The Future of A.I. in Healthcare

The Real Impact of AI in Healthcare in the 2020s

Apr 8

Hey Guys,

This article is going to be a snapshot of some things going on in Artificial Intelligence at the intersection of healthcare.

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I most recently covered in the A.I. intersection of Healthcare the following topics:

Artificial Intelligence is Taking on Parkinson's Disease. ~HERE.
Artificial Intelligence Helps Cut Miss Rate of Colorectal Polyps. ~ HERE.
A.I. Advances in Treatment Of Spinal Cord Injuries and Surgery. ~ HERE.
Future of A.I. in Neurosurgery. ~ HERE.
Artificial Intelligence Could Help Detect Onset of Cardiovascular Disease. ~ HERE.
Can A.I Improve our Breast Cancer Screening?~ HERE.
Artificial Intelligence is Changing the Future of Radiology. ~ HERE.

So let’s get into it:

First autonomous X-ray-analyzing AI is cleared in the EU

An artificial intelligence tool that reads chest X-rays without oversight from a radiologist got regulatory clearance in the European Union last week — a first for a fully autonomous medical imaging AI, the company, called Oxipit, said in a statement.

Meanly broadly speaking, Algorithms are increasingly being put to work alongside radiologists and pathologists to help detect and diagnose cancers.

As A.I. is finding more applications in healthcare, policy makers need to make changes to allow these technologies to actually improve patient-centric care. It’s a big milestone for AI and likely to be contentious, as radiologists have spent the last few years pushing back on efforts to fully automate parts of their job.

ChestLink One of Many

The tool, called ChestLink, scans chest X-rays and automatically sends patient reports on those that it sees as totally healthy, with no abnormalities. Any images that the tool flags as having a potential problem are sent to a radiologist for review. Most X-rays in primary care don’t have any problems, so automating the process for those scans could cut down on radiologists’ workloads, the Oxipit said in informational materials.

Early Diagnosis Augmented with A.I.

When it comes to early diagnosis we may be starting to see a lowering of costs due to A.I.

Why it matters: AI developers say these tools can help relieve a stressed health care system and improve critical medical decision-making, but experts caution about the risk of overdiagnosis that could drive up health spending and bring the possibility of unnecessary, risky biopsies.

As populations in developing nations are aging rapidly with longer life-spans, healthcare systems will come under a lot of strain. This will improve demand for A.I. systems to make the system more efficiency and cost-effective.

FDA on Artificial Intelligence?

Since the FDA began regulating algorithms as medical devices a few years ago, there's been a surge in computer models developed to help detect and diagnose cancer and to assist in prioritizing the workflow of radiologists.

The ChestLink tech now has a CE mark certification in the EU, which signals that a device meets safety standards. The certification is similar to Food and Drug Administration (FDA) clearance in the United States, but they have slightly different metrics: a CE mark is less difficult to obtain, is quicker, and doesn’t require as much evaluation as an FDA clearance. The FDA looks to see if a device is safe and effective and tends to ask for more information from device makers.

Will policy makers catch up to A.I.’s impact on healthcare in the 2020s?

Last year, the FDA cleared an AI tool that sorts prostate biopsy images based on the odds of suspected areas being cancerous tissue for a pathologist to review — a first for cancer pathology.
Paige, the company that developed the tool, says the AI decreased errors in prostate biopsies by 70% in a study that is under review for publication.
PathAI, Nucleai and other companies are also developing AI-based pathology tools. And the FDA has given clearance to other algorithms that assist radiologists in analyzing mammography and colonoscopy images as well as CT scans.

Many of the A.I. impacts on healthcare I’ve covered in AiSupremacy could take years before they reach the healthcare system on the ground.

Still, Artificial intelligence in healthcare can be a business benefit for leaders in hospitals and physician offices who want to improve patient care and increase their revenues through more efficient processes.

Policy makers and clinical decision-makers could fast-track a new suite of tools that takes advantage of the following four prominent AI trends in healthcare. They are:

Digital pathology is at a turning point thanks to AI
AI in healthcare might improve accessibility
Improved efficiencies in billing and revenue collections
AI can alleviate challenges for healthcare

There are dozens of new healthcare startups in each of these pillars that could transform healthcare with A.I. and technology in the 2020s and more so in the 2030s.

Like we’ve been saying, Adoption of digital pathology sped up during the COVID-19 pandemic, and AI has been quick to jump on that progress. In Europe and the U.S., the first AI-powered products that automate digital pathology image analysis for diagnosis are obtaining regulatory clearance.

Improving Accessibility to Healthcare with A.I.

Healthcare could use AI-powered bots to evaluate patients before they see a human clinician, said AI expert Ajit Singh, PhD. He is general partner at Artiman Ventures, a venture capital firm focused on early-stage technology investments, and adjunct professor at Stanford School of Medicine.

