Diagnostic information measures how much uncertainty a test is expected to resolve before its result is known, using sensitivity, specificity, and a stated starting disease probability; worked examples show how starting probability changes expected learning, why tests with similar conventional accuracy can provide different information, and how that expectation differs from the evidence supplied by an individual result; across 273 pooled diagnostic profiles from 210 reviews, we place this established measure on an empirical reference scale for interpreting and reporting diagnostic information across tests and thresholds, with the median profile resolving 29.2% of starting uncertainty at a standardised 20% starting probability.