# CMS Open Payments Scraper - Physician Payments (`dataio/cms-open-payments-physicians`) Actor

Scrape CMS Open Payments: which company paid which US physician, how much and in how many transactions. Filter by company, physician, NPI or recipient type, sorted by amount, which the source does not do. Sunshine Act data for compliance, sales and research.

- **URL**: https://apify.com/dataio/cms-open-payments-physicians.md
- **Developed by:** [Tom Awake](https://apify.com/dataio) (community)
- **Categories:** Lead generation, MCP servers
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 payment relationships

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

### What does CMS Open Payments Scraper do?

Who paid which US physician, how much, and across how many transactions —
from **CMS Open Payments**, the federal register of industry payments to
doctors and teaching hospitals.

**No login. No API key. No proxies.**

### Relationships, not 16 million receipts

CMS publishes every individual payment: 16 million rows for 2025 alone, one
per dinner, per consulting fee, per royalty cheque. Nobody wants that.

What a compliance officer or a medtech sales lead wants is the
**relationship**: *Dr Sethi received $154,631.57 from Medtronic across 151
payments.* This Actor serves exactly that — one row per physician-company
pair, with the total and the transaction count.

| Recipient | Paid by | Total | Payments |
|---|---|---|---|
| UT MD ANDERSON CANCER CENTER | Pfizer Inc. | $22,374,153.36 | 469 |
| THE CHILDREN'S HOSPITAL OF PHILADELPHIA | Pfizer Inc. | $10,103,322.25 | 46 |
| NISHANT SETHI | Medtronic, Inc. | $154,631.57 | 151 |

### The bug it fixes, and why it matters

**CMS sorts amounts as text, not as numbers.**

Ask the source for the highest payments and it stops at **$99,999.96** — not
because that is the maximum, but because `"171059.91"` sorts below
`"99999.96"` when the first character decides. Measured on 13 September
2026: **42,417 relationships exceed six figures**, and every one of them is
invisible to the source's own ranking.

The $22.4 million MD Anderson row above is precisely what that bug hides.

The same flaw breaks numeric filters: asking the source for totals *above
$100,000* returns **4,931,711 rows out of 4,953,301**. So this Actor sorts
and thresholds numerically, on its own side, and never sends a numeric
comparison to the API.

If you need the largest payments — and for compliance screening that is the
entire point — this distinction is the product.

### Output

| Field | Example |
|---|---|
| `recipientName` | NISHANT SETHI |
| `firstName`, `lastName` | NISHANT, SETHI |
| `npi` | 1003024811 — joins to the NPI Registry |
| `recipientType` | Covered Recipient Physician |
| `teachingHospital` | UT MD ANDERSON CANCER CENTER |
| `payerName`, `payerId` | Medtronic, Inc. |
| `paymentType` | General |
| `totalAmountUsd` | 154631.57 |
| `transactionCount` | 151 |
| `averagePaymentUsd` | 1024.05 |
| `programYear`, `openPaymentsUrl` | 2025, link to the CMS record |

`averagePaymentUsd` separates cases a total alone confuses: $40,000 in one
consulting fee and $40,000 across 300 meals are very different relationships.

### Input

```json
{
  "payerName": "Medtronic",
  "programYear": "2025",
  "maxItems": 1000
}
```

| Field | Default | Notes |
|---|---|---|
| `payerName` | `Medtronic` | Prefix match — the highest-value filter |
| `programYear` | `2025` | 2019–2025, published ~6 months in arrears |
| `maxItems` | `1000` | One row per relationship |
| `minTotalUsd` | — | Applied numerically, after fetching |
| `lastName`, `npi` | — | One physician |
| `recipientType` | `all` | Physicians, practitioners, teaching hospitals |

### Use cases

- **Competitive intelligence** — every physician a competitor pays is a
  physician using their products. Medtronic alone has **79,609**
  relationships in 2025.
- **Compliance and conflict-of-interest screening** — what did our
  clinicians receive, from whom, and how much.
- **Medical affairs and KOL mapping** — who the industry actually funds,
  ranked by real amounts.
- **Due diligence and journalism** — the payment trail behind a prescriber
  or an institution.
- **Enrichment** — `npi` joins straight to the NPI Registry for specialty,
  address and practice locations.

