# Healthcare Facilities Scraper – OpenStreetMap (OSM) (`dataquarry/healthcare-facilities`) Actor Extract healthcare facilities from OpenStreetMap by area, radius, or name: pharmacies, doctors, dentists, clinics, hospitals & nursing homes. Get speciality, dispensing, contact and address. No API key; open (ODbL) data. - **URL**: https://apify.com/dataquarry/healthcare-facilities.md - **Developed by:** [Daniel Brenner](https://apify.com/dataquarry) (community) - **Categories:** Lead generation, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Healthcare Facilities Scraper – Pharmacies, Clinics, Doctors & Dentists (OpenStreetMap) Extract **healthcare facilities from OpenStreetMap** by area, radius, or name — **no API key, no medical-directory subscription, no anti-bot battles**. Open, legal (ODbL) data you can redistribute. Public facility listings only — **no patient data**. Give it an area like `"Manchester, United Kingdom"` and get back tidy rows for every pharmacy, doctor's surgery, dentist, clinic, hospital and nursing home: name, **facility type**, **speciality**, **dispensing**, emergency flag, operator, full address, coordinates, contact, and the raw OpenStreetMap tags. You can also search **around a point** (every clinic within X km) or **filter by name** (e.g. every `"Boots"` pharmacy). ### Why use this scraper? - **Healthcare-specific fields.** Beyond a generic POI dump — `facility_type`, normalized `healthcare`, `speciality`, `dispensing` (pharmacies) and `emergency` are parsed out of the OpenStreetMap tags. - **Legal & open.** OpenStreetMap data is ODbL-licensed — redistributable with attribution. Facility listings, **not patient/PII data**. No login. - **No API key.** No medical-data provider account, no quota. - **Search by area, radius, or name.** A whole city/region, everything within X metres of a point, or every facility of one brand. - **Filter by type.** Pharmacies only, or clinics + doctors, etc. - **No duplicates.** When OpenStreetMap maps one facility twice (a node and a building outline), you get a single, richer row. - **Honest data.** Every value comes straight from OpenStreetMap; anything not mapped is left empty (`null`) — never guessed. - **Global coverage & reliable.** Anywhere OSM has data; retries across multiple Overpass mirrors. ### Great for - Medical / pharmacy / clinic directories and finder apps - Healthcare market research, coverage and access analysis - B2B lead lists for healthcare suppliers and services - Care-access mapping, public-health datasets, AI/RAG pipelines ### Input | Field | Type | Description | |---|---|---| | `area` | string | Place to search within, e.g. `"Manchester, United Kingdom"`. Geocoded to a bounding box. | | `aroundLocation` | string | *(optional)* Address/place to search **around** within a radius. Pair with `radiusMeters`. | | `radiusMeters` | integer | *(optional)* Radius in metres for around-a-location search (default `3000`). | | `centerPoint` | object | *(advanced)* Explicit center `{ "lat":.., "lon":.. }` to search around. | | `boundingBox` | object | *(advanced)* Explicit `{ "south":.., "west":.., "north":.., "east":.. }`. Overrides `area`. | | `facilityTypes` | array | *(optional)* Which types to include: `pharmacy`, `doctors`, `dentist`, `clinic`, `hospital`, `nursing_home`. Default: all. | | `searchTerm` | string | *(optional)* Only return facilities whose **name** contains this text (case-insensitive), e.g. `"Boots"`. | | `maxResults` | integer | Maximum number of facilities to return (default `1000`). | #### Example input ```json { "area": "Manchester, United Kingdom", "facilityTypes": ["pharmacy", "doctors", "dentist", "clinic"], "maxResults": 500 } ```` Every Boots pharmacy within 15 km of a point: ```json { "aroundLocation": "Leeds City Centre", "radiusMeters": 15000, "facilityTypes": ["pharmacy"], "searchTerm": "Boots" } ``` ### Output One row per facility: | Field | Description | |---|---| | `name` | Facility name | | `facility_type` | pharmacy / doctors / dentist / clinic / hospital / nursing\_home | | `healthcare` | Normalized OSM healthcare value | | `speciality` | Medical speciality (from `healthcare:speciality`) | | `dispensing` | Pharmacy dispensing flag | | `emergency` | Emergency service flag | | `operator`, `brand` | Operator (e.g. NHS) and brand/chain | | `branch` | Branch / location name of a chain outlet (e.g. `Times Square`) | | `wheelchair` | Accessibility | | `latitude`, `longitude` | Coordinates | | `street`, `housenumber`, `city`, `postcode`, `country` | Address | | `state` | State / province (`addr:state` / `addr:province`); common in US/CA/AU | | `phone`, `email`, `website`, `opening_hours` | Contact + hours | | `osm_id`, `osm_type`, `all_tags`, `source_url` | OpenStreetMap identifiers, raw tags, and link | | `full_address` | All present address parts in one string (e.g. `Main St 1, 10115 Berlin`) | | `map_url` | Google Maps link to the coordinates | #### Example output ```json { "name": "Boots", "facility_type": "pharmacy", "healthcare": "pharmacy", "speciality": null, "dispensing": "yes", "emergency": null, "operator": "Boots UK", "brand": "Boots", "city": "Manchester", "postcode": "M1 1AA", "country": "GB", "phone": "+44 161 000 0000", "opening_hours": "Mo-Sa 09:00-18:00", "osm_type": "node", "source_url": "https://www.openstreetmap.org/node/..." } ``` Any field is `null` when the facility hasn't tagged it in OpenStreetMap — values are never guessed. ### FAQ **Do I need an API key or account?** No — give it an area (plus optional radius/name filters) and run. No data-provider key, no quota, no setup. **Is the data legal to use and redistribute?** Yes. It comes from OpenStreetMap under the Open Database License (ODbL): public data you can redistribute with attribution (© OpenStreetMap contributors). No logins, no Terms-of-Service violations. **How is this different from a Google Maps scraper?** It uses open OpenStreetMap data instead of scraping a site behind anti-bot defenses and Terms of Service — so it's legal, needs no API key, and returns an honest `null` for anything OSM hasn't mapped instead of guessing. It returns facility data only (type, speciality, contact) — no patient or personal data. **How much does it cost?** Pay-per-result: **$3 per 1,000 results** — you only pay for the rows you actually get. **Which countries does it cover?** Worldwide — anywhere OpenStreetMap has data. **How fresh is the data?** It's pulled live from OpenStreetMap at run time, so it reflects the current map. ### Data source & license Data comes from **OpenStreetMap** via the public **Nominatim** (geocoding) and **Overpass** (querying) APIs. OpenStreetMap data is **© OpenStreetMap contributors**, licensed under the **Open Database License (ODbL)**. If you publish or redistribute results, attribute "© OpenStreetMap contributors". ### Notes - Coverage and tag richness vary by region — OSM is community-mapped, so cities are richer than rural areas. - This returns **facility** information (names, addresses, phones, specialities) — not individual practitioners or any patient data. ### More OpenStreetMap data actors Part of **dataquarry**'s family of clean, ODbL OpenStreetMap extractors — same flexible **area / radius / bounding-box / name** search, same honest-null data (a field that isn't mapped is left empty, never guessed): - [OpenStreetMap Places Scraper](https://apify.com/dataquarry/osm-places-scraper) — POI & local business, 115+ categories - [EV Charging Stations Scraper](https://apify.com/dataquarry/ev-charging-stations) — socket types, power (kW), networks - [Hotels & Lodging Scraper](https://apify.com/dataquarry/hotels-lodging) — stars, rooms, brands - [Healthcare Facilities Scraper](https://apify.com/dataquarry/healthcare-facilities) — pharmacies, doctors, dentists, clinics - [Tourist Attractions & Museums Scraper](https://apify.com/dataquarry/tourist-attractions) — Wikidata & Wikipedia links - [Fuel Station Scraper](https://apify.com/dataquarry/fuel-stations) — fuel types, brands, payment methods - [Supermarket & Grocery Scraper](https://apify.com/dataquarry/supermarkets) — brands, organic, payment methods # Actor input Schema ## `area` (type: `string`): Place to search within, e.g. "Manchester, United Kingdom". Geocoded to a bounding box via Nominatim. Provide this OR a bounding box OR a center for radius search. ## `aroundLocation` (type: `string`): Optional. An address or place to search AROUND within a radius. Geocoded to a center point; set the radius with "radiusMeters". ## `radiusMeters` (type: `integer`): Radius in meters for the around-a-location search. Default 3000. ## `centerPoint` (type: `object`): Optional advanced alternative: an explicit center as {"lat":.., "lon":..