Comparison of two methods to estimate adverse events in the IBEAS Study (Ibero-American study of adverse events): cross-sectional versus retrospective cohort design
Aranaz Andrés, Jesús María (UNIR)
Aibar Remón, Carlos
Gea-Velázquez de Castro, María Teresa
Limón Ramírez, Ramón
López Fresneña, Nieves (UNIR)
Díaz-Agero Pérez, Cristina (UNIR)
Terol García, Enrique
Larizgoitia Jauregui, Itziar
Tipo de Ítem:Articulo Revista Indexada
Background Adverse events (AEs) epidemiology is the first step to improve practice in the healthcare system. Usually, the preferred method used to estimate the magnitude of the problem is the retrospective cohort study design, with retrospective reviews of the medical records. However this data collection involves a sophisticated sampling plan, and a process of intensive review of sometimes very heavy and complex medical records. Cross-sectional survey is also a valid and feasible methodology to study AEs. Objectives The aim of this study is to compare AEs detection using two different methodologies: cross-sectional versus retrospective cohort design. Setting Secondary and tertiary hospitals in five countries: Argentina, Colombia, Costa Rica, Mexico and Peru. Participants The IBEAS Study is a cross-sectional survey with a sample size of 11 379 patients. The retrospective cohort study was obtained from a 10% random sample proportional to hospital size from the entire IBEAS Study population. Methods This study compares the 1-day prevalence of the AEs obtained in the IBEAS Study with the incidence obtained through the retrospective cohort study. Results The prevalence of patients with AEs was 10.47% (95% CI 9.90 to 11.03) (1191/11 379), while the cumulative incidence of the retrospective cohort study was 19.76% (95% CI 17.35% to 22.17%) (215/1088). In both studies the highest risk of suffering AEs was seen in Intensive Care Unit (ICU) patients. Comorbid patients and patients with medical devices showed higher risk. Conclusion The retrospective cohort design, although requires more resources, allows to detect more AEs than the cross-sectional design.
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