The AI solution to hospitals’ woes

From: POLITICO Future Pulse - Tuesday Jan 23,2024 07:02 pm
The ideas and innovators shaping health care
Jan 23, 2024 View in browser
 
Future Pulse

By Daniel Payne, Carmen Paun, Ruth Reader and Erin Schumaker

FOLLOW THE MONEY

Dowling

Dowling | Northwell Health

Michael Dowling, president and CEO of New York’s largest provider, Northwell Health, says the hospital industry’s reliance on Medicare and Medicaid has left it in financial peril.

Medicare slashed reimbursement rates by 3.4 percent on Jan. 1, and states, which share Medicaid costs with the federal government, are looking for savings — including New York.

Dowling sees technology, specifically artificial intelligence, as one way to reap the efficiencies needed to handle the shortfalls.

He talked with Daniel about the future of care delivery and what he’s focused on in 2024.

This interview has been edited for length and clarity.

How’s business?

The reimbursement is getting tougher. The payer relationships are getting harder. The government payers — Medicare and Medicaid — don’t provide you enough to cover your expenses.

Providers are basically focused on the following: Everybody’s trying to figure out how to improve operational efficiency.

If you’re a large system, you try to make sure you consolidate services as much as possible.

The other thing that every organization is looking at today is how to continue to grow and expand. Expansion in the outpatient-ambulatory space is huge. Everybody’s focused on gaining new business — and especially new commercial business, which pays you a little bit better than noncommercial.

How does AI play into these challenges?

Everybody’s focused on figuring out how to maximize and optimize the use of technology — especially now with artificial intelligence and its potential.

I think that we can use AI to dramatically reduce a lot of the labor-intensive things: documentation, predicting future outcomes and more.

We have created inside Northwell a center of excellence in AI, and we’re going to be spending an awful lot of time trying to figure out what parts of our business can become more efficient.

It has the potential to dramatically improve a lot of things. We just have to be careful when the machine brain becomes smarter than the human brain — and we can’t figure out what the machine brain is doing.

Is this as challenging a business environment as you’ve seen?

It’s more challenging today, though I look at every challenge as an opportunity. You’re dealt your hand and you have to deal with it.

Many hospitals in New York are in terrible, terrible shape, mainly because that primary source of income is from government payers. I was in government for 12 years. We had that problem, but today, the problem is much larger.

Many government officials want places like Northwell that are doing relatively OK to take over the places that are doing poorly. And I’ve done a lot of that, but I can’t take all of the hospitals doing poorly because then I will be in that situation myself.

 

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CONNECTING THE DOTS

The ChatGPT app is seen on an iPhone.

ChatGPT is just a part of AI's history. | Richard Drew/AP Photo

AI leaped into the public consciousness when the San Francisco firm OpenAI released ChatGPT in November 2022, but the technology’s advancement is a long story, three health researchers at Google explain in JAMA.

“AI 1.0,” they say, began decades ago when people started to encode what they know into computers.

That created a system of rules and decision trees, but it often couldn’t handle the complexity of real-world problems.

To make the data more useful, including in health settings, researchers worked to implement systems to make forecasts based on data.

“AI 2.0,” which they tagged as the era of deep machine learning, fully took hold in the 2010s. Larger datasets and faster computing — as well as new ways of making systems — allowed AI to make sense of images.

That had a big impact on the health care system, allowing computers to aid doctors in analyzing scans.

This iteration of artificial intelligence could recognize patterns without being explicitly programmed.

“AI 3.0,” the current epoch, which includes generative AI — the kind, like ChatGPT, that mimics human intelligence — can do still more without reprogramming.

Generative systems can learn based on new inputs. More computer power and data enable better analysis of text, sound and images.

Why it matters: Lawmakers and leaders in health institutions are trying to learn enough about the emerging technology to set guardrails and invest wisely.

 

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WORLD VIEW

Mosquitos are sorted at the Dallas County mosquito lab in Dallas, Thursday, Aug. 16, 2012. The last time Dallas used aerial spraying to curb the mosquito population, Texas' Lyndon Johnson was in the White House, Mission Control in Houston was launching Gemini missions and encephalitis was blamed for more than a dozen deaths. But for the first time in more than 45 years, the city and county planned Thursday to resume dropping insecticide from the air to combat the nation's worst outbreak of West Nile virus, which has killed 10 people and caused at least 200 others to fall ill. (AP Photo/LM Otero)

A genetic modification aims to make mosquitoes drop dead. | AP

Researchers in sub-Saharan Africa want to test whether genetically modified mosquitoes could help control the spread of malaria.

How’s that? The genetic modification, which would be passed onto future generations of mosquitoes, aims to render the insects unable to transmit the parasitic disease or to kill a mosquito species in certain areas.

The method hasn’t been tested outside of labs, but African- and U.S-based researchers are looking into field trials and how to convince people on the ground that the experiment is worthwhile before introducing the altered insects.

Even so: Researchers supported by the Foundation for the National Institutes of Health — a nonprofit that fundraises and manages partnerships among NIH and other entities — studied the views of 180 professionals from two dozen sub-Saharan countries on the technology.

They surveyed people working in academia, research and regulatory institutions; health and environment ministries; the media; and advocacy groups from countries including Kenya, Nigeria, South Africa and Tanzania.

Most recognized the technology’s potential benefit in fighting malaria, but about as many expressed concerns, over inadequate technical expertise, communities’ and countries’ acceptance and the risk of creating an ecosystem imbalance. They also worried about the plan’s affordability and sustainability.

“When we’re talking about genetically modified mosquitoes, it inherits a lot of the dialogue around genetically modified crops that has existed previously … that’s already a very polarized landscape,” Michael Santos, senior vice president for science partnerships at the Foundation for the National Institutes of Health and a study author, told Carmen.

Why it matters: Hundreds of thousands of children under 5 die from malaria every year, primarily in Africa.

Understanding and acceptance of the genetic-modification technology could make or break its use. A World Mosquito Program plan to release 200 million mosquitoes infected with a bacteria to fight dengue on the Indonesian island of Bali was put on hold indefinitely last year after opposition from locals.

 

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