Revista espanola de salud publica · 2015
[Contribution of Electronic Health Record in Surveillance of Notifiable Diseases].
Оценочное исследованиеСтатьяНазвание и аннотация: Перевод в очереди
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Onieva-García María Ángeles, López-Hernández Begoña, Molina-Rueda María José, Cabrera-Castro Natalia, Mochón-Ochoa María Mar
Аннотация
BACKGROUND: In 2009 a system was introduced for the automatic import (AI) of cases with suspected notifiable diseases (ND) from electronic medical record (EMR) to RedAlerta, an application for surveillance in Andalusia. At present, the contribution of this system to classical active statement has not been determined enough. The main objective of this study is to evaluate the usefulness of IA in the province of Granada, between 2009 and 2014.
METHODS: During the study period (2009-2014), an epidemiologist assessed whether AI met declaration criteria or not. We calculate the contribution of AI to RedAlerta and the percentage of validation of AI, estimating 95% CI.
RESULTS: The contribution of AI was 17.3% (95% CI 16.1 to 18.5); and type of statement, 5.2% (95% CI 4.1 to 6.5) for urgent and 24.4% (95% CI 22.7 to 26.2) for ordinary. The contribution was higher (more than 45%) in Lyme disease, congenital hypothyroidism, genital herpes, hepatitis C and other viral hepatitis. 30% (95% CI 28.1 to 32) of AI were validated; 39.9% (95% CI 33 to 47.2) urgent and 29.1% (95% CI 27.2 to 31.2%) ordinary. The percentage of validation was higher than 45% (between 47.5 and 100%) in vaccine-preventable diseases, sexually transmitted infections and low incidence.
CONCLUSIONS: Although not replace manual reporting and requires verification, the AI system is useful and increases the completeness of the epidemiological surveillance system.
METHODS: During the study period (2009-2014), an epidemiologist assessed whether AI met declaration criteria or not. We calculate the contribution of AI to RedAlerta and the percentage of validation of AI, estimating 95% CI.
RESULTS: The contribution of AI was 17.3% (95% CI 16.1 to 18.5); and type of statement, 5.2% (95% CI 4.1 to 6.5) for urgent and 24.4% (95% CI 22.7 to 26.2) for ordinary. The contribution was higher (more than 45%) in Lyme disease, congenital hypothyroidism, genital herpes, hepatitis C and other viral hepatitis. 30% (95% CI 28.1 to 32) of AI were validated; 39.9% (95% CI 33 to 47.2) urgent and 29.1% (95% CI 27.2 to 31.2%) ordinary. The percentage of validation was higher than 45% (between 47.5 and 100%) in vaccine-preventable diseases, sexually transmitted infections and low incidence.
CONCLUSIONS: Although not replace manual reporting and requires verification, the AI system is useful and increases the completeness of the epidemiological surveillance system.