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Azure Health Data Services de-identification service client library for Python - version 1.1.0b1

This package contains a client library for the de-identification service in Azure Health Data Services which enables users to tag, redact, or surrogate health data containing Protected Health Information (PHI). For more on service functionality and important usage considerations, see the de-identification service overview.

This library supports API versions 2025-07-15-preview and earlier.

Use the client library for the de-identification service to:

  • Discover PHI in unstructured text
  • Replace PHI in unstructured text with placeholder values
  • Replace PHI in unstructured text with realistic surrogate values
  • Manage asynchronous jobs to de-identify documents in Azure Storage

Source code | Package (PyPI) | API reference documentation | Product documentation | Samples

Getting started

Prequisites

Install the package

python -m pip install azure-health-deidentification

Authentication

To authenticate with the de-identification service, install azure-identity:

python -m pip install azure.identity

You can use DefaultAzureCredential to automatically find the best credential to use at runtime.

You will need a service URL to instantiate a client object. You can find the service URL for a particular resource in the Azure portal, or using the Azure CLI. Here's an example of setting an environment variable in Bash using Azure CLI:

# Get the service URL for the resource
export HEALTHDATAAISERVICES_DEID_SERVICE_ENDPOINT=$(az deidservice show --name "<resource-name>" --resource-group "<resource-group-name>" --query "properties.serviceUrl")

Optionally, save the service URL as an environment variable named HEALTHDATAAISERVICES_DEID_SERVICE_ENDPOINT for the sample client initialization code.

Create a client with the endpoint and credential:

from azure.health.deidentification import DeidentificationClient
from azure.identity import DefaultAzureCredential
import os


endpoint = os.environ["HEALTHDATAAISERVICES_DEID_SERVICE_ENDPOINT"]
credential = DefaultAzureCredential()
client = DeidentificationClient(endpoint, credential)

Key concepts

De-identification operations:

Given an input text, the de-identification service can perform four main operations:

  • Tag returns the category and location within the text of detected PHI entities.
  • Redact returns output text where detected PHI entities are replaced with placeholder text. For example, John would be replaced with [name].
  • Surrogate returns output text where detected PHI entities are replaced with realistic replacement values. For example, My name is John Smith could become My name is Tom Jones.
  • SurrogateOnly returns output text where user-defined PHI entities are replaced with realistic replacement values.

String Encoding

When using the Tag operation, the service will return the locations of PHI entities in the input text. These locations will be represented as offsets and lengths, each of which is a StringIndex containing three properties corresponding to three different text encodings. Python applications should use the code_point property.

For more on text encoding, see Character encoding in .NET.

Available endpoints

There are two ways to interact with the de-identification service. You can send text directly, or you can create jobs to de-identify documents in Azure Storage.

You can de-identify text directly using the DeidentificationClient:

from azure.health.deidentification import DeidentificationClient
from azure.health.deidentification.models import (
    DeidentificationContent,
    DeidentificationOperationType,
    DeidentificationResult,
)
from azure.identity import DefaultAzureCredential
import os

endpoint = os.environ["HEALTHDATAAISERVICES_DEID_SERVICE_ENDPOINT"]
credential = DefaultAzureCredential()
client = DeidentificationClient(endpoint, credential)

body = DeidentificationContent(
    input_text="Hello, my name is John Smith.", operation_type=DeidentificationOperationType.SURROGATE
)
result: DeidentificationResult = client.deidentify_text(body)
print(f'\nOriginal Text:     "{body.input_text}"')
print(f'Surrogated Text:   "{result.output_text}"')  # Surrogated output: Hello, my name is <synthetic name>.

To de-identify documents in Azure Storage, you'll need a storage account with a container to which the de-identification service has been granted an appropriate role. See Tutorial: Configure Azure Storage to de-identify documents for prerequisites and configuration options. You can upload the files in the test data folder as blobs, like: https://<storageaccount>.blob.core.windows.net/<container>/example_patient_1/doctor_dictation.txt.

