# HRSA HPSA & MUA Shortage Designation Monitor API (`malonestar/hrsa-shortage-designation-monitor`) Actor Monitor HRSA HPSA & MUA/MUP shortage designations from the official ArcGIS feed. Normalize the 3 HPSA disciplines + MUA into one row per designation; filter by state, discipline, score, rural; delta newly designated vs withdrawn; roll up by county, district or state. - **URL**: https://apify.com/malonestar/hrsa-shortage-designation-monitor.md - **Developed by:** [Kyle Maloney](https://apify.com/malonestar) (community) - **Categories:** Lead generation, Developer tools, MCP servers - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.95 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## HRSA HPSA & MUA Shortage Designation Monitor Track federal **health-care shortage designations** — **HPSA** (Health Professional Shortage Areas) and **MUA/MUP** (Medically Underserved Areas/Populations) — straight from HRSA's official ArcGIS feed. This actor **normalizes** the three HPSA disciplines plus MUA into one clean row-per-designation, then lets you **filter, delta, and roll up** so you get an answer instead of a raw dump. Designations decide real money: **HPSA status = Medicare telehealth originating-site reimbursement eligibility**, HPSA score drives **NHSC loan-repayment** and **J-1 / Conrad 30 waiver** priority, and **MUA status gates FQHC / RHC / grant eligibility**. When a designation is **withdrawn**, that funding and eligibility can disappear — so the delta mode is a genuine recurring alert. ### Who it's for - **Telehealth companies** — confirm which sites/areas keep Medicare originating-site eligibility (HPSA), catch withdrawals early. - **Physician & locum recruiters / staffing** — target high-HPSA-score areas for NHSC loan-repayment and J-1 waiver candidates. - **Rural hospitals & clinics** — monitor their own and neighboring designations. - **FQHC / RHC grant writers** — MUA/MUP status is a hard eligibility gate; verify before applying. - **Health-equity researchers & GIS teams** — clean, normalized, geo-tagged shortage data by state / county / congressional district. ### Example input ```json { "designationType": "HPSA", "discipline": "Primary Care", "state": "Alabama", "minScore": 14, "ruralStatus": "rural", "maxResults": 5000 } ```` #### Delta example (newly withdrawn/designated since a date) ```json { "designationType": "all", "state": "Texas", "sinceDate": "2026-01-01" } ``` #### Rollup example (count + avg score by county) ```json { "designationType": "HPSA", "discipline": "all", "state": "California", "rollupBy": "county_fips" } ``` ### Output fields (one row per designation) | Field | Description | |---|---| | `source_id` | HRSA HPSA/MUA source id | | `designation_type` | `HPSA` or `MUA` | | `discipline` | Primary Care / Mental Health / Dental, or MUA type | | `name` | Designation / service-area name | | `status` | Designated / Withdrawn / Proposed for Withdrawal | | `score` | HPSA score (0-26) or MUA/IMU score (0-100) | | `designation_date` | First designated (YYYY-MM-DD) | | `last_update_date` | Last updated (YYYY-MM-DD) | | `withdrawal_date` | Withdrawn date, if any | | `rural_status` | Rural / Non-Rural | | `hpsa_type` | HPSA facility/area type | | `designation_population` | Population covered | | `pop_provider_ratio_goal` | Target population-to-provider ratio | | `state`, `state_fips`, `county_fips`, `congressional_district` | Geography | | `source_layer` | ArcGIS layer id | | `status_change` | Delta mode only: `newly_designated` / `newly_withdrawn` | In **rollup** mode each row is instead `rollup_by`, `group_key`, `designation_count`, `avg_score`. ### Use as an MCP tool This actor is callable by AI agents (Claude, Cursor, etc.) via **mcp.apify.com**. The input and output schemas are fully field-described, so an agent can chain it — e.g. "find newly withdrawn Primary Care HPSAs in Texas since Jan 2026" — and pass the normalized rows straight into a downstream tool. ### Coverage - **HPSA:** Primary Care, Mental Health, Dental (three feature layers). - **MUA/MUP:** Medically Underserved Areas & Populations. - Data is national; filter by state to keep runs fast. Source: HRSA GeoPortal (`gisportal.hrsa.gov`), keyless. WKID 4326. ### FAQ **How do I get an HPSA shortage designation dataset / API?** Set `designationType: "HPSA"` and a `state`; this actor returns normalized HPSA rows with scores and dates. **How do I find newly withdrawn HPSA or MUA designations?** Use delta mode: set `sinceDate` (e.g. `2026-01-01`). Rows come back with `status_change` = `newly_withdrawn` or `newly_designated`. **Which areas qualify for Medicare telehealth originating-site reimbursement?** Areas with an active HPSA designation; filter `status: "Designated"` and your state. **How do I find high-score HPSA areas for NHSC loan repayment or J-1 waivers?** Set `minScore` (e.g. 14+) — higher HPSA scores get funding/priority. **Is a place a Medically Underserved Area (MUA/MUP)?** Set `designationType: "MUA"` and your `state`; MUA status gates FQHC/RHC eligibility. **Can I count shortage areas by county or district?** Yes — set `rollupBy` to `county_fips`, `congressional_district`, `state`, or `discipline` for counts + average score. ### Notes - Billing is a single automatic result event (per dataset item). - Data is refreshed by HRSA; this actor always reads the live feed. # Actor input Schema ## `designationType` (type: `string`): Which HRSA shortage program to pull. HPSA = Health Professional Shortage Areas (point designations by discipline). MUA = Medically Underserved Areas/Populations (polygon designations). 