# Japan Health & Medical Data API (`lentic_clockss/japan-health-data-search`) Actor Search Japanese health and medical datasets from e-Gov open data catalog and MHLW portal navigation links via SIP API. - **URL**: https://apify.com/lentic\_clockss/japan-health-data-search.md - **Developed by:** [kane liu](https://apify.com/lentic_clockss) (community) - **Categories:** Lead generation, MCP servers - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Japan Health & Medical Data Search Search across Japan's most authoritative health and medical data sources in one unified Apify Actor. This tool queries the **e-Gov Health & Medical Open Data Catalog** and the **MHLW (Ministry of Health, Labour and Welfare) Portal Navigation Links** to deliver structured, up-to-date results from Japanese government health databases. ### Why Japan Health Data Matters Japan maintains some of the most comprehensive public health datasets in the world. The Japanese government publishes health statistics, medical facility registries, pharmaceutical databases, disease surveillance reports, and welfare program data through multiple official portals. Accessing this Japan health data programmatically has traditionally required navigating fragmented Japanese-language portals, understanding different API conventions, and handling inconsistent data formats. This Actor solves that problem by providing a single search interface across two key Japanese medical database sources, returning normalized results ready for analysis, research, or integration into your data pipelines. ### Data Sources #### e-Gov Health & Medical Open Data Catalog (`egov_health`) The e-Gov open data platform is Japan's central government data portal. The health and medical subset includes datasets published by national ministries and agencies covering: - Public health surveillance and epidemiological data - Hospital and clinic registries across all Japanese prefectures - Pharmaceutical approval and drug safety databases - Health insurance and national medical expenditure statistics - Cancer registry data and screening program results - Maternal and child health records - Infectious disease monitoring reports including COVID-19, influenza, and tuberculosis - Mental health service utilization statistics - Nutrition surveys and dietary reference intakes for the Japanese population This source is ideal for researchers, policy analysts, and healthcare organizations seeking official Japanese government health datasets. The catalog is continuously updated as ministries publish new open data releases. #### MHLW Portal Navigation Links (`mhlw`) The Ministry of Health, Labour and Welfare (MHLW) is Japan's primary government body responsible for healthcare policy, medical regulation, social welfare, and labor standards. The MHLW portal navigation links dataset provides structured access to: - Policy documents and white papers on Japanese healthcare reform - Statistical reports on Japan's aging population and long-term care - Medical practitioner licensing and workforce data - Welfare program guidelines and social assistance frameworks - Food safety and pharmaceutical regulation notices - Occupational health and workplace safety standards - Links to regional health bureau resources across Japan This source is particularly valuable for navigating the extensive MHLW web presence, which contains thousands of pages of health policy documentation, statistical tables, and regulatory guidance that are otherwise difficult to discover through manual browsing. ### How It Works The Actor connects to the SIP API, which aggregates and indexes Japanese government data sources. When you provide a search keyword, the Actor queries each selected source in parallel using async HTTP requests, collects the results, and pushes them to the Apify dataset for easy export and integration. Each result record includes the original data fields from the source along with a `source` field indicating which database it came from (`egov_health` or `mhlw`), making it straightforward to filter and process results downstream. ### Input Configuration | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `keyword` | string | Yes | `cancer` | The search term to query across selected Japanese health data sources. Supports both English and Japanese keywords. | | `sources` | array | No | All sources | Which data sources to search. Options: `egov_health` (e-Gov Health Open Data), `mhlw` (MHLW Portal Links). | | `maxResults` | integer | No | 50 | Maximum number of results per source. Maximum allowed value is 200. | #### Example Input ```json { "keyword": "diabetes", "sources": ["egov_health", "mhlw"], "maxResults": 100 } ```` To search only the MHLW portal for mental health resources: ```json { "keyword": "精神保健", "sources": ["mhlw"], "maxResults": 50 } ``` ### Output Format Results are stored in the default Apify dataset. Each record contains fields returned by the source API along with a `source` identifier. You can access results via the Apify API, download as JSON/CSV/Excel, or connect them directly to your workflows using Apify integrations. #### Example Output Record ```json { "source": "egov_health", "title": "Cancer Registry Data 2022", "url": "https://example.go.jp/dataset/cancer-2022", "description": "National cancer registry statistics for fiscal year 2022." } ``` ### Use Cases - **Medical research**: Search for specific disease data, clinical trial registries, or epidemiological datasets from official Japanese government sources to support academic research on Japan health data. - **Healthcare market analysis**: Find MHLW data on