De-identification API¶

The deidentify() helper returns a typed DeidentificationResult with the redacted text, detected PIIEntity spans, result metadata, and a to_dict() representation for JSON-style workflows.

Entity Table Export¶

Use DeidentificationResult.to_dataframe() when you want to inspect the entities detected in a single de-identification result as a table:

from openmed import deidentify

result = deidentify("Patient John Doe called 555-1234", method="mask")
entities = result.to_dataframe()

The method imports pandas lazily, so importing openmed or openmed.core.pii does not import pandas. If pandas is not installed, calling to_dataframe() raises an actionable ImportError with the install command.

The returned DataFrame has one row per detected entity and always uses this column order:

Column	Description
`text`	Entity text span captured by the detector.
`label`	Detector label for the span.
`entity_type`	Normalized PII entity type stored on the result entity.
`start`	Character start offset in the original text.
`end`	Character end offset in the original text.
`confidence`	Detector confidence score.
`action`	De-identification policy action applied to the entity, when available.
`result_id`	Stable hash-derived identifier shared by every row from the result.

When no PII entities are present, to_dataframe() returns an empty DataFrame with the same columns.

India ABDM and ABHA identifiers¶

Enable the ABDM recognizer bundle for Indian clinical records to detect and replace ABHA numbers and addresses, Aadhaar numbers, PAN values, and contextual HPR/HFR registry identifiers:

from openmed import deidentify

result = deidentify(
    note,
    method="replace",
    lang="en",
    locale="en_IN",
    abdm=True,
)

The bundle also activates automatically for Hindi or Telugu, an India locale, or the india_dpdp_act policy profile. Pass abdm=False to opt out explicitly. It is inactive for other languages and locales by default. Recognized source labels (ABHA_NUMBER, ABHA_ADDRESS, AADHAAR, PAN, ABDM_HPR_ID, and ABDM_HFR_ID) normalize to ID_NUM and the DIRECT_IDENTIFIER policy class. Replacement mode produces synthetic values only; it does not call ABDM, verify an identifier, or store or resolve a real ABHA number. ABHA numbers are validated by their publicly documented 14-digit shape; the public NHA materials do not specify an offline checksum algorithm.

ABHA-linked record sharing requires the individual's informed consent. This mode de-identifies recognized identifiers, but it does not collect or record consent and does not decide whether a disclosure is permitted. Applications must enforce their own consent and disclosure workflow before sharing records. See the official ABDM FAQ for the ABHA identity and consent model.