Friday, September 29, 2023

How to advance AI in healthcare

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Shreya Christina
Shreya has been with for 3 years, writing copy for client websites, blog posts, EDMs and other mediums to engage readers and encourage action. By collaborating with clients, our SEO manager and the wider team, Shreya seeks to understand an audience before creating memorable, persuasive copy.

Rick Newell, MD MPH is CEO of Influencing healthChief Transformation Officer at Viuity, and passionate about driving change in healthcare.

I’ve explained some of the many ways artificial intelligence can vastly improve healthcare at all levels, from telehealth to the emergency department, from diagnosis to claims processing. I also pointed out the inherent limitations of what AI can do so that we don’t waste time and resources or put patients at risk by trying to make it do what it can’t. What can we do to advance AI in healthcare, keeping both opportunities and limits in mind?

“AI” needs a new name.

For starters, I think we need a new term for machine learning and other technologies as applied to healthcare. The words ‘artificial intelligence’ conjure up the image we do not want: a machine making its own decisions. studies have shown the best results of machines and humans working together, with the AI ​​acting as a sort of physician’s assistant – supernaturally brilliant in some ways, known to be clueless in others.

I’ve suggested calling it “augmented intelligence” instead. (Maybe it’s time to bring in the naming consultants.) We need patients who are comfortable with and rely on AI.

Involve patients and doctors.

There is a necessary first step that we often see at Inflect Health: physicians must be involved from the outset in machine learning systems training as the arbiters of truth in interpreting data. The most brilliant AI engineer has not spent years in medical school, years in residency, and hours a week working with real patients while surrounded by other experts. The larger the data set, the greater the need for sophisticated expertise to train the system so that it can accurately analyze patient data.

Set data standards and transparency.

Anyone who works in healthcare knows that this is a huge challenge. The legacy data we need is huge, but we don’t have a unique national patient identifier or sub-optimal interoperability between systems. AI needs these areas to correlate data to deliver more than human insights.

We also need a lot more collaboration between all stakeholders – physicians, investors, technology developers, hospitals, ethicists, employers, health plans, regulators and, most importantly, patients – to break down specific walls so that the right entities work together and not against each other.

Healthcare naturally requires strict adherence to privacy and confidentiality, but this should not be an excuse for hiding vital information where it must be shared transparently with patient consent.

With caregivers, we need to be transparent and recognize that some tasks and even some jobs may no longer be necessary. We can highlight the ways in which the jobs of many professionals will change and look for ways in which people with a passion for care can advance rather than be eliminated.

Robust investments and supervision are needed.

I hardly need to mention that AI in healthcare needs close supervision. The U.S. Food and Drug Administration, American Medical Association, specialty associations such as the American Medical Informatics Association, American College of Radiology, American Academy of Dermatology, and other dedicated guardians of integrity and accountability must be closely involved to ensure privacy and security standards.

As an innovation and investment center, Inflect Health proudly pairs health technology innovators with people with ongoing frontline medical experience. But we would like to see other wise investors nurture AI solutions for patients, doctors, other healthcare providers and payers. The field also seems ripe for public investment. Just as federal and state programs have promoted more medical degrees for much-needed positions, a wise investment could yield better outcomes for more patients.

Frame the problem, then enter robust AI data.

After ensuring proper consent, oversight, standards, transparency and involvement of physician/patient and other stakeholders, data can be considered ready for AI input. Then, as we discussed in my previous article, people need to identify the health problems they need to fix. They need to assess the problem wisely and determine restrictions and barriers. Then they can feed AI with robust data and make it work with a doctor’s supervision. It’s long and hard work, but it can bring about transformative change in healthcare.

It’s about progress, not perfection.

The biggest hurdle I see for AI in healthcare is that we tend to expect and demand perfection from technology. Let’s be realistic: the current state of concern has many problems. As we invest, build, test and implement hopeful solutions, let’s avoid perfectionism and keep in mind a more humane goal: how can AI improve healthcare? better than it is today? Business Council is the leading growth and networking organization for entrepreneurs and leaders. Am I eligible?

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