### Limits, honestly

- **Wide queries are slow.** Filtering 5 million relationships takes roughly
  a minute per page at the source. A large manufacturer has tens of
  thousands of rows; set `maxItems` deliberately.
- **`maxItems` truncates before sorting.** Rows are fetched in the source's
  own order, then sorted numerically. Asking for 1,000 out of 79,609 gives
  the top of *those 1,000*, not the national top 1,000. Narrow the filter, or
  raise the limit, when you need a true ranking.
- Teaching hospitals carry no NPI in this dataset — the column is empty for
  them by design, not by omission.
- CMS restates data: figures for a year can change after publication.
- A payment is a payment. It is not evidence of wrongdoing, and this data
  says nothing about whether any relationship was improper.
- Requests are paced out of courtesy to a free public service.
- Not affiliated with CMS.

### How much does it cost?

You pay per payment relationship returned: **$0.003 each**, that is $3.00 per 1,000. There is no start fee, and subscription plans pay less per payment relationship.

The example input below asks for up to 500 payment relationships, so it costs **$1.50 at most**.

If a run reaches the spending limit you set, the output stops at that limit and never goes past it. You are never charged for rows that were not delivered.

### Use CMS Open Payments Scraper as an API

Call it from your own code with the Apify client, here in Python:

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("DataIO/cms-open-payments-physicians").call(run_input={
    'payerName': 'Medtronic',
    'programYear': '2025',
    'maxItems': 500,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

It also works from JavaScript, Make, Zapier, n8n, and from AI agents through the Apify MCP server.

### Other actors you might like

- [FDA 510(k) Scraper](https://apify.com/DataIO/openfda-510k-device-clearances): Device Clearances Data
- [FDA Recalls Scraper](https://apify.com/DataIO/openfda-recalls-enforcement): openFDA Enforcement
- [NPI Registry Scraper](https://apify.com/DataIO/nppes-npi-provider-registry): US Healthcare Providers

### FAQ

#### Is it legal to use this data?

The actor reads public data from its official source, without logging in and without bypassing any access control. What you do with the data, for example contacting people listed in it, is your responsibility under the laws that apply to you, such as GDPR in Europe.

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

Yes. Create a schedule in Apify Console, daily or weekly for example, and each run delivers a fresh dataset, which you can send by email, webhook or integration.

#### Can AI agents use it?

Yes. It is available through the Apify MCP server, and every input field is described in its input schema, so an agent can call it directly.

# Actor input Schema

## `payerName` (type: `string`):

Manufacturer or GPO name, for example Medtronic, Pfizer, Stryker. Matched as a prefix, so "Medtronic" catches every Medtronic entity. This is the highest-value filter: it lists every physician a company pays.

## `programYear` (type: `string`):

CMS publishes each year with roughly six months' delay.

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

One row per physician-company pair. A large manufacturer has tens of thousands, and a wide filter takes about a minute per page, so raise this deliberately.

## `minTotalUsd` (type: `integer`):

Applied after fetching, on purpose: the source compares amounts as text, so asking it for "over 100000" returns almost every row. See the README.

## `lastName` (type: `string`):

Exact surname, case-insensitive.

## `npi` (type: `string`):

Ten-digit National Provider Identifier for one physician. Joins directly to the NPI Registry.

## `recipientType` (type: `string`):

Teaching hospitals receive far larger sums than individual physicians.

## Actor input object example

```json
{
  "payerName": "Medtronic",
  "programYear": "2025",
  "maxItems": 1000,
  "recipientType": "all"
}
```

# Actor output Schema

## `results` (type: `string`):

Every row produced by the run, in 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 = {
    "payerName": "Medtronic",
    "maxItems": 1000
};

// Run the Actor and wait for it to finish
const run = await client.actor("dataio/cms-open-payments-physicians").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 = {
    "payerName": "Medtronic",
    "maxItems": 1000,
}

# Run the Actor and wait for it to finish
run = client.actor("dataio/cms-open-payments-physicians").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 '{
  "payerName": "Medtronic",
  "maxItems": 1000
}' |
apify call dataio/cms-open-payments-physicians --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,dataio/cms-open-payments-physicians"
        }
    }
}
```

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/CHLK0VwOqWcpaVMsn/builds/IIGvAANjnG9Dt2lXk/openapi.json