Chris Mazzolini

No policy is a policy. And when it comes to advancements in artificial intelligence (AI) and machine learning (ML), not having a policy could have serious implications for the patients, physicians, and every sector of the health care industry.

That was the point made by Brian Scarpelli and Sebastian Holst during their presentation titled “A modest proposal for AI regulation in healthcare,” held during the HIMSS22 Global Health Conference in Orlando. Scarpelli is the senior global policy counsel for the Connected Health Initiative and Holst is principal with Qi-fense, a consulting group that works in AI and ML.

“ML properties do more than challenge domain-specific applications of technology,” Scarpelli and Holst write. “Many of these properties will force an evaluation and retooling of core manufacturing, quality, and risk frameworks that have effectively served as the foundation of today’s industry-specific regulations and policies.”

Here’s some key points from their presentation on the growth of AI/ML and the need for regulation.

AI can potentially revolutionize health care in all facets. It can reduce administrative burdens for providers and payer and allow for resources to be deployed within a health system to serve vulnerable patient populations. It can manage public health emergencies such as the COVID-19 pandemic and help improve both preventive care and diagnostic efficiency.

2. Machine learning is a rapidly growing industry.

According to Scarpelli and Holst, the growth in machine learning products has surged since 2015, starting first with processing applications, including products for processing radiological images, and has since progressed into diagnosis applications, particularly also in the radiological space to assist with triage and prioritization.

The number of patents coded to machine learning and health informatics has exploded, from 165 in 2017 to more than 1,100 in 2021.

While AI is promising, there are potential legal and ethical challenges that must be addressed. For example, one of the major themes of the HIMSS22 conference has been the challenge of achieving health equity and eliminating implicit bias. That’s one of the major challenges of AI as well since AI solutions can be biased. Many sessions focused on how diverse teams are needed when creating AI solutions to ensure that the programs don’t carry the same biases as society, which could exacerbate current social problems, according to Tania M. Martin-Mercado, MS, MPH, a clinical researcher who presented on “How implicit bias affects AI in healthcare.”

During her presentation, she pointed to an example of “an online tool that estimates risk of breast cancer calculates a lower risk for Black or Latinx women than White even when every other risk factor is identical.”

A diverse group of health agencies, including the FDA, HHS, CMS, FTC, and the World Health Organization, are developing regulations and asking from guidance from various stakeholders, including AI developers, physicians and other providers, patients, medical societies, and academic institutions.

Scarpelli says that the vision for successful AI follows four principals. It should:

Empower patients to manage their own health.

Strengthen the relationship patients have with their health care teams.

Reduce administrative and cognitive burdens for both physicians and patients.

This article was originally published by sister publication Medical Economics.

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Good machine learning practices’ are needed to address the unique social, legal, and ethical concerns potentially raised by artificial intelligence (AI).

Regulation needed for health care AI

Telehealth visits helped physicians, patients and the rest of the U.S. health care system weather the COVID-19 pandemic when much of in-person care was reduced.

But Medicare still has old-fashioned regulations on the books that restrict when and how telehealth services can be used. All those difficulties went out the window when the federal government declared a public health emergency at the beginning of the pandemic — and has since extended it multiple times.

But when the health emergency finally is allowed to expire, the telehealth rules will revert back without legislation from Congress, said Brian Scarpelli, senior global policy counsel for the Connected Health Initiative, during a session at the 

Those rules are quite onerous compared to modern telehealth practices, Scarpelli said. For example, a residence is not considered a valid site of care, and a patient has to reside in a recognized provider shortage area. In addition, telehealth has to be live and on video to qualify for reimbursement.

“What sense do those rules make in this day and age?” Scarpelli said.

All of those restrictions were put aside during the health emergency, which is set to expire on April 16, according to HHS. It could still be extended, as it has been numerous times already during the pandemic. In fact, the 

 recently approved by both chambers of Congress calls for the loosened telehealth rules to continue for five months after the official end of the public health emergency.

However, even with that extension baked in, there’s no promises that the “telehealth cliff” that many virtual care advocates are concerned about will be avoided. That’s because Congress will need to get involved.

This will depend on Congress to act,” Scarpelli said. “And you can never bank on Congress to act.”

This article originally appeared on Medical Economics®. 

Congress will have to take action to keep the telehealth floodgates open, so uncertainty remains.

What happens to telehealth when pandemic emergency measures end?

Physician burnout is one of the most pervasive problems facing medicine today. Can an AI assistant help?

While the impacts of the COVID-19 pandemic are often highlighted as a main source of burnout, most issues contributing to burnout among physicians predate the pandemic, according to Steven E. Waldren, MD, MS, the vice president and chief medical informatics officer for the American Academy of Family Physicians (AAFP). Waldren spoke during a session at the HIMSS22 Global Health Conference in Orlando.

: documentation, billing, prior authorizations, quality metrics, EHR systems that don’t work well enough. It’s all the stuff that keeps physicians away from their patients.

“Why are they burned out? It’s the amount of administrative work they have to do and the time constraints they have on being able to practice the medicine the way the want to,” he said.

One of Waldren’s roles with AAFP is with the academy’s Innovation Lab, which has spent the last few years studying technology tools that can help front-line primary care physicians deal with the challenges of running a modern medical practice. The lab’s studies are aimed at addressing what Waldren says are the three main areas: reducing the clerical burden, support value-based programs and integrate artificial intelligence and machine learning into the routine of a family physician.

Waldren explained that the lab evaluates technology in three phases, starting with a proof-of-concept stage in which 10 clinicians across a few practices use a product to see how well it works. If it passes that stage, about 100 clinicians across the AAFP membership will use the product to make sure its workable. Once a breakthrough product shows to really help physicians, then the AAFP moves onto the educational phase.

So how are AI tools to assist with clinical documentation faring? Are they showing improvements in physician burnout?

Waldren pointed to a product called Suki, an AI digital assistant which works like Alexa or Siri. Essentially a physician uses their voice to assist with documentation. Waldren explained that a physician can ask Suki to retrieve a specific note template, say for an annual wellness visit or a diabetes screening.

During AAFP’s Innovation Lab trial, 132 physicians used this product, which resulted in a 72% reduction in documentation time, reducing it to 3 minutes per note. This resulted in 3.3 hours saved per week, Waldren said.

One of the primary challenges facing documentation assistants like Suki or any other helpful health technology is that they must be integrated with the EHR to provide benefits to clinicians, Waldren says, and integration services vary among EHR vendors.

He explained that one EHR vendor might take a work week to help a practice integrate something like Suki with their system while another vendor with similar capabilities could take weeks.

One of the major benefits to the Innovation Lab’s approach to finding burnout solutions is that physicians are often skeptical of tech tools until they have seen their peers in a similar practice situation use the tool successfully. Because of burnout, they are often too busy to even try these new things. So having proof that other physicians have “been there, done that, and been successful” is key, Waldren said.

The results of physician trials led by the AAFP Innovation Lab are very promising.

Chris Mazzolini

Articles

Regulation needed for health care AI

What happens to telehealth when pandemic emergency measures end?

Are AI assistants key to fixing physician burnout?