Today, one of the main stake of the interfaced health information systems or networks is to be able to gather the different parts of the medical record of a patient without any risk to mix them with those of one other patient. This objective could appear easy to reach but only in theory because in practice many name are misspelled or erroneous and a great attention has to be paid to define what is the best identifier to link medical record. As a linkage using less informative identifiers could lead to linkage errors, it is essential to quantify the information associated to each identifier. The aim of this study was to estimate the discriminating power of different identifiers susceptible to be used in a record linkage process. This work showed the interest of three identifiers when linking data concerning a same patient using an automatic procedure based on the method proposed by Jaro; the date of birth, the first and the last names seemed to be the more appropriate identifiers. Including a poorly discriminating identifier like gender did not improve the results. Moreover, adding a second christian name, often missing, increased linkage errors. On the contrary, it seemed that using a phonetic treatment adapted to the French language could improve the results of linkage in comparison to the Soundex. However, whatever, the method used it seems necessary to improve the quality of identifier collection as it could greatly influence linkage results.