# Ny Medical Conduct Board Actions Scraper (`zerobreak/ny-medical-conduct-board-actions-scraper`) Actor

NY Medical Conduct Board Actions Scraper is a Python tool designed to extract physician disciplinary actions, license numbers, hearing decisions, charges, and board orders from the NY State Department of Health. It exports structured medical compliance datasets into clean CSV or JSON format

- **URL**: https://apify.com/zerobreak/ny-medical-conduct-board-actions-scraper.md
- **Developed by:** [ZeroBreak](https://apify.com/zerobreak) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

### NY Medical Conduct Board Actions Scraper — New York Physician Disciplinary Records

![NY Medical Conduct Board Actions Scraper cover](https://images.bigibyte.com/cdn-cgi/image/width=1260,height=540,fit=cover,format=webp/apify-actors-covers/ny-medical-conduct-board-actions-scraper-cover.png)

Collect publicly available physician disciplinary actions from the New York State Department of Health. Retrieve medical board records, filter results by license information or other criteria, and explore dataset metadata. Export structured results as JSON, CSV, or Excel without requiring a login.

### Overview

NY Medical Conduct Board Actions Scraper helps researchers, compliance teams, and developers collect and organize public records from New York's Professional Medical Conduct Board Actions dataset.

Choose between collecting all available rows, filtering records with search conditions, or retrieving dataset metadata. The collected records can include physician names, license details, disciplinary action information, and relevant dates.

### Features

- **Full dataset collection:** Retrieve records from the public medical conduct board dataset.
- **Filtered collection:** Narrow results using conditions and full-text searches.
- **Dataset metadata:** Retrieve available column names, data types, and descriptions.
- **Physician information:** Collect names, license numbers, and license types.
- **Disciplinary records:** Retrieve action descriptions, notes, and effective dates.
- **Result limits:** Control the maximum number of records collected.
- **Structured exports:** Download results as JSON, CSV, Excel, and other supported formats.
- **Scheduled collection:** Refresh records periodically to review updated information.

### Collection Modes

**All rows mode**

Collect records from the public Professional Medical Conduct Board Actions dataset, with pagination and a configurable result limit.

**Filtered rows mode**

Narrow the collection using filtering conditions or full-text search. This is useful for finding records by license type, effective date, physician name, or other available fields.

**Dataset metadata mode**

Retrieve information about the dataset's available columns, including their names, data types, and descriptions.

### Use Cases

- **Compliance research:** Review publicly available medical disciplinary records.
- **License research:** Find records associated with specific license types or numbers.
- **Physician research:** Search public records by physician name.
- **Disciplinary monitoring:** Review newly published or updated board actions.
- **Data analysis:** Analyze disciplinary records using spreadsheets or data tools.
- **Dataset integration:** Import structured records into research and reporting workflows.

### Input Parameters

| Parameter | Type | Description |
|---|---|---|
| `mode` | String | Collection mode: `rows`, `filtered`, or `metadata`. |
| `maxItems` | Integer | Maximum number of records to collect. |
| `orderBy` | String | Field or ordering expression used to sort collected rows. |
| `where` | String | Optional filtering condition used in filtered mode. |
| `search` | String | Optional full-text search term, if supported by the actor input. |
| `requestDelaySecs` | Number | Delay between requests in seconds. |

### Example Input

**All rows mode**

```json id="3m8xqv"
{
  "mode": "rows",
  "maxItems": 50,
  "orderBy": ":id",
  "requestDelaySecs": 1
}
```

**Filtered rows mode**

```json id="7k2pwb"
{
  "mode": "filtered",
  "where": "licensetype='MD'",
  "maxItems": 25,
  "requestDelaySecs": 1
}
```

### What Data Does This Actor Extract?

**Disciplinary records**

| Field | Description |
|---|---|
| `last_name` | Physician's last name. |
| `first_name` | Physician's first name. |
| `address` | Address associated with the record. |
| `licensenum` | Professional license number. |
| `licensetype` | Professional license type, such as MD. |
| `yearofbirth` | Year of birth when available. |
| `effectivedate` | Effective date of the disciplinary action. |
| `webaction` | Description of the disciplinary action. |
| `webnotes` | Additional notes about the board action. |
| `dateupdated` | Date the record was last updated. |
| `scraped_at` | Date and time the record was collected. |

**Dataset metadata**

Metadata mode returns available dataset column information, including column names, data types, and descriptions.

