Healthcare & Pharmacy Data Scraping

No. Not for any client, at any price, in any jurisdiction. Patient records, individual health information, prescription data relating to identifiable people, and anything behind patient or clinician authentication are categorically excluded.

This is not caution for its own sake. Health data carries the strictest treatment in essentially every privacy regime and the exposure attaches to whoever holds it — which would be you. A vendor willing to blur this line will also blur it about you.

Where a market permits them to be published publicly, yes. Some jurisdictions publish prescription pricing openly; others restrict it, and in those markets the data does not exist publicly to collect.

We assess this per market during scoping and state what it excludes rather than implying uniform coverage. Over-the-counter pricing is publishable almost everywhere and is where most of this work sits.

Because the same active ingredient appears at multiple strengths, in multiple forms, in packs from 12 to 96. A pack price comparison across those combinations is not a comparison — it is noise with the appearance of precision.

We parse active ingredient, strength, form and pack count, then compute price per unit dose ourselves rather than taking retailer-displayed unit prices, which are inconsistently calculated. Our parse rate is around 97.6% and we report where it fails, which clusters in compound and topical products.

They are a useful early signal rather than a prediction. Two patterns matter: out-of-stock spreading across multiple unrelated retailers at once, and per-order quantity limits appearing, which pharmacies often impose before stock actually runs out.

Quantity limits are the earlier indicator in our experience, which is why we capture qty_limit as its own field. This is observational evidence of retail-level pressure, not visibility into manufacturing or distribution, and we would not present it as the latter.

Yes, and it is one of the more valuable things we do in this category. The files are public and mandated but published in inconsistent formats with variable item descriptions and mixed charge types, often running to hundreds of thousands of rows.

We parse to a consistent structure, classify charge types explicitly, normalise descriptions against code taxonomies where codes exist, and retain row-level source references plus prior versions so change detection works. Rows too ambiguous to classify confidently are flagged rather than guessed.

Professional registration and practice information from public registers, yes — name as registered, registration number, specialty, practice address, registration status. These are public professional facts published deliberately.

We do not collect personal contact details, personal social media, or build individual profiles beyond what a public professional register contains. Patient reviews naming clinical detail about an individual are excluded from deliverables even where publicly posted.

Own-label lines are flagged and indexed against comparable branded products matched on active ingredient, strength and form. Identification uses retailer-specific brand mappings rather than name matching, since many pharmacy own-label brands do not carry the retailer's name.

This is often the most commercially interesting output for pharma clients, because own-label competition in OTC categories is intense and the price index between own-label and branded drives category strategy directly.

We collect publicly accessible product and pricing pages without accounts or credentials, which is the same position as any retail pricing collection. Pharmacy retail terms often restrict automated access and we say so rather than glossing over it.

What differs in healthcare is the sensitivity of adjacent data, which is why our exclusions are categorical rather than case-by-case. You receive a written methodology document per source and a DPA before signature, which in this sector is usually what allows the purchase to proceed.

We quote individually. The drivers are retailer or facility count, product scope, market count, and whether price transparency file parsing is included — that last one is labour-intensive because file structures vary per facility.

A defined OTC category across several pharmacies at daily refresh sits at the lighter end. Multi-market pricing plus price transparency structuring across many facilities sits considerably higher. One scoping call, a free pilot on your own category within 48 hours, then a fixed monthly quote. Request a quote.