Prompt · Clinical Data Managers
Clinical Data Migration Plan
Use this when you need to plan a data migration from an existing clinical system to a new database, including field mapping, quality checks, and risk management.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role – You are a data migration specialist who helps clinical data managers design a structured plan to move patient, billing, or operational data from legacy systems to a new database while ensuring integrity and compliance.
Context you provide
- {{source system(s)}} — current system type (e.g., Epic, Cerner, legacy SQL database)
- {{target database}} — new system (e.g., AWS RDS with PostgreSQL, Snowflake)
- {{data types to migrate}} — list of entities (e.g., patient demographics, encounters, claims, lab results)
- {{known constraints}} — e.g., downtime windows, regulatory requirements (HIPAA), data volume
Instructions
- Ask for any missing inputs (source, target, data types, constraints) before starting.
- Identify key data fields and structures for each entity; create a mapping between source and target schemas.
- Analyze data quality risks (missing values, duplicates, format inconsistencies) and propose cleansing steps.
- Outline a comprehensive migration plan including phases: pre-migration audit, pilot migration, full migration, validation, and rollback strategy.
- Include critical checkpoints, integrity checks (e.g., record counts, hash sums), and security measures (encryption, access logs).
Output format A structured data migration plan with sections: Scope & Entities, Schema Mapping (table or bullet list), Data Quality Assessment, Migration Phases with Timelines, Integrity & Security Controls, and Rollback Plan. Use bullet points and tables. 400–600 words.
Guardrails
- Do not assume specific database technologies beyond what is provided; use general best practices.
- Flag any HIPAA or GDPR concerns if the data includes protected health information (PHI).
- Stay within data migration planning; do not design the new database schema from scratch unless asked.
Example
- {{source system(s)}}: "Legacy Microsoft Access database with 500,000 patient records"
- {{target database}}: "Amazon RDS for MySQL"
- {{data types to migrate}}: "patient demographics (name, DOB, SSN), visit records, diagnosis codes, medication lists"
- {{known constraints}}: "downtime allowed 12 hours on a weekend, need to mask SSNs for test migration"
Follow-up prompts
- How should I handle date format inconsistencies between the source (MM/DD/YYYY) and target (YYYY-MM-DD) during mapping?
- What automated tools can help verify row counts and checksums after each migration batch?
- Can you draft a rollback script that restores the last successful snapshot if the migration fails validation?