# Deduplicating Patient Records

Deduplicating patient records from multiple sources is a nuanced workflow. We've put this guide together to go over the basics of merging patient records, and review some of the most important technical design considerations when building a patient deduplication pipeline. The pipeline described here is the basis of an [Enterprise Master Patient Index](https://en.wikipedia.org/wiki/Enterprise_master_patient_index) (EMPI).

We've organized the guide as follows:

- First, we review the [high-level architecture of a patient deduplication pipeline](/content/docs/fhir-datastore/patient-deduplication/architecture-overview/index.html)
- Then we talk about [ingesting records with either a batch or incremental pipeline](/content/docs/fhir-datastore/patient-deduplication/ingestion/index.html)
- Next, we discuss how to [match duplicate records](/content/docs/fhir-datastore/patient-deduplication/matching/index.html)
- Finally, we go into some detail on the specific rules that you can use to perform deduplication by [merging records](/content/docs/fhir-datastore/patient-deduplication/merging/index.html)

While it requires some planning up front, reconciling patient data from multiple sources can create a powerful data asset to power your clinical workflows. This guide may not be exhaustive, but it serves as a starting point for building a production ready deduplication workflow.

The merge techniques described here are general purpose, but can exist in two contexts (a) automatic merge, (b) manual merge or "human-in-the-loop." In both cases, audit reports are produced allowing visibility into why records were matched, why they were merged and who merged them.

You can also check out our [blog post](/content/blog/patient-deduplication/index.html) on the topic for more information.