do. What we need to do is balance expectations with reality.”
Finding sense in data
Vendor enthusiasm and a deeply-seated desire among healthcare organizations to make sense of their big data assets has produced a highly charged environment that is full of lofty promises, the majority of which come with large caveats and lots of fine print. Healthcare organizations are rightly eager to harness the latest and greatest analytics technologies to improve efficiency, safeguard patients, boost revenue, and succeed with population health management. Doing so requires individual clinicians to synthesize vast amounts of information from disparate sources, Kimura explained, and the challenge of analyzing so much data is quickly outpacing providers’ abilities. […]
read more – copyright by healthitanalytics.com
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