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J Biomed Inform ; 61: 276-82, 2016 06.
Artículo en Inglés | MEDLINE | ID: mdl-27179758

RESUMEN

OBJECTIVE: To investigate disease-disease associations by conducting a network analysis using Korean nationwide claims data. METHODS: We used the claims data from the Health Insurance Review and Assessment Service-National Patient Sample for the year 2011. Among the 2049 disease codes in the claims data, 1154 specific disease codes were used and combined into 795 representative disease codes. We analyzed for 381 representative codes, which had a prevalence of >0.1%. For disease code pairs of a combination of 381 representative disease codes, P values were calculated by using the χ(2) test and the degrees of associations were expressed as odds ratios (ORs). RESULTS: For 5515 (7.62%) statistically significant disease-disease associations with a large effect size (OR>5), we constructed a human disease network consisting of 369 nodes and 5515 edges. The human disease network shows the distribution of diseases in the disease network and the relationships between diseases or disease groups, demonstrating that diseases are associated with each other, forming a complex disease network. We reviewed 5515 disease-disease associations and classified them according to underlying mechanisms. Several disease-disease associations were identified, but the evidence of these associations is not sufficient and the mechanisms underlying these associations have not been clarified yet. Further research studies are needed to investigate these associations and their underlying mechanisms. CONCLUSION: Human disease network analysis using claims data enriches the understanding of human diseases and provides new insights into disease-disease associations that can be useful in future research.


Asunto(s)
Algoritmos , Enfermedad , Seguro de Salud , Humanos , Corea (Geográfico) , Oportunidad Relativa
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