Crawled clinic directories — advertised services
RepVector directory sweeps (MDDcare and partner directories)
In a RepVector build, this dataset names the individual practitioners and organisations you can actually call.
What this dataset is
Clinics and clinicians harvested from public commercial care directories, each row carrying the treatments the site actually advertises (TMS / transcranial magnetic stimulation, esketamine / Spravato, ketamine, medication management, therapy), the insurers accepted, street address, phone and a named clinician where published. This is the only source that knows which psychiatry practices deliver a specific modality — federal registries record taxonomy, never the service line. Use it whenever the question names a treatment or modality rather than a specialty. It is published by RepVector directory sweeps (MDDcare and partner directories) and can be queried at place, county and state level, refreshed annual full sweep, incremental in between. Each row is an individual entity — an organisation, site or practitioner — so results can be filtered, routed and turned directly into a call list.
Why it is useful
- Yields names, specialties, practice addresses and, where published, phone numbers.
- Supports specialty and taxonomy filtering so a call list matches what you sell.
- Feeds the tiering engine that ranks who to see first and explains why.
Questions it helps answer
- Who specifically should I see in this territory this week?
- Which specialties are dense enough here to build a route around?
- Which named targets are new since my last pull?
How different verticals use it
RepVector is vertical-agnostic: this dataset is selected by what your question asks for, not by industry. These are common ways teams put it to work.
Builds named call lists with specialty, address and phone straight from the registry.
Finds counsellors, prescribers and programmes eligible for referral partnerships.
Targets practices by size and specialty for platform or EHR adjacent sales.
Segments practice owners as commercial banking or insurance prospects.
How RepVector uses it
- You describe a market in plain language. The geography resolver turns the place you named into the exact identifiers this dataset needs — city to county to state, plus DMA where relevant — so a query at place runs without you knowing any codes.
- The planner selects Crawled clinic directories — advertised services only when your question matches what it actually reports. It is never included to pad a result.
- Returned rows are normalised into the shared metric layer, so figures from RepVector directory sweeps (MDDcare and partner directories) line up with every other source in the same dashboard instead of sitting in an isolated table.
- Quality checks score coverage and recency. If RepVector directory sweeps (MDDcare and partner directories) suppresses or omits a value for your geography, the gap is reported as a gap — nothing is estimated or filled in.
- The result renders as charts, KPIs and, where the rows are entities, prioritised targets you can export to PDF, Excel, CSV or JSON.
What it does not tell you
- Registry contact details reflect what the publisher holds; they age and are verified against other sources rather than trusted alone.
How it fits with the rest of the catalog
Provider rosters answer who; need and spending data answer why that person is worth the visit. RepVector queries every selected dataset against the same resolved geography and time window, then normalises the results into one metric layer so they can be charted side by side. These datasets are the most common companions to Crawled clinic directories — advertised services:
Other providers datasets
Build the list for one county and see whether the names are right.
Ask in plain language. RepVector finds the universe, enriches each target from its own website, scores it 0–100, and hands you a ranked call list with phones, addresses and named contacts.
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