Journal

Analysis from our data

These pieces are data journalism on our own dataset: every number in them is computed at build time from the same manifests that render this site's tables, so an analysis can never disagree with the pages it analyzes. Where the data is inherited, thin, or unverified, the analysis says so — that is frequently the finding.

• How much GLP-1 telehealth pricing is actually verifiable

  We audited every pricing row in our own dataset by evidence status. The headline: not one figure meets our verification standard, and the distribution of what remains says a lot about how this market publishes prices.

• The entry-price illusion: what GLP-1 teaser rates hide

  Computed from our pricing manifest: how advertised starting prices relate to ongoing rates across providers, and why the cheapest number on a landing page is the least predictive one in the dataset.

• The pharmacy disclosure gap: the question no provider answers

  We asked which pharmacy fills each provider's prescriptions and whether it is a 503A pharmacy or 503B facility. The response rate across every provider we cover is zero — and that single blank field caps every score we can award.

How journal pieces differ from news

News explainers reconstruct external events from primary sources. Journal pieces make an argument from computation: the claims are ours, the arithmetic is reproducible from the data behind this site, and the inference is labeled as inference. Neither format quotes marketing copy as fact, and both fall under the same corrections policy.