From early diagnosis to screening for potential maladies, before you step into the Doctor’s office A.I. could already be there for you in the future.

With accessibility also comes affordability, as inflation, stagflation and automation as well as the pandemic squeezes us and the system. Expect to see a range of AI-powered products to streamline revenue cycle management (RCM) functions that are critical to the financial well-being of healthcare organizations.

The future of healthcare with telemedicine, A.I. in drug discovery and many related domains of digital transformation also means A.I. will become more implicated in its future.

The Fear and the Opportunity of Letting A.I. into Healthcare

The next frontier for AI in cancer pathology is to use biological markers "to predict a clinical outcome that we don't easily predict today," says David Klimstra, the chief medical officer and co-founder of Paige. That could include predicting the risk of recurrence or the likelihood that a cancer will respond to a particular drug. A.I’s ability to predict treatments and outcomes better could also help clinicians personalized our care better with data.

A.I. will also automate many aspects of tedious healthcare administration. AI can automate labor-intensive functions in coding, billing, claims appeals, and collections, all of which will reduce RCM costs and may increase the total amount of revenue collected from the same number of claims. Our healthcare system really needs an overhaul from legacy outdated architectures.

Policy maker and regulators also need to learn how to fast-track A.I. improvements and tools that can help save lives. The FDA has cleared autonomous AI devices before, starting with a tool that can detect diabetes-related eye problems in 2018 (the same tool received a CE mark in 2013). But autonomous radiology devices are more controversial. There appears to be a bottleneck in the bureaucracy of many healthcare systems. It’s only a matter of time before A.I. smart clinics and hospitals appear and it will be big business.

Artificial intelligence in healthcare will open doors to greater efficiency for hospitals and physician offices but some will be faster than others to adopt them. Cloud leaders will also innovate new AI-as-a-Service tools for healthcare and hospital providers which demonstrate how companies like Amazon, Google, Apple and Microsoft will invest in healthcare significantly in the years and decades ahead.

There will also be pushback from unions and medical professional groups. For instance as in the case with Radiology, professional organizations already have a history of speaking out against the idea: the American College of Radiology and the Radiological Society of North America published a joint letter in 2020 after an FDA workshop on artificial intelligence in medical imaging, saying that autonomous AI wasn’t ready for clinical use.

In 2022, it’s not clear how many health workers might be impacted by the use of A.I. tools and have some of their tasks automated. However with the pandemic and the nursing shortage that seems like an existential threat, new solutions will have to be found across many aspects of healthcare today.

A.I’s Role will Only Increase in Healthcare

While artificial intelligence (AI) has been around for decades, its use in the healthcare industry remains in its infancy, with plenty of room for increased acceptance and adoption. There is a sense that hospital administration is lagging the R&D of the A.I. to a very significant degree, where adoption is slow and people are resistant to the change.

Today, perhaps the most common use of AI in healthcare is hospitals leveraging the technology for patient flow and bed management. So today AI enables hospital staff to remain fully informed, allowing for potentially shorter hospital stays and enhanced bed management. In the future of healthcare, A.I’s role could be much greater.

This application of AI has a variety of implications, including short- and long-term implications. Many of these advances we haven’t even thought of yet. We are just scratching the surface of A.I.’s impact in healthcare and managing our health as healthy individuals. A.I. as a tool to promote well-being should also be a priority and not just the treatment of illness.

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Even as A.I’s research in healthcare scales, so will communities for medical professionals. Doximity is an online networking service for medical professionals. Launched in 2010, the platform offers its members curated medical news, telehealth tools, and case collaboration. It has been called the LinkedIn for Physicians and has a high adoption rate in the U.S. Networks like this will also mean younger Physicians will adopt new technologies faster in the years ahead.

Since the health industry has undergone a rapid digital transformation over the past two years, I think A.I will begin to be taken more seriously by regulators, hospital leaders and healthcare workers. By the 2030s, friction of pilot studies for early adoption will be very much reduced. Smart cities will also be more likely to develop prototypes of smart clinics and smart hospitals.

Consolidation and Growing Pains Likely

It’s also possible consolidation will occur in EMR, Pharma, hospital networks and other sectors of healthcare whereby Technology companies begin to take a larger stake in the future of healthcare. The pressure to our healthcare system is also under-reported. Doctor burnout could also backfire with the adoption of A.I. One case study that’s often cited is how amid pandemic burnout and increased demand for documentation, doctors are recording patient conversations and giving note-writing work to an AI-based tool, even if that risks privacy or medical errors. Microsoft’s acquisition of Nuance covers this domain.

At AiSupremacy I’m committed to covering A.I. in healthcare on a regular basis because I believe it’s a really important new frontier for A.I. Machine learning won’t just change healthcare, it will change how we relate to everything so say the pundits. Time will tell if that turns out to be true. The truth is more likely that the commercialization of A.I. in healthcare will have both significant pros and cons.

Thanks for reading!

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