Matching Module

In progress

This module is in progress and open for Community review and feedback. You are invited to provide feedback in the virtual forum or as a comment in the Google Document. Please provide your name comments.

Purpose

This module outlines key steps for designing and implementing an effective approach for matching person-level records within and across health-related datasets. It is intended for health data analysts, IT systems managers, developers, and program implementers.

Learning Objectives

At the end of this module, readers should be able to:

1. Name the three key phases of a person-matching approach and describe what occurs in each phase.

2. Describe how data quality can affect person matching and state ways that identifier data can be assessed and improved.

3. Understand different types of matching strategies and the advantages and disadvantages of each.

4. Describe methods for evaluating the performance of the matching algorithm.

5. State rationale for ongoing monitoring and enhancement of the matching process.

Module Moderators

Dr. Toan Ong - Email: [e-mail]

Dr. Shaun Grannis [e-mail]

Co-Authors

If you are interested in partnering on the further development/refinement of this module, please connect with the module moderators.