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Health Care Transformation In A Human + Machine World: Accenture Health

posted by Alicia Caramenico

on December 19, 2019

Human-machine collaboration sounds like it’s from a Sci-Fi plot. But it’s becoming more of a reality every day.

In health care, human-machine collaboration has the potential to improve cost, quality, and access. On this episode of “The Next Big Thing in Health” podcast, AHIP CEO Matt Eyles talks to Sig Shirodkar of Accenture Health about the promise of machine learning for patients and what this new technology means for our industry.

We’d like to thank his organization, Accenture Health, for serving as the sponsor for Season 1 of The Next Big Thing in Health.

Listen to the full interview on AppleSpotifySoundcloud, and Stitcher.

Matt Eyles: It’s amazing the think about how rapidly the technology is changing, and the impact it’s going to have. But let’s translate that to how a patient might actually experience machine learning. What does that look like in practice?

Sig Shirodkar: AI provides opportunity to take cost out of the health care system. That helps everyone – not just the people delivering care, but also people that are consuming that care. AI in its infancy took hold in corporate back offices. So if you’re looking at an insurance company – or even our massive provider systems – that’s where people have been most comfortable using bots that learn transaction patterns via human keystrokes. Think of a long, complex macros you may have used in Microsoft Excel, and scale that 100 times. In terms of being able to use that to make transactions easier. AI is spreading into the field operations and moving outside the organization to engage and influence customers, and in this case patients.

In the provider example, AI is being used to reduce diagnosis errors, assist in surgeries, find new genetic links, chat with patients through chat bots – that’s very real today as patients call into their providers. Or call into their insurers. Analyze unstructured data for deeper medical insights. And that’s probably the most indirect, positive impact to the patient. If you think of AI as the superhero-computer-brain-assistant that can unemotionally gather and analyze data faster than the human brain can – and work without stopping to eat, drink, or sleep – that’s continuously providing information to providers that are then translated into patients.

In the payer example, we’re seeing AI being used to reduce the rocketing administrative costs. In a recent Accenture study, we found that insurers could save up to $7 billion over 18 months using AI-driven technologies by streamlining admin processes. 15 million per 100 full-time employees by simply automating routine business tasks. In the same study, Accenture found that 72% of health insurance executives say investing in AI will be one of their top 3 strategic priorities for 2020.

So what does this all mean for the patient? Reduced cost, by reducing wasteful spending. AI could help insurers improve consumers overall health in the way that they deliver services at a less expensive price tag.

I mentioned chat bots earlier. Chat bots handle routine web inquiries about benefits, claims, and provider networks. Imaging you’re calling in as a consumer, as a patient, and you’re just wanting to understand what the status of your benefits or claims are. Instead of having to wait for a human to go through and talk to you about it, you could ask questions in an FAQ form and get quick answers. Now, behind the scenes is detecting errors and missed information in claims – where your claim is hung up because it has the wrong zip code, or missing a letter or number from the zip code.

The AI that’s deployed is able to find that out, potentially fix it, and move that claim along. Imagine getting adjudication faster or in the time that you would expect to get it. And then lastly predicting member events, such as out-of-network or ER visits. These are some of the ways that AI is already working alongside humans.

 

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