title: Survey of adverse drug reactions on a pediatric ward: a strategy for early and detailed detection.
abstract: OBJECTIVE
  Adverse drug reactions (ADRs) occur frequently in children. However, the exact incidence of ADRs is unknown. Therefore, we studied ADRs in 1 ward and assessed whether a general approach, eg, by a computerized monitoring system, to detect ADRs in children is feasible and likely to yield a higher rate of early detected ADRs. The aim was to assess the usefulness of a computerized monitoring system before implementing costly adaptations.
  
  
  METHODS
  An 8-month prospective study was conducted at a 10-bed pediatric isolation ward of the University Hospital. Charts were reviewed once weekly by a pharmacoepidemiological team. Clinical signs as well as laboratory changes were documented and assessed. Algorithms were used to assess the probability and severity of each detected event.
  
  
  RESULTS
  All 214 patients admitted were enrolled in the study. A total of 68 ADRs were detected in 46 of 214 patients by the pharmacoepidemiological team. Thirty-four ADRs (50%) were detected by the staff physician, and 27 (40%) were detected primarily by analyzing laboratory parameters. Antibiotics-associated ADRs (50%) predominated, followed by glucocorticoids (16%), tuberculostatic (4%), and immunosuppressive agents (4%). In 5 cases, an ADR was responsible for the prolongation of hospital stay, and in 4 children, the ADR was responsible for hospitalization.
  
  
  CONCLUSIONS
  The detection rate of ADRs would almost be doubled by a computerized monitoring system analyzing laboratory data. Implementation of a computer monitor system that automatically generates laboratory signals may help to identify ADRs in children, and to reduce morbidity and hospital stay, as well as costs.
authors.affiliation: Department of Pediatrics, University of Erlangen-Nürnberg, Erlangen, Germany.
authors.forename: Jutta
authors.initials: J
authors.lastname: Weiss
authors.forename: Sabine
authors.initials: S
authors.lastname: Krebs
authors.forename: Claudia
authors.initials: C
authors.lastname: Hoffmann
authors.forename: Ulrike
authors.initials: U
authors.lastname: Werner
authors.forename: Antje
authors.initials: A
authors.lastname: Neubert
authors.forename: Kay
authors.initials: K
authors.lastname: Brune
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Rascher
mesh_terms: D000293:Adolescent; D016907:Adverse Drug Reaction Reporting Systems; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D003141:Communicable Diseases / Q000188:drug therapy; D003625:Data Collection; D064420:Drug-Related Side Effects and Adverse Reactions; D006743:Hospital Bed Capacity, under 100; D006757:Hospital Units / Q000706:statistics & numerical data*; D006785:Hospitals, University / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D010356:Patient Isolation; D010372:Pediatrics / Q000706:statistics & numerical data*; D011336:Probability; D011446:Prospective Studies