Accuracy of probabilistic record linkage applied to health databases: systematic review.
OBJECTIVE
To analyze both national and international literature on validity of record linkage procedure of health databases focusing on quality assessment of results.


METHODS
A systematic review of cohort, case-control, and cross-sectional studies that evaluated quality of probabilistic record linkage of health databases was conducted. Cochrane methodology of systematic reviews was used. The following databases were widely searched: Medline, LILACS, Scopus, SciELO and Scirus. A time filter was not applied and articles were searched in the following languages: Portuguese, Spanish, French and English.


RESULTS
Summary measures of the quality of probabilistic record linkage were sensitivity, specificity, and positive predictive value. There were identified 202 studies, and after applying the inclusion criteria, a total of 33 articles were reviewed. Only six had complete data on the summary measures of interest. The main limitations were: no reviewer to evaluate titles and abstracts; and no blinding of the article's authors in the review process. Most scientific publications in this field were from the United States, United Kingdom, and New Zealand. Overall, the accuracy of probabilistic record linkage of databases ranged from 74% to 98% sensitivity and 99% to 100% specificity.


CONCLUSIONS
Probabilistic record linkage of health databases has notably been characterized by high sensitivity and greater flexibility of the procedure's sensitivity, indicating concern with data accuracy. The positive predictive value in studies shows a high proportion of truly positive record pairs. The quality assessment of these procedures has been proved essential for validating the results obtained in these studies, and can also contribute to improve large health databases available in Brazil.
Programa de Pós-Graduação em Saúde Pública, Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brasil.
Daniele Pinto da
DP
Silveira
Elizabeth
E
Artmann
D035843:Biomedical Research; D016208:Databases, Factual; D008498:Medical Record Linkage / Q000592:standards*; D016347:Medical Records Systems, Computerized; D012680:Sensitivity and Specificity