I think we can all agree that if a breast is not diseased, it should not be removed. High on the list of modest, achievable healthcare goals should be avoiding misdiagnosing breast cancer, and avoiding cutting off healthy breasts.
There are widely known methods and proven technologies that are available for achieving this goal. Instead of applying them, the leading minds in the healthcare technology field ignore them, and instead invest billions of dollars in exotic, cool-sounding AI software that may deliver benefits sometime in the future. Something is deeply wrong here.
Yes, breasts are cut off by mistake
Perhaps you think I'm exaggerating? Here is a recent cover from the NY Post:
The woman felt a lump and had a biopsy. The diagnosis was cancer. She was sent to another hospital for surgery.
Makes, sense, right? Someone should double-check. The rule in carpentry is "measure twice, cut once." When breasts are involved? Double-check should be the minimum; triple-check would be nice.
Checklists
Wait, hasn't someone gone into this already? For healthcare, specifically? Oh, yeah, there's that book written by that famous doctor on this very subject, Atul Gawande:
He dives real deep into checklists in many fields, medicine in particular. Here's a partial summary by Malcolm Gladwell he puts on his site:
The hospital at which the healthy breast was removed knew about checking.They wrote a procedure for it!
What was the procedure? More paperwork. Another in the long list of things doctors have to plow through before they can do their jobs. If doctors actually took all the paperwork seriously, they'd get nothing done. In other words, the "procedure" was just paperwork created by lawyers and bureaucrats that makes life harder and helps nothing. As usual.
Effective, automated workflow checklists
What the healthy-breast-removing hospital did was not what Gawande had in mind, of course. He was thinking group meetings at which everyone goes through each step and signs off. Something meaningful. But that doesn't exactly apply here, since the double-check pathology exam should have taken place before surgery was scheduled. Thinking about it, there are many similar situations in which the checklists are spread out.
There's a concept and proven technology that applies here: workflow. Think of a flowchart with worksteps, lines and conditional branches. Here's a trivial example:
Think of the workflow as being driven not by paper diagrams like this, but implemented in software that interacts with EMR's and people, and tells them what to do.
In this case, when the patient was referred for breast surgery, a proper workflow would have scheduled the pathologist to examine the cancer biopsy data before anything else happened. If the results were negative, as they would have been, the patient would have been notified and that would be the end of it. Only if the results were positive would the system allow breast surgery to be scheduled.
Workflow systems assure that all the work that should be done is done. They eliminate paperwork by putting the checking and doctor sign-offs into the system. No lawyers. No bureaucrats. Near-zero errors. Corrections and enhancements can be made to the workflow without massive re-training and human error. Workflow is like a system-wide, automated checklist, with all the checklist benefits and more.
Let's do AI instead!
Workflow software exists. It's implemented in many industries, even sometimes in healthcare. It works. It reduces human labor and improves outcomes. Why isn't it ubiquitous in healthcare?
Workflow works, solves problems and is understandable. AI, by contrast, is cool, the coming thing and few of the people yakking about it understand it. AI is exploding:
I see a recurring pattern here: people jumping on the new trend, the leading edge, the cool new stuff that "everyone says" is the coming thing, that none of them really understands. And ignoring relatively prosaic technology that works and can provide real benefits today.
Conclusion
Cutting off healthy breasts tells us everything we need to know about exotic new AI, which is at the far end of the innovation spectrum I've described for healthcare here, and illustrated here. Workflow is at the simple end of the spectrum: proven, works, understandable and understood, delivers immediate benefits. I guess that's why the leading thinkers ignore it and all the "smart money" avoids it.