Most labs bill the same test at several different prices. That is usually deliberate. The trouble starts when nobody can say what the spread is, or what a given discount actually bought.
For each test, look across your accounts at the price actually billed — not the price on the rate card, the one in the data. You are looking for three numbers: the lowest, the highest, and how many accounts buy it.
A health package billed at ₹1,700 to one account and ₹2,500 to another has a spread of ₹800 across eleven accounts. That is not automatically wrong. It is simply a fact most lab owners do not have to hand, and cannot negotiate without.
A lower rate is meant to buy something — usually volume. So put the two together:
| Account's price | Account's volume | Reading |
|---|---|---|
| Below average | Above average | Working as intended |
| Below average | Below average | A discount that bought nothing |
| Above average | Above average | Your best commercial relationship |
| Above average | Below average | Small account, probably fine |
The second row is the one worth a conversation. It is also the one nobody finds by looking at a rate card, because the rate card does not know about volume.
If you compute price as revenue divided by tests, and some of those test rows carry no price because of an export quirk, your average price collapses and one centre looks 1,200% cheaper than another. Divide by the tests that actually carried a price.
If one account took 22 of the 27 units of a test at a special rate, the "spread" for that test is really one negotiated contract, not a pricing policy. Any comparison that does not name the dominant account is going to mislead you.
Not a mass repricing. Pick the two or three accounts where the price is below your average and the volume is too, and ask what the rate was originally for. Often the answer is a volume promise from three years ago that quietly stopped being true.