You can create jobs to de-identify documents in the source Azure Storage account and container with an optional input prefix. If there's no input prefix, all blobs in the container will be de-identified. Azure Storage blobs can use / in the blob name to emulate a folder or directory layout. For more on blob naming, see Naming and Referencing Containers, Blobs, and Metadata. The files you've uploaded can be de-identified by providing example_patient_1 as the input prefix:

<container>/
├── example_patient_1/
       └──doctor_dictation.txt
       └──row-2-data.txt
       └──visit-summary.txt

Your target Azure Storage account and container where documents will be written can be the same as the source, or a different account or container. In the examples below, the source and target account and container are the same. You can specify an output prefix to indicate where the job's output documents should be written (defaulting to _output). Each document processed by the job will have the same relative blob name with the input prefix replaced by the output prefix:

<container>/
├── example_patient_1/
       └──doctor_dictation.txt
       └──row-2-data.txt
       └──visit-summary.txt
├── _output/
       └──doctor_dictation.txt
       └──row-2-data.txt
       └──visit-summary.txt

Set the following environment variables, updating the storage account and container with real values:

export HEALTHDATAAISERVICES_STORAGE_ACCOUNT_LOCATION="https://<storageaccount>.blob.core.windows.net/<container>"
export INPUT_PREFIX="example_patient_1"
export OUTPUT_PREFIX="_output"

The client exposes a begin_deidentify_documents method that returns a LROPoller instance. You can get the result of the operation by calling result(), optionally passing in a timeout value in seconds:

from azure.health.deidentification import DeidentificationClient
from azure.health.deidentification.models import (
    DeidentificationJob,
    DeidentificationOperationType,
    SourceStorageLocation,
    TargetStorageLocation,
)
from azure.identity import DefaultAzureCredential
import os
import uuid

endpoint = os.environ["HEALTHDATAAISERVICES_DEID_SERVICE_ENDPOINT"]
storage_location = os.environ["HEALTHDATAAISERVICES_STORAGE_ACCOUNT_LOCATION"]
inputPrefix = os.environ.get("INPUT_PREFIX", "example_patient_1")
outputPrefix = os.environ.get("OUTPUT_PREFIX", "_output")

credential = DefaultAzureCredential()

client = DeidentificationClient(endpoint, credential)

jobname = f"sample-job-{uuid.uuid4().hex[:8]}"

job = DeidentificationJob(
    operation_type=DeidentificationOperationType.SURROGATE,
    source_location=SourceStorageLocation(
        location=storage_location,
        prefix=inputPrefix,
    ),
    target_location=TargetStorageLocation(location=storage_location, prefix=outputPrefix, overwrite=True),
)

finished_job: DeidentificationJob = client.begin_deidentify_documents(jobname, job).result(timeout=120)

print(f"Job Name:   {finished_job.job_name}")
print(f"Job Status: {finished_job.status}")
print(f"File Count: {finished_job.summary.total_count if finished_job.summary is not None else 0}")

Examples

The following sections provide code samples covering some of the most common client use cases, including:

See the samples for code files illustrating common patterns, including creating and managing jobs to de-identify documents in Azure Storage.

Discover PHI in unstructured text

When you specify the TAG operation, the service will return information about the PHI entities it detects. You can use this information to customize your de-identification workflow:

from azure.health.deidentification import DeidentificationClient
from azure.health.deidentification.models import (
    DeidentificationContent,
    DeidentificationOperationType,
    DeidentificationResult,
)
from azure.identity import DefaultAzureCredential
import os

endpoint = os.environ["HEALTHDATAAISERVICES_DEID_SERVICE_ENDPOINT"]
credential = DefaultAzureCredential()
client = DeidentificationClient(endpoint, credential)

body = DeidentificationContent(
    input_text="Hello, I'm Dr. John Smith.", operation_type=DeidentificationOperationType.TAG
)
result: DeidentificationResult = client.deidentify_text(body)
print(f'\nOriginal Text:    "{body.input_text}"')

if result.tagger_result and result.tagger_result.entities:
    print(f"Tagged Entities:")
    for entity in result.tagger_result.entities:
        print(
            f'\tEntity Text: "{entity.text}", Entity Category: "{entity.category}", Offset: "{entity.offset.code_point}", Length: "{entity.length.code_point}"'
        )
else:
    print("\tNo tagged entities found.")

