Which action helps prevent duplicate patient records in Phreesia?

• A. Running de-duplication and merging suspected duplicates using matching identifiers (name, DOB, phone, MRN)
• B. Deleting all duplicates manually from the system
• C. Restricting new registrations to a single user
• D. Using a global unique ID only for new patients

Answer: (A)

Preventing duplicate patient records comes from running de-duplication and merging suspected duplicates using identifiers such as name, date of birth, phone, and MRN. This approach scans existing records for near matches, flags likely duplicates, and merges them into a single, authoritative patient record. By creating one complete history per patient, you maintain consistent contact and medical information, reduce fragmentation, and minimize errors in care and billing.

Deleting duplicates manually isn’t practical or reliable because it’s time-consuming and prone to accidentally removing or mislinking important history. Restricting registrations to a single user doesn’t address duplicates that already exist or catch near-matches from data entry. Relying on a global unique ID only for new patients helps future entries but doesn’t clean up or prevent duplicates in the current dataset. The de-duplication and merging workflow directly tackles both detection and consolidation, making it the best choice.