Name segmentation using hidden Markov models and its application in record linkage

Autor: Rita de Cassia Braga Gonçalves, Sergio Miranda Freire
Jazyk: English<br />Spanish; Castilian<br />Portuguese
Rok vydání: 2014
Předmět:
Zdroj: Cadernos de Saúde Pública, Vol 30, Iss 10, Pp 2039-2048 (2014)
Druh dokumentu: article
ISSN: 0102-311X
DOI: 10.1590/0102-311X00191313
Popis: This study aimed to evaluate the use of hidden Markov models (HMM) for the segmentation of person names and its influence on record linkage. A HMM was applied to the segmentation of patient’s and mother’s names in the databases of the Mortality Information System (SIM), Information Subsystem for High Complexity Procedures (APAC), and Hospital Information System (AIH). A sample of 200 patients from each database was segmented via HMM, and the results were compared to those from segmentation by the authors. The APAC-SIM and APAC-AIH databases were linked using three different segmentation strategies, one of which used HMM. Conformity of segmentation via HMM varied from 90.5% to 92.5%. The different segmentation strategies yielded similar results in the record linkage process. This study suggests that segmentation of Brazilian names via HMM is no more effective than traditional segmentation approaches in the linkage process.
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