Possible adverse drug events leading to hospital admission in a Brazilian teaching hospital

Clinics (Sao Paulo). 2014 Mar;69(3):163-7. doi: 10.6061/clinics/2014(03)03.

Abstract

Objectives: Drug safety problems can lead to hospital admission. In Brazil, the prevalence of hospitalization due to adverse drug events is unknown. This study aims to estimate the prevalence of hospitalization due to adverse drug events and to identify the drugs, the adverse drug events, and the risk factors associated with hospital admissions.

Method: A cross-sectional study was performed in the internal medicine ward of a teaching hospital in São Paulo State, Brazil, from August to December 2008. All patients aged ≥18 years with a length of stay ≥24 hours were interviewed about the drugs used prior to hospital admission and their symptoms/complaints/causes of hospitalization.

Results: In total, 248 patients were considered eligible. The prevalence of hospitalization due to potential adverse drug events in the ward was 46.4%. Overprescribed drugs and those indicated for prophylactic treatments were frequently associated with possible adverse drug events. Frequently reported symptoms were breathlessness (15.2%), fatigue (12.3%), and chest pain (9.0%). Polypharmacy was a risk factor for the occurrence of possible adverse drug events.

Conclusion: Possible adverse drug events led to hospitalization in a high-complexity hospital, mainly in polymedicated patients. The clinical outcomes of adverse drug events are nonspecific, which delays treatment, hinders causality analysis, and contributes to the underreporting of cases.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Distribution
  • Brazil / epidemiology
  • Cross-Sectional Studies
  • Drug-Related Side Effects and Adverse Reactions / epidemiology*
  • Female
  • Hospitalization / statistics & numerical data*
  • Hospitals, Teaching / statistics & numerical data
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Patient Admission / statistics & numerical data*
  • Prevalence
  • Risk Factors
  • Sex Distribution
  • Statistics, Nonparametric