}. Overrides Around Location. ## `boundingBox` (type: `object`): Explicit bounding box as {"south":..,"west":..,"north":..,"east":..}. Overrides Area. ## `facilityTypes` (type: `array`): Which facility types to include. Supported: pharmacy, doctors, dentist, clinic, hospital, nursing\_home. Default: all of them. ## `searchTerm` (type: `string`): Optional. Only return facilities whose name contains this text (case-insensitive), e.g. "Boots", "NHS". ## `maxResults` (type: `integer`): Maximum number of facilities to return. ## Actor input object example ```json { "area": "Manchester, United Kingdom", "radiusMeters": 3000, "facilityTypes": [ "pharmacy", "doctors", "dentist", "clinic" ], "maxResults": 1000 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "area": "Manchester, United Kingdom", "facilityTypes": [ "pharmacy", "doctors", "dentist", "clinic" ] }; // Run the Actor and wait for it to finish const run = await client.actor("dataquarry/healthcare-facilities").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "area": "Manchester, United Kingdom", "facilityTypes": [ "pharmacy", "doctors", "dentist", "clinic", ], } # Run the Actor and wait for it to finish run = client.actor("dataquarry/healthcare-facilities").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "area": "Manchester, United Kingdom", "facilityTypes": [ "pharmacy", "doctors", "dentist", "clinic" ] }' | apify call dataquarry/healthcare-facilities --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dataquarry/healthcare-facilities", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Healthcare Facilities Scraper – OpenStreetMap (OSM)", "description": "Extract healthcare facilities from OpenStreetMap by area, radius, or name: pharmacies, doctors, dentists, clinics, hospitals & nursing homes. Get speciality, dispensing, contact and address. No API key; open (ODbL) data.", "version": "0.0", "x-build-id": "drM184HG3ncI2ccNz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dataquarry~healthcare-facilities/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dataquarry-healthcare-facilities", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dataquarry~healthcare-facilities/runs": { "post": { "operationId": "runs-sync-dataquarry-healthcare-facilities", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dataquarry~healthcare-facilities/run-sync": { "post": { "operationId": "run-sync-dataquarry-healthcare-facilities", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "area": { "title": "Area", "type": "string", "description": "Place to search within, e.g. \"Manchester, United Kingdom\". Geocoded to a bounding box via Nominatim. Provide this OR a bounding box OR a center for radius search." }, "aroundLocation": { "title": "Search around a location (radius)", "type": "string", "description": "Optional. An address or place to search AROUND within a radius. Geocoded to a center point; set the radius with \"radiusMeters\"." }, "radiusMeters": { "title": "Radius (meters)", "minimum": 1, "type": "integer", "description": "Radius in meters for the around-a-location search. Default 3000.", "default": 3000 }, "centerPoint": { "title": "Center point (advanced radius)", "type": "object", "description": "Optional advanced alternative: an explicit center as {\"lat\":.., \"lon\":..}. Overrides Around Location." }, "boundingBox": { "title": "Bounding box (advanced)", "type": "object", "description": "Explicit bounding box as {\"south\":..,\"west\":..,\"north\":..,\"east\":..}. Overrides Area." }, "facilityTypes": { "title": "Facility types", "type": "array", "description": "Which facility types to include. Supported: pharmacy, doctors, dentist, clinic, hospital, nursing_home. Default: all of them.", "items": { "type": "string" } }, "searchTerm": { "title": "Filter by name (optional)", "type": "string", "description": "Optional. Only return facilities whose name contains this text (case-insensitive), e.g. \"Boots\", \"NHS\"." }, "maxResults": { "title": "Max results", "minimum": 1, "type": "integer", "description": "Maximum number of facilities to return.", "default": 1000 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```