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Data migration best practices

Data migration best practices in healthcare are the playbook for moving PHI when you upgrade an EHR, go to the cloud, or consolidate after a merger. The URL is generic (“data migration”) because that is the query; the work is still clinical: one wrong allergy row or a broken DICOM tag is a patient-safety event, not a failed IT ticket.

If you meant whether the data are any good before you move them → data quality in healthcare. If you meant who owns the rules → data governance in healthcare. If you meant HIPAA transport of the copy → HIPAA-compliant data transfer.

This page is a 10-point playbook. PYCAD is not a migration vendor and does not run your cutover.

The 10-point playbook

# Practice Why it matters on PHI
1 Pre-migration assessment Inventory sources, DICOM archives, interfaces, and who uses them. Unmapped feeds are how labs vanish on Monday.
2 Quality validation and cleansing Duplicates, broken MRNs, empty allergies. Moving dirt is how the new EHR starts untrusted. See the quality page.
3 Phased cutover Waves (department, facility, or data class). A big-bang EHR weekend is how you meet the incident commander.
4 Automated testing Row counts, checksums, coded-value spot checks, image open tests. Manual sampling does not cover a PACS.
5 Rollback Named RTO/RPO, a tested restore, and a trigger that is not “we will know.” Keep read-only legacy for a defined window.
6 Mapping documentation Field-level maps, including ICD / SNOMED / DICOM tag transforms, versioned like code. Auditors will ask.
7 Parallel run Same encounters through old and new; reconcile before you pull the plug. Highest confidence, highest cost — use it on the clinical core.
8 Change management Clinician champions, role-based training, a place to report “this chart is wrong.” Adoption is the migration.
9 Performance baselines Capture query and study-open times on the source; the new cloud is not faster because the slide said so.
10 Post-migration monitoring Dashboards from hour one: error rates, interface backlogs, missing-image tickets. Go-live is the start of hypercare.

Healthcare-specific pressure

Treat this as a clinical go-live, not a data-center move:

  • MPI / identity — merge rules before load, or you mint duplicates the EMPI will spend a year chasing.
  • Legal medical record — retention, legal hold, and a plan for the legacy chart that still has to be produced in court.
  • Imaging — DICOM is not “files on a share.” Instance counts, transfer syntax, and a viewer test per modality belong in the test plan. PACS cutovers fail silently: the study is “there” and will not open.
  • Interfaces — every HL7 feed is a dependency. Freeze, replay, or dual-publish; do not assume vendors will re-point on the day.
  • BAA and encryption — contractors who touch the extract are business associates. The copy on the staging bucket is still PHI.

What not to do

Do not cleanse “later.” Do not skip a rollback drill. Do not let mapping live in one analyst’s spreadsheet. Do not call a vendor demo a rehearsal. And do not treat decommissioned disks as afterthoughts — retired arrays are a breach waiting for facilities to recycle them.

PYCAD implements imaging pipelines on top of DICOM / FHIR / PACS. It does not migrate your EHR or run your cutover. Case studies.

We build custom medical imaging platforms — advanced DICOM viewers, AI segmentation, and the clinical systems around them.

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