HAS data: 4,342 clinics mapped and targeted in 9 days (2026)

The Haute Autorité de Santé (HAS, France’s National Authority for Health) publishes open-access quality data on more than 4,300 French healthcare facilities: certification, satisfaction scores, and patient safety indicators. It’s one of the richest commercial assets in the healthcare sector, and almost nobody uses it as one.

A French healthcare messaging platform decided to do just that. In 9 days, it had 4,342 clinical facilities mapped with their complete HAS data and more than 9,000 anesthesiologists and nurse managers qualified, giving its 10 sales reps a comprehensive view of the private clinic market.

This case study covers what the HAS quality overview contains, why this data is an underused buying signal, the 9-day mapping method, and what a specialized business agent brings compared with a general-purpose AI assistant.

What does the HAS quality overview contain?

The HAS quality overview is a public reference database covering more than 4,300 French healthcare facilities, searchable and filterable facility by facility. For each one, it publishes the certification result (certified with distinction, certified, certified with conditions, not certified), e-Satis patient satisfaction indicators, and safety indicators such as post-surgical readmissions and healthcare-associated infections.

Everything can be filtered by facility type, by activity (oncology, surgery, psychiatry, and nine other specialties), by geographic area, and by certification result. The data can even be exported. In practice, the HAS overview of healthcare facility quality is an open database on the quality status of France’s entire hospital landscape.

For a sense of the market’s scale: as of late 2024, DREES (the French health ministry’s statistics directorate) counted 980 for-profit private clinics in France, out of a total of 2,965 healthcare facilities. The HAS overview goes down to the level of each individual site, which explains its more granular count.

Why is HAS data an underused buying signal?

HAS data is a buying signal because it shows where a facility has a dated quality problem to solve. A facility certified with conditions must fix its gaps and undergo a full new inspection within 6 to 24 months. That deadline creates a window in which the quality department reinvests, reorganizes, and makes purchasing decisions: exactly when a healthcare supplier wants to be in the room.

Most sales CRMs don’t carry this information. Apollo, Sales Navigator, or a purchased database give you a name and a job title, never the certification status or the satisfaction score. We break down this dynamic in our article on HAS certification as a buying signal, and more broadly in what Sales Navigator can’t see in the French hospital market.

So the quality score isn’t administrative data. It’s a prioritization trigger: a sales rep who knows which facilities are certified with conditions, and since when, knows where to strike first.

How do you map 4,342 clinics in 9 days?

The mapping relies on three chained operations: scraping the HAS overview, structuring each facility around its FINESS identifier, and then enriching the decision-makers. The whole thing was delivered in 9 days, from order to final, usable database.

The first stage scrapes the entire HAS overview: name, type, address, region, certification status, scores by criterion, and certification date to anticipate renewals. The second stage anchors each row to its FINESS number, the nine-character identifier from the Fichier national des établissements sanitaires et sociaux (FINESS, France’s national registry of healthcare facilities), managed by the health authorities. FINESS distinguishes the legal entity from each geographic site, which makes it possible to reconcile HAS data and contacts without duplicates. The third stage identifies 4 to 5 decision-makers per facility (CIO, executive management, nurse manager, quality manager) and enriches them with a professional email address, phone number, and LinkedIn profile.

Each group of prospects was then delivered in three tiers, classified as hot, warm, or cold based on the facility’s signals. A sales rep doesn’t tackle a list of 9,000 names: they tackle the hot tier first. This logic of ranking by buying signal, not by enthusiasm, shapes the entire delivery.

This is exactly the kind of project we scope in 30 minutes during a healthcare prospecting scoping call, to identify the public sources that already describe your market. The overall method is documented in the guide to MedTech prospecting in France.

Why does a specialized business agent beat a general-purpose AI agent on HAS data?

A specialized business agent beats a general-purpose agent because it queries a specific structured database, not the entire web. The platform was already using a general-purpose AI agent for internal purposes. For the HAS database, it switched to a specialized Agify agent, connected directly to the 4,342 facilities and their decision-makers.

The difference is operational. A sales rep asks in plain language, “List the clinics certified with conditions in Normandy,” or “Which facilities have a certification expiring in six months?”, and the agent returns the filtered list in seconds. Before a meeting, it generates a complete pre-call brief: certification status, scores, identified contacts, recent news. A general-purpose assistant can’t do this because it doesn’t have the database at hand: it infers, and on medical data, inference has no commercial value.

Specialization isn’t a technical refinement. It’s what turns a 4,342-row database into a tool a sales rep opens every morning.

What were the results for a healthcare messaging platform?

The results come down to three numbers: 4,342 clinical facilities mapped with their HAS data, more than 9,000 anesthesiologists and nurse managers qualified, all delivered in 9 days. Each record was delivered only with its verified LinkedIn profile, to guarantee usable data rather than a ghost contact.

Beyond the volume, the order addressed a pressing commercial need. The platform was preparing a key-account tender representing €600,000 in potential revenue and needed a summary combining certification and activity volume to make its case. The database delivered served that specific bid, then became the daily tool for the 10 sales reps across the entire private clinic market.

This model translates to other contexts. Any supplier selling to healthcare facilities described by a foundational public source (HAS, FINESS, authorizations from ARS regional health agencies) can build the same asset: a comprehensive, up-to-date map, enriched with decision-makers and searchable in plain language. In the European market, the same structured sourcing logic enabled an imaging MedTech company to build more than 10,000 medical leads across 18 countries in 8 days, without any shared centralized registry.

Frequently asked questions

Is HAS overview data public and reusable?

Yes. The HAS quality overview is open access and publishes, facility by facility, the certification result and quality indicators. This data describes the quality status of France’s hospital landscape and can be aggregated to build a commercial map of the healthcare market.

What is a FINESS number, and why is it useful for prospecting?

FINESS is the nine-character identifier from the Fichier national des établissements sanitaires et sociaux, France’s national registry of healthcare facilities. It distinguishes the legal entity from the geographic site, which makes it possible to reconcile different sources (HAS data, contacts, authorizations) around the same facility without duplicates. It’s the linchpin of a clean healthcare database.

How long does it take to map a healthcare market like private clinics?

In this case, full delivery took 9 days, from order to the final database, enriched and ranked by tier. The timeline depends on the number of facilities, the number of decision-makers per organization, and the enrichment sources used, but the order of magnitude is a few days, not a few months.

Isn’t a general-purpose AI agent enough to use this data?

No, not on a specialized business database. A general-purpose agent searches the web and infers when it doesn’t know. A specialized agent is connected to a specific structured database and answers only from it, with fine-grained filters (region, certification status, deadline) and reliable pre-meeting briefs.

Conclusion

HAS quality data is public, comprehensive, and dated. Those three properties make it a first-rate buying signal for anyone selling to healthcare facilities, and a blind spot for most CRMs. This healthcare messaging platform’s case shows the full chain: scrape the overview, anchor each row to its FINESS number, enrich the decision-makers, rank by signal, and make it all searchable through a specialized business agent.

The asset isn’t the list. It’s the reading of public sources that nobody else aggregates. If you sell to clinics, hospitals, or care organizations, let’s look at your situation in 30 minutes: together, we’ll identify the sources that already describe your market and how to turn them into a qualified pipeline.

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Agify is a French agency specializing in AI prospecting agents for the healthcare sector. It builds market databases from public sources (HAS, FINESS, BOAMP, RPPS) and makes them usable for sales reps through specialized business agents.