8 December 2025 · Medows · Dr. Soumyadeep Adhikari & Alapan Mondal
Pediatric Dosing in the Busy OPD
A 14 kg child, the wrong dose, and the dose-checking literature that says it's the system, not the resident.
Dr. Soumyadeep Adhikari, Alapan Mondal
2 authors
A four-year-old, 14 kg, casualty at 11 p.m. Bronchopneumonia. The intern writes the amoxicillin order: 250 mg three times a day.
The senior, looking over his shoulder during a brief handover pause, asks: "What dose are you using?"
"Forty per kg per day."
"That's 560 mg per day. Three times a day is about 186 mg per dose. You wrote 250."
The intern corrects it. It is a minor error. The drug is amoxicillin, the patient is robust, the dose he wrote was a third over instead of a tenth under. He moves on, embarrassed.
The error he actually made
He did not miscalculate. Follow the exchange again and notice that he never did the arithmetic at all.
He knew the correct rule and stated it accurately when asked. What he wrote was 250 mg — a round, familiar, adult-shaped number that lives in every clinician's muscle memory because amoxicillin comes in 250 and 500. Under load, a recalled number substituted itself for a computed one, and the substitution was invisible to him because the recalled number was plausible. 186 mg and 250 mg belong to the same universe. Nothing felt wrong.
That is the characteristic paediatric error, and it explains why "be careful with paediatric doses" has never worked as an intervention. Carefulness detects implausible answers. It does not detect plausible ones.
Why this specialty is structurally error-prone
Paediatric prescribing has more places to go wrong per order than almost anything else on a ward:
- Every dose is a calculation, and the input is a weight that may have been estimated rather than measured at 11 p.m.
- Per-day versus per-dose is a division step that exists in no adult prescription, and it is the step in this case.
- Milligrams versus millilitres. The order is written in mg. The syrup on the shelf is 125 mg/5 mL or 250 mg/5 mL, and someone has to convert — usually a nurse or a parent, not the prescriber.
- The decimal point. A tenfold error in an adult is usually caught by implausibility. In a child, the plausible range spans an order of magnitude across ages, so tenfold errors survive.
- The margin is smaller. A 14 kg child has less reserve to absorb the error that a 70 kg adult would shrug off.
Most pediatric dosing errors look like this. Not catastrophic. Slightly wrong. Hard to notice unless someone checks.
The published rates
The published rates are worse than residents are taught to expect. Kaushal and colleagues (JAMA, 2001) audited a paediatric inpatient ward and found a medication error rate of 5.7 per 100 orders, with 57% being potential adverse drug events — errors that could have caused harm if not caught. The actual harm rate was lower (1.1 ADEs per 100 admissions), because most errors got caught by a pharmacist or nurse or, as above, the senior glancing at the order.
The gap between those two numbers is the whole story. The system is not preventing errors; it is intercepting them. And the interception layer is entirely human — a pharmacist who happened to be at their desk, a nurse who has drawn up this drug a thousand times, a senior who happened to be standing behind the intern during a pause in handover.
The robust catch system is mostly people. In a busy casualty without a pharmacist embedded in the workflow, the catch fails. Not sometimes — predictably, on the nights when the interception layer is busy, which are exactly the nights the error rate is highest.
Soft signal, not hard stop
Medows handles pediatric dosing by being patient-grounded. When the intern types the amoxicillin order, the patient's weight is on the screen. The standard dose range for amoxicillin in pediatric bronchopneumonia (40–50 mg/kg/day divided three times) auto-populates as a recommended range below the dose field, derived from the AIIMS pediatric formulary. If the typed dose falls outside, the line greys with a soft note: "Outside typical range for this weight."
This is not a hard stop. It is a soft signal — the way a pharmacist looks up from their desk when an unusual dose lands. The intern reads it, adjusts if needed, moves on. The patient gets the right dose. The dose-checking is adjacent to where the order is being written, not a separate workflow.
The refusal to block is deliberate. Out-of-range doses are frequently correct: loading doses, renal adjustment, a specialist's deliberate deviation, a drug being used off the standard indication. A system that blocks them trains the prescriber to defeat it, and a prescriber who has learned to defeat the check will defeat it on the night it was right.
What the range has to carry
A recommended range on its own is only half the help. The version that actually prevents the error carries four things:
- The range in the same units as the rule the doctor was taught — mg/kg/day.
- The arithmetic already done, for this child's weight, at this frequency. 560 mg/day; 186 mg per dose. The division step is the failure point, so the tool should own it.
- The source, so it can be disagreed with. A formulary the hospital recognises, not an unattributable number.
- The volume. 186 mg of a 125 mg/5 mL suspension is 7.4 mL. That is the number a parent will measure at home with a spoon, and it is the number nobody computes at 11 p.m.
The 5.7-per-100 number from 2001 is, for what it is worth, almost certainly the same today in the average busy unit. The catches happen because of the doctors and the pharmacists, not because the technology improved.
If the AI consult already knows the patient is 14 kg, it should know what the dose range is. That is the bar.
Authors
Dr. Soumyadeep Adhikari, MBBS, MD
PGT General Medicine, RG Kar Medical College
MBBS from Calcutta Medical College. Currently a post-graduate trainee in General Medicine at RG Kar Medical College, Kolkata.
Alapan Mondal, B.Tech, M.Tech, IIT BBS
Founder, Medows
Founder of Medows. Building doctor-side AI workspaces.
Medows is a clinical AI workspace for the doctor on rounds. Learn more or write to alapan@medows.ai / alapanx@gmail.com.