healthcare delivery – The Health Care Blog

The Business Reality of Healthcare AI

Jul 4, 2023• 1

BY KIM BELLARD

I was at the barbershop the other day and overheard one barber talking with his senior citizen customer about when – not if – robot AIs would become barbers. I kid you not.

Now, I don’t usually expect to heard conversations about technology at the barber, but it illustrates that I think we are at the point with AI that we were with the Internet in the late ‘90’s/early ‘00s: people’s lives were just starting to change because of it, new companies were jumping in with ideas about how to use it, and existing companies knew they were going to have to figure out ways to incorporate it if they wanted to survive. Lots of missteps and false starts, but clearly a tidal wave that could only be ignored at one’s own risk. So now it is with AI.

I’ve been pleased that healthcare has been paying attention, probably sooner than it acknowledged the Internet. Every day, it seems, there are new developments about how various kinds of AI are showing usefulness/potential usefulness in healthcare, in a wide variety of ways. There’s lots of informed discussions about how it will be best used and where the limits will be, but as a long-time observer of our healthcare system, I think we’re not talking enough about two crucial questions. Namely:

Who will get paid?
Who will get sued?

Now, let me clarify that these are less unclear in some cases than others. e.g., when AI assists in drug discovery, pharma can produce more drugs and make more money; when it assists health insurers with claims processing or prior authorizations, that results in administrative savings that go straight to the bottom line. No, the tricky part is using AI in actual health care delivery, such as in a doctor’s office or a hospital.

Guidelines vs. Personalized Medicine: the Battle for the Future of Healthcare

Jul 23, 2013• 23

By Joseph Kvedar, MD

As we grapple with provider shortages, the surge in chronic illness and the quality to price (QPR as they say in the wine business) challenge in US healthcare delivery, it’s hard to imagine a future that does not include some sort of guideline or algorithm-driven care. As providers take on more financial risk, one common strategy involves team-based care, and the attendant increase in decision-making and care delivery by non-physician clinicians. If the je ne sais quoi feature of a quintessentially great doctor is clinical judgment and instinct, one of the challenges of this transition to team-based care is how to harness that trait and use it efficiently.

Care decisions that are unassailable at a population level (e.g., women should have regular, routine PAP smears or smoking is bad for your health) or are algorithmic in nature (e.g., titration of treatment for uncomplicated hypertension or therapy for mild to moderate teenage acne) can all be effectively reduced to guidelines. This, in turn, allows a physician to delegate certain therapeutic decisions to non-physician providers while maintaining a high degree of care quality. It is also thought that this type of uniformity of care delivery will improve the QPR too, by decreasing variability.

How do we come up with guidelines? Typically they are based on large-scale, randomized, controlled clinical studies. As is nicely articulated in a recent JAMA opinion piece by Drs. Jeffrey Goldberg and Alfred Buxton (JAMA, June 26, 2013—Vol 309, No. 24, pg 2559), guidelines are formulated based on the inclusion criteria for these trials. This process gives us comfort that guidelines are based on rigorous science — and that is a good thing. The challenge arises when we realize that individuals do not reflect populations exactly. Clinical research is much more complex than wet lab work because people are complex and indeed unique. Every clinician has had the experience of prescribing a therapy to a patient who fit guideline criteria exactly and having the opposite outcome of what the guideline predicts.