### Example Output

**Disciplinary record**

```json id="9q5vnc"
{
  "last_name": "Seodat",
  "first_name": "Vishnudat",
  "address": "C/O Joseph P. Walsh, Esq., Barnes & Barnes, P.C., Melville, New York 11747",
  "licensenum": "174744",
  "licensetype": "MD",
  "yearofbirth": "1949",
  "effectivedate": "2026-09-30T00:00:00.000",
  "webaction": "License revocation. Both parties may request a review of the Hearing Committee's Determination and Order.",
  "webnotes": "The Hearing Committee sustained the charges finding the physician committed professional misconduct...",
  "dateupdated": "2026-09-28T00:00:00.000",
  "scraped_at": "2026-10-26T00:00:00+00:00"
}
```

### Working with Your Dataset

After the run finishes, open the dataset in Apify Console to review your collected records.

You can:

- Export records as JSON, CSV, or Excel.
- Filter records by physician name or license type.
- Sort disciplinary actions by effective date.
- Review action descriptions and additional notes.
- Analyze records for research and compliance workflows.
- Import collected data into spreadsheets and reporting tools.

### FAQ

**Who is this actor for?**

It is designed for compliance teams, researchers, analysts, and developers who need structured public medical disciplinary records.

**What collection modes are available?**

You can collect all rows, filtered records, or dataset metadata.

**How do filters work?**

Use filtered rows mode with a filtering condition and/or full-text search to narrow records by available fields.

**Can I collect a specific license type?**

Yes. You can use a filtering condition such as `licensetype='MD'` to narrow the results.

**What can I export?**

You can export JSON, CSV, Excel, and other supported Apify dataset formats.

**Can I run it on a schedule?**

Yes. You can configure an Apify schedule to refresh your collection at your preferred intervals.

**What happens if some information is unavailable?**

Some fields may be empty or unavailable depending on the original public record.

### Disclaimer

This actor is an independent tool and is not affiliated with, endorsed by, sponsored by, or officially associated with the New York State Department of Health or its owners. It collects publicly available records. Users are responsible for ensuring that their collection and use of the data comply with applicable laws and relevant terms.

### Is Web Scraping Legal?

Collecting information that is already public is generally legal. There is no single law that bans all forms of web scraping. The limits are the usual ones: do not break into accounts, do not take private or confidential data, and be careful with personal data and copyrighted works. A site's terms can also restrict how you access it. Facts such as a public name, price, or rating are not the same thing as republishing someone's article or photo.

This actor collects information from public pages. It does not log in and it does not bypass access controls.

For a longer explanation, see Apify's article [Is web scraping legal?](https://blog.apify.com/is-web-scraping-legal/).

# Actor input Schema

## `mode` (type: `string`):

What to scrape.

## `where` (type: `string`):

SoQL $where clause, e.g. effectivedate > '2024-01-01'

## `q` (type: `string`):

Full-text search ($q) across text columns

## `orderBy` (type: `string`):

SoQL $order (stable paging needs a unique order)

## `maxItems` (type: `integer`):

Stop after this many successful rows. Hard max is 1000.

## `requestDelaySecs` (type: `number`):

Seconds to wait between requests.

## `userAgent` (type: `string`):

User-Agent header sent with each request.

## `timeoutSecs` (type: `integer`):

Overall run budget in seconds.

## `requestTimeoutSecs` (type: `integer`):

Per-request timeout in seconds.

## `proxyConfiguration` (type: `object`):

Optional proxy. Leave off unless you need it.

## Actor input object example

```json
{
  "mode": "rows",
  "where": "",
  "q": "",
  "orderBy": ":id",
  "maxItems": 100,
  "requestDelaySecs": 1,
  "userAgent": "ActorResearch/1.0",
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `overview` (type: `string`):

Dataset rows in the overview table.

## `dataset` (type: `string`):

Full dataset for this run.

## `items` (type: `string`):

Dataset items as JSON.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("zerobreak/ny-medical-conduct-board-actions-scraper").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("zerobreak/ny-medical-conduct-board-actions-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call zerobreak/ny-medical-conduct-board-actions-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,zerobreak/ny-medical-conduct-board-actions-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/qt1lvfdFE8QrXMEV1/builds/fJIteShSEMYdQhVDZ/openapi.json