Decision analysis for the assessment of a record linkage procedure: application to a perinatal network.
OBJECTIVE
According to European legislation, we must develop computer software allowing the linkage of medical records previously rendered anonymous. Some of them, like AUTOMATCH, are used in daily practice either to gather medical files in epidemiologic studies or for clinical purpose. In the first situation, the aim is to avoid homonymous errors, and in the second one, synonymous errors. The objective of this work is to study the effect of different parameters (number of identification variables, phonetic treatments of names, direct or probabilistic linkage procedure) on the reliability of the linkage in order to determine which strategy is the best according to the purpose of the linkage.


METHODS
The assessment of the Burgundy Perinatal Network requires the linking of discharge abstracts of mothers and neonates, collected in all the hospitals of the region. Those data are used to compare direct and probabilistic linkage, using different parameterization strategies.


RESULTS
If the linkage has to be performed in real time, so that no validation of indecisions generated by probabilistic linkage is possible, probabilistic linkage using three variables without any phonetic treatment seems to be the most appropriate approach, combined with a direct linkage using four variables applied to non-conclusive links. If a validation of indecisions is possible in an epidemiological study, probabilistic linkage using five variables, with a phonetic treatment adapted to the local language has to be preferred. For medical purpose, it should be combined with a direct linkage with four or five variables.


CONCLUSIONS
This paper reveals that the time and money available to manage indecision as well as the purpose of the linkage are of paramount importance for choosing a linkage strategy.
Quantin
C
C
Division of Medical Informatics, University Hospital, Dijon Cedex, France. catherine.quantin@chu-dijon.fr
Binquet
C
C
Allaert
F A
FA
Cornet
B
B
Pattisina
R
R
Leteuff
G
G
Ferdynus
C
C
Gouyon
J B
JB
D005602:France; D008498:Medical Record Linkage; D011336:Probability