reviewing-reidentification-risk SKILL.md skillA
reviewing-reidentification-risk from maziyarpanahi/openmed is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add maziyarpanahi/openmed/reviewing-reidentification-risk@v1.0Pins v1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- maziyarpanahi/openmed
- Path
skills/reviewing-reidentification-risk/SKILL.md- Versions recorded
- 1
- Latest version
- v1.0, committed Jul 20, 2026
- Size
- 7,667 bytes
- Repository stars
- 5,784
- License
- Apache-2.0
Run expert-determination-style quasi-identifier risk scoring (k-anonymity, l-diversity) plus OpenMed's empirical re-identification attack on a de-identified dataset, then document residual risk in a defensible memo. Use when the user needs HIPAA Expert Determination (45 CFR 164.514(b)(1)) support, asks whether a dataset is safe to release, worries about singling-out via age/ZIP/dates, or wants a statistical "very small risk" determination. Covers identifying quasi-identifiers, computing…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Reviewing re-identification risk Removing direct identifiers is not enough. A record stripped of name, SSN, and MRN can still be **singled out** by a combination of *quasi-identifiers* — age, ZIP/region, admission date, sex, rare diagnosis. The HIPAA Expert Determination pathway (45 CFR 164.514(b)(1)) requires a qualified person to apply statistical methods and document that the risk of re-identification is **"very small."** This skill produces that evidence: quasi-identifier risk metrics (k-anonymity, l-diversity) plus OpenMed's empirical re-identification attack, written up as a residual-risk memo. ## When to use - After direct-identifier removal passes `auditing-deid-leakage` (no leaks) and you must decide whether the dataset is releasable. - The user invokes Expert Determination, asks for a re-identification risk score, k-anonymity, l-diversity, or a "very small risk" determination memo. - You need an adversarial linkage attack — modeling an attacker with auxiliary data — not just a structural metric. ## Quick start ```python from openmed.eval.attacks.reid import run_reid_attack, run_reid_benchmark …
Read the whole file at its exact version.
How to install
mdr add maziyarpanahi/openmed/reviewing-reidentification-risk@sha256:52bb16dde423adefThe line at the top of this page pins the label v1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_3xsnvzqpn5tp4cnm)
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Versions
The registry has recorded 1 version of this file, committed on Jul 20, 2026.
Audit of the latest version
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Source
maziyarpanahi/openmed · 5,784 stars · license Apache-2.0 · pushed 2026-11-07 · branch master
API
GET https://markdownregistry.com/api/v1/artifacts/art_3xsnvzqpn5tp4cnm GET https://markdownregistry.com/api/v1/resolve?ref=maziyarpanahi/openmed/reviewing-reidentification-risk GET https://markdownregistry.com/api/v1/blob/52bb16dde423adeff6ad232ced4ad8732754ccf8d9ae6c7e746160f0a602d0d1
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