medical facility counts, healthcare spending trends, pharmaceutical approvals, and workforce statistics relevant to the Japanese medical database landscape. - **Policy monitoring**: Track new publications and dataset releases from Japan's health ministries to stay current on regulatory changes and public health initiatives. - **Data journalism**: Access primary source data from Japanese government health portals for investigative reporting on healthcare outcomes, spending, and policy effectiveness. - **Public health surveillance**: Query infectious disease reports, vaccination coverage data, and health screening results from Japan's comprehensive public health monitoring systems. - **Cross-border health comparisons**: Retrieve standardized Japanese health statistics for international comparative studies and global health research projects. ### Environment Variables | Variable | Description | |----------|-------------| | `SIP_API_KEY` | Your SIP API key for authenticating requests to the data source API. Configure this in your Apify Actor environment settings. | ### Technical Details - Built with Python 3.13 and async HTTP via `httpx` for fast parallel queries - Uses the Apify SDK v2 for seamless integration with the Apify platform - All source queries execute concurrently to minimize total run time - Graceful error handling per source — a failure in one source does not block results from others - Supports both English and Japanese search keywords for maximum flexibility when querying Japanese medical database content ### Keywords Japan health data, Japanese medical database, MHLW data, e-Gov open data, Japan healthcare API, Japanese government health statistics, Japan public health data, medical data Japan, Japan health search, MHLW portal, Japan disease data, Japanese health datasets, Japan medical research data, healthcare data scraper Japan ### Use as MCP Tool (AI Agent Integration) This Actor works as an MCP tool — AI agents (Claude, GPT, Cursor) can discover and run it automatically. #### Quick setup (Claude Desktop / Cursor / VS Code) Add to your MCP config: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com", "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" } } } } ``` Then ask your AI: *"Search for pharmaceutical in Japanese health databases"* #### Direct API call ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("lentic_clockss/japan-health-data-search").call( run_input={"searchTerms": ["pharmaceutical"], "maxResultsPerSource": 50} ) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` ### Other Data API Actors - [US Healthcare Provider Data API](https://apify.com/lentic_clockss/us-healthcare-search) - [EU Health & Compliance Data API](https://apify.com/lentic_clockss/eu-health-compliance-search) - [Taiwan Government Data API](https://apify.com/lentic_clockss/taiwan-data-search) # Actor input Schema ## `keyword` (type: `string`): The keyword to search for across Japanese health and medical data sources. ## `sources` (type: `array`): Select which data sources to search. Leave empty to search all sources. ## `maxResults` (type: `integer`): Maximum number of results to return per source. ## Actor input object example ```json { "keyword": "cancer", "sources": [ "egov_health", "mhlw" ], "maxResults": 50 } ``` # Actor output Schema ## `records` (type: `string`): Contains the search results from the selected Japanese health and medical data sources. # 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 = { "keyword": "cancer" }; // Run the Actor and wait for it to finish const run = await client.actor("lentic_clockss/japan-health-data-search").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 = { "keyword": "cancer" } # Run the Actor and wait for it to finish run = client.actor("lentic_clockss/japan-health-data-search").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 '{ "keyword": "cancer" }' | apify call lentic_clockss/japan-health-data-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lentic_clockss/japan-health-data-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Japan Health & Medical Data API", "description": "Search Japanese health and medical datasets from e-Gov open data catalog and MHLW portal navigation links via SIP API.", "version": "0.1", "x-build-id": "cFYF3x4LlVWEP0Kp5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lentic_clockss~japan-health-data-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lentic_clockss-japan-health-data-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lentic_clockss~japan-health-data-search/runs": { "post": { "operationId": "runs-sync-lentic_clockss-japan-health-data-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lentic_clockss~japan-health-data-search/run-sync": { "post": { "operationId": "run-sync-lentic_clockss-japan-health-data-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "keyword" ], "properties": { "keyword": { "title": "Search Keyword", "type": "string", "description": "The keyword to search for across Japanese health and medical data sources." }, "sources": { "title": "Data Sources", "type": "array", "description": "Select which data sources to search. Leave empty to search all sources.", "items": { "type": "string", "enum": [ "egov_health", "mhlw" ], "enumTitles": [ "e-Gov Health & Medical Open Data Catalog", "MHLW Portal Navigation Links" ] }, "default": [ "egov_health", "mhlw" ] }, "maxResults": { "title": "Max Results", "maximum": 200, "type": "integer", "description": "Maximum number of results to return per source.", "default": 50 } } }, "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 } } } } } } } } } } ```