Forecasting Against the Visit Schedule

Part of Trial Pharmacy (PHARM) Training: Supply, Expiry and Forecasting.

About 2 minutes. Free, in your language, no account needed.

Why this matters

A stockout stops treatment. For a participant that is a missed dose; for the trial it is a major deviation and sometimes a lost endpoint.

Almost every stockout was visible weeks earlier in data the pharmacy already held.

Forecast from visits, not from stock

Counting what is on the shelf tells you the present. Counting who is due tells you the future.

Take the visit schedule, count participants due in the resupply lead time, multiply by what each needs, and compare to usable stock.

Usable means in date at the time of the visit, and available in that participant's stratum.

Expiry is measured against the visit, not today

A kit expiring in five weeks is not stock for a participant due in seven.

This is the most common forecasting error. A shelf that looks full can hold nothing usable for the people actually coming.

Keep an expiry list sorted by date, not by kit number.

Know your lead time honestly

Resupply takes longer than the stated lead time. Approvals, shipping, customs, depot scheduling and receipt checks all add days.

Use the time it actually took last time. If a resupply took eleven days when the manual says five, plan on eleven.

Raise it early and in writing

A shortage raised early is a logistics task. The same shortage raised three days out is an escalation involving several people and sometimes a protocol deviation.

Email, so there is a record of when the site flagged it.

In practice

Twelve participants are due in the next three weeks. Fourteen kits are on the shelf, of which five expire before the relevant visits.

You have nine usable kits for twelve visits. You raise a resupply request today, not when the shelf looks empty.

What this looks like when it goes wrong

A pharmacy tracks total stock and it never drops below twenty. Two participants in a small stratum cannot be dispensed to, because stock in that stratum ran out while the total stayed healthy.

Both miss a dose. The aggregate number concealed the shortage completely.

Key takeaways