Identity/biometrics/technology marketing and writing services
I don’t know that Oosto or even Evolv could have prevented this determined hospital attack in York, Pennsylvania.
“A man carrying a handgun and zip ties took hostages inside a Pennsylvania hospital on Saturday, fatally shooting a responding police officer and wounding five others before he was killed by police, officials said.
“The gunman entered UPMC Memorial hospital in York, Pennsylvania, on Saturday morning and went directly to the intensive care unit, where he took staff members hostage…”
(Imagen 3)
Like Google Glass before it, Apple Vision Pro truly shines in vertical niche applications—not the mass market. Take healthcare:
“Apple Vision Pro’s price and weight are of no concern to doctors in the operating room, as the spatial computing platform helps replace expensive monitors and stiff necks.”
From “300 doctors attended a summit on Apple Vision Pro’s applications in surgery”
https://appleinsider.com/articles/25/01/31/300-doctors-attended-a-summit-on-apple-vision-pros-applications-in-surgery
There’s a critical difference between biometrics for identification and biometrics for health. Well, MOST biometrics for identification; what I’m about to say doesn’t apply to DNA.
When you capture biometrics from people, you don’t really care about cleanliness. If the person’s fingernails are dirty, you capture the fingerprints anyway. If the eye is infected, you capture the irises anyway.
But when you get into the healthcare arena, cleanliness is next to you-know-what.
And there are technologies for that.
Ethylene Oxide (EtO) gas is one of the most common ways to sterilize medical devices, a safe, tightly controlled, highly regulated process which is critical for preventing infections and ensuring patients have safe surgeries and medical treatments.
And in some cases, EtO is the ONLY way to sterilize some medical devices.
So great! Use it all the time! There’s just one teeny problem…
EtO is a human carcinogen. It causes cancer in humans. Scientific evidence in humans indicates that regular exposure to EtO over many years increases the risk of cancers of the white blood cells, including non-Hodgkin lymphoma, myeloma, and lymphocytic leukemia. Studies also show that long-term exposure to EtO increases the risk of breast cancer in women.
Workers who use EtO as a part of their jobs and people who work, live, or go to school or daycare near facilities that use EtO may breathe in EtO at levels that can increase cancer risk.
So there are companies (I won’t name them here, but you can find them) who specialize in mitigating EtO risk to humans.
And these companies need content, proposal, and analysis services.
But let’s get on to the important part: the song I quoted in the title of this post.
(Imagen 3)
I’m not the only person interested in AI applications in health. Kerry Langstaff is exploring various AI applications in a series of LinkedIn articles, and her recent article is entitled “How AI Became My Caregiving Superpower: Managing Medical Tests, Doctor Visits, and More.”
Langstaff explores six possible applications. I’m not going to delve into all of them; read her article to find out about her success in using generative AI to understand medical tests, take appointment notes (with consent), understand terminology, organize medications, and figure out how to fold a wheelchair to fit in a car.
But I will look at her fourth application: navigating Medicare and medical equipment.
Medicare, or any U.S. health insurance plan (I can’t speak to other countries), definitely needs navigation assistance. Deductibles, copays, preventive, diagnostic, tiers, or the basic question of what is covered and what isn’t. Or, as Langstaff put it, it’s like solving a Rubik’s Cube blindfolded.
Such as trying to answer this question:
“How do I get approval for a portable oxygen concentrator?”
Now if I had tried to answer this question before reading the article, I would find a searchable version of the health plan (perhaps from the government), search for “portable oxygen concentrator,” not find it, finally figure out the relevant synonym, then confirm that it is (or is not) covered.
But that still wouldn’t tell me how to get it approved.
Langstaff was warned that the whole process would be a “nightmare.”
But generative AI tools (for example, NotebookLM) are getting better and better at taking disparate information and organizing it in response to whatever prompt you give it.
So what happened to Langstaff when she entered her query?
“AI walked me through the entire process, from working with her doctor to dealing with suppliers.”
But we all know that generative AI hallucinates, right? Weren’t those instructions useless?
Not for Kerry.
“I got it approved on the first try. Take that, bureaucracy.”
But I should add a caution here. Many of us use general purpose generative AI tools, in which all the data we provide is used to train the algorithm.
Including any Protected Health Information (PHI) that we feed into the tool.
Imagine if Langstaff had inadvertently included some PHI in her prompt:
“Here is the complete prescription for Jane Jones, including her diagnosis, date of birth, Social Security Number, home address, and billing credit card. The prescription is for a portable oxygen concentrator. How do I get it approved?”
Oh boy.
Most medical providers freak out if you include PHI in an email. What happens when you submit it to Stargate?
Be careful out there.
(Imagen 3)
When Woz was building computers 50 years ago, he didn’t realize his successors would build medical devices that would receive FDA approval.
I touched on this earlier in my Thursday post about H.R. 238 and its proposal to use AI tools to write prescriptions.
But just in passing. Here’s a deeper, um, dive from May 2024.
“The FDA created the Medical Device Development Tools (MDDT) program to reduce uncertainty in device development.…Through MDDT, the FDA has created a portfolio of qualified tools that sponsors know the agency will accept without needing to reconfirm their suitability for use in a study.”
And now the Apple Watch is one of those qualified tools.
“Apple applied to get its AFib history feature qualified as a MDDT in December (2023). It is the first digital health technology qualified under the program.”
