An Introduction to Probabilistic Record Linkage with a Focus on Linkage Processing for WTC Registries

Area of Science:

• Data Science
• Information Science
• Computer Science

Background:

• Record linkage has expanded significantly since World War II.
• It is utilized across various sectors including industry, government, and academia.
• Diverse academic fields like history, public health, and demography depend on record linkage.

Purpose of the Study:

• To provide a historical overview of data linkage development.
• To introduce different types of data linkage.
• To discuss underlying models and practical considerations for record linkage programs.

Main Methods:

• Exploration of Fellegi-Sunter-based methods for probabilistic record linkage.
• Examination of machine learning approaches for data linkage.
• Review of Bayesian methods in probabilistic record linkage.

Main Results:

• Discussion of practical aspects such as data standardization and privacy.
• Presentation of recommendations for organizations managing record linkage initiatives.
• Emphasis on applications in studying long-term disaster complications, exemplified by 9/11.

Conclusions:

• Record linkage is a vital, evolving field with diverse applications.
• Understanding different linkage models and practicalities is crucial for effective programs.
• The study offers guidance for optimizing record linkage, particularly for longitudinal health outcome research.