'all' returns both. ## `discipline` (type: `string`): HPSA discipline to query (ignored for MUA). 'all' queries Primary Care, Mental Health, and Dental layers. ## `state` (type: `string`): Filter by full state name exactly as HRSA stores it, e.g. 'Alabama', 'California', 'Texas'. Leave blank for all states (large result set). ## `minScore` (type: `integer`): Only return designations with a shortage score at or above this value. HPSA scores run 0-26 (higher = greater need, drives NHSC loan repayment / J-1 waiver priority). MUA/IMU scores run 0-100. Use 0 for no threshold. ## `status` (type: `string`): Optional exact status filter, e.g. 'Designated', 'Withdrawn', 'Proposed for Withdrawal'. Leave blank for all statuses. ## `ruralStatus` (type: `string`): Filter by rural classification. 'any' returns all; 'rural' or 'non-rural' filter to that class. ## `sinceDate` (type: `string`): Delta mode. When set, only returns designations that were newly Designated or newly Withdrawn on/after this date (compared against last-update and withdrawal dates). Adds a status\_change field. A withdrawal = loss of Medicare originating-site / NHSC eligibility — a real recurring alert. Leave blank for a full snapshot. ## `rollupBy` (type: `string`): Optional aggregation. When set, output becomes one row per group with a designation count and average score instead of one row per designation. ## `maxResults` (type: `integer`): Maximum number of designation records to fetch/emit (before rollup). Paginates the ArcGIS layers in pages of 1000. ## Actor input object example ```json { "designationType": "HPSA", "discipline": "Primary Care", "state": "Alabama", "minScore": 0, "ruralStatus": "any", "rollupBy": "", "maxResults": 5000 } ``` # Actor output Schema ## `results` (type: `string`): The default dataset. # 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 = { "designationType": "HPSA", "discipline": "Primary Care", "state": "Alabama", "minScore": 0, "status": "", "ruralStatus": "any", "sinceDate": "", "rollupBy": "", "maxResults": 5000 }; // Run the Actor and wait for it to finish const run = await client.actor("malonestar/hrsa-shortage-designation-monitor").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 = { "designationType": "HPSA", "discipline": "Primary Care", "state": "Alabama", "minScore": 0, "status": "", "ruralStatus": "any", "sinceDate": "", "rollupBy": "", "maxResults": 5000, } # Run the Actor and wait for it to finish run = client.actor("malonestar/hrsa-shortage-designation-monitor").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 '{ "designationType": "HPSA", "discipline": "Primary Care", "state": "Alabama", "minScore": 0, "status": "", "ruralStatus": "any", "sinceDate": "", "rollupBy": "", "maxResults": 5000 }' | apify call malonestar/hrsa-shortage-designation-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=malonestar/hrsa-shortage-designation-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "HRSA HPSA & MUA Shortage Designation Monitor API", "description": "Monitor HRSA HPSA & MUA/MUP shortage designations from the official ArcGIS feed. 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HPSA = Health Professional Shortage Areas (point designations by discipline). MUA = Medically Underserved Areas/Populations (polygon designations). 'all' returns both.", "default": "HPSA" }, "discipline": { "title": "HPSA discipline", "enum": [ "all", "Primary Care", "Mental Health", "Dental" ], "type": "string", "description": "HPSA discipline to query (ignored for MUA). 'all' queries Primary Care, Mental Health, and Dental layers.", "default": "Primary Care" }, "state": { "title": "State (full name)", "type": "string", "description": "Filter by full state name exactly as HRSA stores it, e.g. 'Alabama', 'California', 'Texas'. Leave blank for all states (large result set)." }, "minScore": { "title": "Minimum shortage score", "minimum": 0, "maximum": 100, "type": "integer", "description": "Only return designations with a shortage score at or above this value. HPSA scores run 0-26 (higher = greater need, drives NHSC loan repayment / J-1 waiver priority). MUA/IMU scores run 0-100. Use 0 for no threshold.", "default": 0 }, "status": { "title": "Designation status", "type": "string", "description": "Optional exact status filter, e.g. 'Designated', 'Withdrawn', 'Proposed for Withdrawal'. Leave blank for all statuses." }, "ruralStatus": { "title": "Rural status", "enum": [ "any", "rural", "non-rural" ], "type": "string", "description": "Filter by rural classification. 'any' returns all; 'rural' or 'non-rural' filter to that class.", "default": "any" }, "sinceDate": { "title": "Delta since date (YYYY-MM-DD)", "type": "string", "description": "Delta mode. When set, only returns designations that were newly Designated or newly Withdrawn on/after this date (compared against last-update and withdrawal dates). Adds a status_change field. A withdrawal = loss of Medicare originating-site / NHSC eligibility — a real recurring alert. Leave blank for a full snapshot." }, "rollupBy": { "title": "Geo rollup", "enum": [ "", "state", "county_fips", "congressional_district", "discipline" ], "type": "string", "description": "Optional aggregation. When set, output becomes one row per group with a designation count and average score instead of one row per designation.", "default": "" }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum number of designation records to fetch/emit (before rollup). Paginates the ArcGIS layers in pages of 1000.", "default": 5000 } } }, "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 } } } } } } } } } } ```