The last time anything arrived from me here, it was April 2023, and the argument was that clinical decision support does not have to mean a pop-up. I still believe that. What follows is not a retraction. It is the part I left out, which turns out to be the larger part.
That 2023 piece admired a group at the Medical University of South Carolina who wanted emergency physicians to send at-risk patients home with naloxone. Rather than throwing a modal window across the screen, they watched for signals already in the chart (e.g., a triage reason of drug overdose, or the words naloxone or Narcan typed into the free-text complaint) and then quietly dropped a suggestion into the history section of the note the physician was already writing. Take-home kits went from 25.7% of eligible encounters to about half. Three-quarters of the physicians surveyed rated the thing good or excellent, which is not a sentence anyone gets to write about a best-practice alert.
I credited the format and the timing. Interrupt less, arrive at a receptive moment. That reading is not wrong, and it is incomplete in a way that took me three years and somebody else’s data to see.
Look at what that intervention actually asked a physician to do. Hand the patient a box. That is the entire request, and it finishes inside the visit. No result comes back two days later. Nobody has to decide whether a borderline number means anything. No parent needs a phone call. No threshold for referral has to be weighed by a person who has eleven other charts open. The work terminates.
Without meaning to, I had chosen the friendliest possible case for non-interruptive decision support: one where the task closes on contact. Design the prompt well and the loop shuts by itself.
Most clinical work is not like that, and I think this is where a decade of decision support has quietly gone to die.
What the new data show
A study out in Pediatrics this summer looked at what children actually receive after a first diagnosis of high blood pressure. The guideline is not ambiguous: urinalysis and a chemistry panel for everyone, at the front. What happened instead is that the echocardiogram finished first, at 21.1%, ahead of the urinalysis at 19.9% and the chemistry panel at 17.7%.
Consider what those two tests cost to obtain. One of them needs a cup. The other needs somebody to arrange a referral, fight an insurer, find an appointment, staff a sonographer, and book cardiology reading time, and the guideline does not call for it until a medication is on the table, six to twelve months down the road. Every implementation framework I have ever worked from says the easy test wins. It lost.
Sort the tests a different way, though — by how much unfinished business each result creates — and the ranking stops being mysterious. An echocardiogram resolves. It reassures the family, or it moves the child to cardiology and the next several decisions belong to somebody else. A urinalysis showing trace protein resolves nothing at all. It produces a repeat test, a judgment call, a fuzzy threshold for phoning nephrology, and a family conversation that has to be had while the meaning of the number is still unsettled. There is nowhere for it to go. It becomes something the physician is now carrying.
Nobody skips a urinalysis because an abnormal result would make work. The mechanism is quieter than that and almost certainly below conscious awareness. Some orders close a visit. Others open a loop, and a loop can always be pushed to the next visit, defensibly, one child at a time, until several hundred thousand small reasonable choices add up to a number like 19.9%.
So the governance question I would put to any decision support proposal is no longer whether the alert fires cleanly. It is: for every result this thing can produce, what happens next, and whose name is on it? “The ordering clinician decides” is an acceptable answer. It is a terrible default, and it is what you get when the meeting ends five minutes early.
The longer version, including why your order sets may still be running a guideline that was retired in 2017, is on my site.
Also worth your time
Menon and colleagues, in BMJ Open, on why test results get missed — they name three situations where results reliably fall through: tests ordered by trainees, alerts handed to a covering clinician, and patients with nobody assigned as their physician. Every one of them is an ownership vacuum rather than a technology failure. Free to read.
Meyer and colleagues, in the Journal of General Internal Medicine, on catching delayed follow-up automatically — instead of nagging a clinician at the moment of ordering, they built an algorithm that goes looking for abnormal thyroid results nobody acted on within sixty days. This is software doing the work rather than assigning it, which is the whole argument above, implemented. Free to read.
Nugent and Kaelber, in Pediatrics — the study behind this issue. Two pages, open access, and worth reading in the original if only for how flat the authors keep their voices.
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