[Preventable adverse drug events in hospitalized patients]

Med Clin (Barc). 2006 Jan 28;126(3):81-7. doi: 10.1157/13083875.
[Article in Spanish]


Background and objective: To determine the incidence of adverse drug events (ADE) in hospitalized patients, identify those that were potentially preventable, and asses the drug classes involved, the clinical symptoms and the type of medication errors that led to the preventable ADE.

Patients and method: An observational study of ADE prevalence in hospitalized patients in internal medicine, pneumology, gastroenterology, nephrology and neurology wards, over a six-month period, at a tertiary university hospital. ADE were prospectively detected through physician and nurses reporting fostered by daily visits of a clinical research and retrospectively through review of medical records using event codes as defined by the IDC-9-CM system.

Results: In a total of 2,643 hospitalized patients, 191 (7.2%) ADE were detected. Of these, 38 cases (19.9%) were classified as preventable, of which 21.1% were mild; 60.5% moderate and 18.4% serious or life-threatening. Preventable ADE were frequently associated with anti-infective drugs (22.9%), diuretics (18.8%) and digoxin (16.7%). Inadequate therapy monitoring (28.3%), excessive dosage (21.7%), selection of an inappropriate drug according to patient characteristics and/or to diagnosis (15.0%), lack of prescription of a necessary drug (15.0%) and drug-drug interactions (11.7%) were the most common identified type of errors leading to preventable ADE.

Conclusions: 1.4% of hospitalized patients in medical wards experienced potentially preventable ADE. Healthcare professionals and administrators must be made aware of the scope of this problem so that they will implement effective safety practices directed to reduce the incidence of medication errors, particularly prescription and monitoring errors.

Publication types

  • English Abstract

MeSH terms

  • Drug-Related Side Effects and Adverse Reactions*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Medication Errors* / statistics & numerical data