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A Simple Sampling Method for Estimating the Accuracy of Large Scale Record Linkage Projects

journal contribution
posted on 2022-11-14, 01:43 authored by James H Boyd, Tenniel Guiver, Sean M Randall, Anna M Ferrante, James B Semmens, Phil Anderson, Teresa Dickinson
SummaryBackground: Record linkage techniques allow different data collections to be brought together to provide a wider picture of the health status of individuals. Ensuring high linkage quality is important to guarantee the quality and integrity of research. Current methods for measuring linkage quality typically focus on precision (the proportion of incorrect links), given the difficulty of measuring the proportion of false negatives.Objectives: The aim of this work is to introduce and evaluate a sampling based method to estimate both precision and recall following record linkage.Methods: In the sampling based method, record-pairs from each threshold (including those below the identified cut-off for acceptance) are sampled and clerically reviewed. These results are then applied to the entire set of record-pairs, providing estimates of false positives and false negatives. This method was evaluated on a synthetically generated dataset, where the true match status (which records belonged to the same person) was known.Results: The sampled estimates of linkage quality were relatively close to actual linkage quality metrics calculated for the whole synthetic dataset. The precision and recall measures for seven reviewers were very consistent with little variation in the clerical assessment results (overall agreement using the Fleiss Kappa statistics was 0.601).Conclusions: This method presents as a possible means of accurately estimating matching quality and refining linkages in population level linkage studies. The sampling approach is especially important for large project linkages where the number of record pairs produced may be very large often running into millions.

History

Journal

Methods of Information in Medicine

Volume

55

Article number

03

Pagination

276-283

Location

New York, N.Y.

ISSN

0026-1270

eISSN

2511-705X

Language

English

Publication classification

C1 Refereed article in a scholarly journal

Issue

3

Publisher

Thieme Publishing Group