The advantage of using an Apple Watch to gather this data?
“Officials said the wearable can help address the challenges ‘by allowing for passive, opportunistic AFib burden estimation in a wearable form that is already familiar to Apple Watch users.’”
Medical measurements are often skewed by stress from the health experience itself. But if you’re already wearing an Apple Watch, and you always wear an Apple Watch, the passive nature of AFib data collection means you don’t even know you’re being measured.
On Threads, Dr. Jen Gunter called our attention to the newly-introduced H.R. 238, “To amend the Federal Food, Drug, and Cosmetic Act to clarify that artificial intelligence and machine learning technologies can qualify as a practitioner eligible to prescribe drugs if authorized by the State involved and approved, cleared, or authorized by the Food and Drug Administration, and for other purposes.”
Ultra-modern healthcare?
Presumably these non-person entities would not be your run-of-the-mill consumer generative AI packages, by rather specially trained Large Medical Models (LMMs).
Kinda like my “Dr. Jones, NPE.”
Even so, don’t count on this becoming law in the next two years. For one, Rep. David Schweikert introduced a similar bill in 2023 which never made it out of committee.
Why is Rep. Schweikert so interested in this and related topics? Because medical bills are too damn high:
““How do I make sure we’re embracing technology and using it to bring disruptive cures to market, or other opportunities to market?” Schweikert asked. “And does that also now help lower drug pricing?””
Before you reject this idea entirely, Rep. Schweikert cited one example of technology decision-making:
“Schweikert noted that the FDA last month approved Apple Watch’s atrial fibrillation feature for use in clinical trials — the first such digital health tool approved for inclusion in the agency’s Medical Device Development Tools program.”
But before anything like this will ever happen with prescriptions, the FDA will insist on extremely rigorous testing, including double-blind tests in which some prescriptions are written by currently-authorized medical professionals, while other prescriptions are written by LMMs.
And even when the ethical questions surrounding this are overcome, this won’t happen overnight.
(All images Imagen 3)
I’ve discussed identity and privacy regarding people.
I’ve discussed identity and privacy regarding non-person entities.
But I missed something in between.
Earlier this week I was discussing a particular veterinary software use case with an undisclosed person when I found myself asking how the data processing aspects of the use case complied with HIPAA, the U.S. Health Insurance Portability and Accountability Act.
Then I caught myself, realizing that HIPAA (previously discussed here) does not apply to dogs, cats, cows, or other animals. They are considered property, and we all know how U.S. laws have treated property in the past.
So you can violate an animal’s privacy all you want and not run afoul of HIPAA.
But you could run afoul of some other law. As Barb Rand noted back in 2013, 35 states (at the time) had “statutes that address the confidentiality of veterinary patient records.”
And when animal records are commingled with human records—for example, for emotional support animals—protected health information rules do kick in.
Unless the animal is intelligent enough to manage their own prescriptions without human assistance.
Since I started creating (sort of) pillar pages in April 2022, I’ve built more, including three devoted to particular industries.
Oosto has highlighted two reasons why it’s critical to identify people in healthcare environments.
Healthcare facilities account for 42% of infant abductions…
Think about it. If all you need to identify yourself (or impersonate someone else) is your name and birthdate, a fraudster could easily gain access to a facility and abduct someone else’s child.
(H)ealthcare workers experience violence—both physical and verbal—at a shockingly 5 times higher rate than other industries. This violence accounts for up to 73% of all nonfatal workplace injuries caused by violence.
Again, if you don’t know who you’re dealing with, bad things can happen. I’ll admit that identity verification doesn’t solve this-people can attack healthcare workers even if their identities are known-but the danger of unidentified assaults is great.
Oosto discusses these and other healthcare topics in a recent podcast: “Healthcare Under Pressure: Bringing a Championship Mindset to Healthcare Security.“
(Image: AI-predicted cell detection results of Biomy’s DeepPathFinder™. From the January 10, 2025 NEC press release.)
When I interact with the worldwide company NEC, I am usually dealing with automated biometric identification systems (ABIS).
Of course, ABIS is only a small part of what NEC does. It’s also involved in healthcare.
Consider…artificial intelligence and deep learning-powered digital pathology (“a field involving the digitization and computational analysis of pathology slides”).
“NEC Corporation (NEC; TSE: 6701) and Biomy, Inc. (Biomy) have signed a Memorandum of Understanding (MoU) for a joint marketing partnership to develop and expand artificial intelligence/deep learning (AI/DL)-based analytical platforms in the field of digital pathology. Through this partnership, the two companies aim to promote precision medicine for cancer patients and contribute to the advancement of the healthcare industry.”
So what is Biomy contributing?
“Biomy, which aims to realize personalized medicine through pathological AI technology, has developed DeepPathFinder™, a proprietary, cloud-based, AI/DL automated digital pathology analytical platform.”
And NEC?
“NEC has positioned healthcare and life sciences as a core pillar of its growth strategy. With a strong foundation in image analysis and other AI technologies, NEC has a long history of providing medical information systems such as electronic medical records to healthcare institutions.”
As I’ve said before, healthcare must deal with privacy concerns (protected health information, or PHI) similar to those NEC addresses in its other biometric product line (personally identifiable information, or PII). I personally can’t do nefarious things if I fraudulently acquire your digital pathology slide, but some bad actors could. Presumably the Biomy product is well protected.
Bredemarket