Shifting clinical dates

HIPAA Safe Harbor forbids keeping dates more specific than the year. But naively deleting dates destroys the temporal structure research depends on, time to event, length of stay, intervals between visits. Date shifting is the compromise: move every date by a single random offset so the absolute dates become meaningless while the intervals between them are preserved exactly. OpenMed does this on-device with deidentify(method="shift_dates", ...).

When to use this skill

Use it when downstream analysis needs temporal relationships (survival curves, sepsis-to-antibiotic time, readmission gaps) but the calendar dates must be de-identified. If you can throw dates away entirely, plain method="mask" is simpler, reach for shifting only when intervals matter.

Quick start

import openmed

note = (
    "Admitted 2024-03-02, started antibiotics 2024-03-04, discharged 2024-03-09. "
    "Follow-up scheduled 2024-04-02."
)

# Shift every date by the SAME offset -> intervals preserved, dates obscured.
result = openmed.deidentify(
    note,
    method="shift_dates",
    consistent=True,        # one stable offset for this run
    seed=20240519,          # reproducible per-patient offset (use a per-patient key)
    keep_year=False,        # do NOT retain the year (Safe Harbor: year-only is the max)
)
print(result.deidentified_text)
# Admit -> antibiotics is still 2 days; admit -> discharge still 7 days; etc.

How interval preservation works

All dates in the document are moved by one offset (auto-selected as a random non-zero value in roughly ±1 year, or fixed with date_shift_days=). Because the offset is identical for every date, the difference between any two dates is unchanged:

real:    Mar 2  ──2d──▶ Mar 4  ──5d──▶ Mar 9
shifted: Jul 18 ──2d──▶ Jul 20 ──5d──▶ Jul 25     (offset = +138 days, intervals intact)