Replace PHI in unstructured text with placeholder values

When you specify the REDACT operation, the service will replace the PHI entities it detects with placeholder values. You can learn more about redaction customization.

from azure.health.deidentification import DeidentificationClient
from azure.health.deidentification.models import (
    DeidentificationContent,
    DeidentificationOperationType,
    DeidentificationResult,
)
from azure.identity import DefaultAzureCredential
import os

endpoint = os.environ["HEALTHDATAAISERVICES_DEID_SERVICE_ENDPOINT"]
credential = DefaultAzureCredential()
client = DeidentificationClient(endpoint, credential)

body = DeidentificationContent(
    input_text="It's great to work at Contoso.", operation_type=DeidentificationOperationType.REDACT
)
result: DeidentificationResult = client.deidentify_text(body)
print(f'\nOriginal Text:   "{body.input_text}"')
print(f'Redacted Text:   "{result.output_text}"')  # Redacted output: "It's great to work at [organization]."

Replace PHI in unstructured text with realistic surrogate values

The default operation is the SURROGATE operation. Using this operation, the service will replace the PHI entities it detects with realistic surrogate values:

from azure.health.deidentification import DeidentificationClient
from azure.health.deidentification.models import (
    DeidentificationContent,
    DeidentificationOperationType,
    DeidentificationResult,
)
from azure.identity import DefaultAzureCredential
import os

endpoint = os.environ["HEALTHDATAAISERVICES_DEID_SERVICE_ENDPOINT"]
credential = DefaultAzureCredential()
client = DeidentificationClient(endpoint, credential)

body = DeidentificationContent(
    input_text="Hello, my name is John Smith.", operation_type=DeidentificationOperationType.SURROGATE
)
result: DeidentificationResult = client.deidentify_text(body)
print(f'\nOriginal Text:     "{body.input_text}"')
print(f'Surrogated Text:   "{result.output_text}"')  # Surrogated output: Hello, my name is <synthetic name>.

Replace only specific PHI entities with surrogate values

The SURROGATE_ONLY operation returns output text where user-defined PHI entities are replaced with realistic replacement values.

from azure.health.deidentification import DeidentificationClient
from azure.health.deidentification.models import (
    DeidentificationContent,
    DeidentificationCustomizationOptions,
    DeidentificationOperationType,
    DeidentificationResult,
    PhiCategory,
    SimplePhiEntity,
    TaggedPhiEntities,
    TextEncodingType,
)
from azure.identity import DefaultAzureCredential
import os

endpoint = os.environ["HEALTHDATAAISERVICES_DEID_SERVICE_ENDPOINT"]
credential = DefaultAzureCredential()
client = DeidentificationClient(endpoint, credential)

# Define the entities to be surrogated - targeting "John Smith" at position 18-28
tagged_entities = TaggedPhiEntities(
    encoding=TextEncodingType.CODE_POINT,
    entities=[SimplePhiEntity(category=PhiCategory.PATIENT, offset=18, length=10)],
)

# Use SurrogateOnly operation with input locale specification
body = DeidentificationContent(
    input_text="Hello, my name is John Smith.",
    operation_type=DeidentificationOperationType.SURROGATE_ONLY,
    tagged_entities=tagged_entities,
    customizations=DeidentificationCustomizationOptions(
        input_locale="en-US"  # Specify input text locale for better PHI detection
    ),
)

result: DeidentificationResult = client.deidentify_text(body)
print(f'\nOriginal Text:        "{body.input_text}"')
print(f'Surrogate Only Text:  "{result.output_text}"')  # Surrogated output: Hello, my name is <synthetic name>.

Troubleshooting

The DeidentificationClient raises various AzureError exceptions. For example, if you provide an invalid service URL, an ServiceRequestError would be raised with a message indicating the failure cause. In the following code snippet, the error is handled and displayed:

from azure.core.exceptions import AzureError
from azure.health.deidentification.models import (
    DeidentificationContent,
)


error_client = DeidentificationClient("https://contoso.deid.azure.com", credential)
body = DeidentificationContent(input_text="Hello, I'm Dr. John Smith.")

try:
    error_client.deidentify_text(body)
except AzureError as e:
    print("\nError: " + e.message)

If you encounter an error indicating that the service is unable to access source or target storage in a de-identification job:

Next steps

Find a bug, or have feedback? Raise an issue with the Health Deidentification label.

Troubleshooting

  • Unable to Access Source or Target Storage
    • Ensure you create your deid service with a system assigned managed identity
    • Ensure your storage account has given permissions to that managed identity

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information, see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.