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APRIL 24, 2020

2 min read

The US Healthcare System is Struggling

We asked Gene Miyamoto one of Arbolus's senior #healthcare experts about his view on AI's place within the healthcare sector.

A lack of investment, an ageing population and heavy political uncertainty have placed a strain on even the simplest of healthcare solutions within the US, a system that is already operating at maximum capacity on many fronts.

Combine this with the fact that the industry in many areas is firmly rooted in paper-heavy, outdated systems and is lacking necessary funds to prepare for upcoming challenges such as Coronavirus Disease (COVID-19) and any other future outbreaks, is of concern.

We discuss with Gene Miyamoto, what is being done to ease this situation.

Artificial Intelligence - the healthcare savour?

AI and Machine Learning have been heralded by many as the healthcare saviour - but can they live up to the hype?

"The clinical application of AI was really over-marketed. Services such as IBM's Watson promised so much but failed to deliver substantial help to physicians and doctors. Many employees were since let go and a considerable amount of high-profile health system partnerships were closed."

One prominent example of this is the MD Anderson Cancer Center in Texas, which prominently invested over $62 million in planning and developing AI-assisted solutions, only to scrap the program.

IBM has since laid off more than 300 people in Watson's healthcare program and is struggling to implement a business case around the AI's capabilities.

That is not to say that AI has not yet delivered benefits to the healthcare community. AI has proved to be more effective in accurately diagnosing breast cancer than radiologists and now works not to replace, but rather to supplement and support them in a more rapid and accurate diagnosis of cancer.

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"It can help hospitals more accurately predict a patient's recovery progress and more effectively evaluate next treatment steps. AI has also become quite adept at analysing, coding and billing in revenue cycle management. It can track payments more accurately and can further help reduce an organisation's exposure to payment denials by insurance carriers. This alleviates a real problem, as currently, about 70% of claims denials by insurance carriers are avoidable."

So whilst AI in healthcare already shows first results to both doctors and patients, the promised revolution of the healthcare sector still seems like a long way ahead.

The potential is there, but in the meantime, hospitals will keep on struggling.

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