Published in:
Open Access 01-12-2011 | Research article
Hospital deaths and adverse events in Brazil
Published in: BMC Health Services Research | Issue 1/2011
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Background
Adverse events are considered a major international problem related to the performance of health systems. Evaluating the occurrence of adverse events involves, as any other outcome measure, determining the extent to which the observed differences can be attributed to the patient's risk factors or to variations in the treatment process, and this in turn highlights the importance of measuring differences in the severity of the cases. The current study aims to evaluate the association between deaths and adverse events, adjusted according to patient risk factors.
Methods
The study is based on a random sample of 1103 patient charts from hospitalizations in the year 2003 in 3 teaching hospitals in the state of Rio de Janeiro, Brazil. The methodology involved a retrospective review of patient charts in two stages - screening phase and evaluation phase. Logistic regression was used to evaluate the relationship between hospital deaths and adverse events.
Results
The overall mortality rate was 8.5%, while the rate related to the occurrence of an adverse event was 2.9% (32/1103) and that related to preventable adverse events was 2.3% (25/1103). Among the 94 deaths analyzed, 34% were related to cases involving adverse events, and 26.6% of deaths occurred in cases whose adverse events were considered preventable. The models tested showed good discriminatory capacity. The unadjusted odds ratio (OR 11.43) and the odds ratio adjusted for patient risk factors (OR 8.23) between death and preventable adverse event were high.
Conclusions
Despite discussions in the literature regarding the limitations of evaluating preventable adverse events based on peer review, the results presented here emphasize that adverse events are not only prevalent, but are associated with serious harm and even death. These results also highlight the importance of risk adjustment and multivariate models in the study of adverse events.