[Consensus validation of a tool to identify inappropriate prescribing in pediatrics (POPI)]

Arch Pediatr. 2016 May;23(5):481-90. doi: 10.1016/j.arcped.2016.02.010. Epub 2016 Apr 8.
[Article in French]

Abstract

Objective: Medication errors including inappropriate prescriptions and drug omissions are one of the causes of adverse drug events in children. Our aim was to develop a preliminary screening tool to detect omissions and inappropriate prescriptions in pediatrics based on French and international guidelines.

Materiel and methods: Disease classification was based on the prevalence rate of pathology and hospital statistics. The criteria were obtained by reviewing many French and international references. The Delphi consensus technique was used to establish the content validity of POPI. The level of agreement and the proposals of healthcare professionals was noted on a nine-point Likert scale.

Results: The criteria were categorized according to the main physiological systems (gastroenterology, respiratory infections, pain, neurology, dermatology, and miscellaneous). They were distributed to 16 French pediatric panelists (eight pharmacists, eight pediatricians who were hospital-based [50%] or working in the community [50%]). After two rounds of the Delphi process, 101 of 108 criteria were chosen with strong consensus (76 inappropriate prescriptions and 25 omissions).

Conclusions: POPI is the first screening tool to detect inappropriate prescriptions and omissions in pediatrics. It is now necessary to conduct a prospective study to determine inter-rater reliability and the tool's detection capacity.

Publication types

  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Consensus*
  • Drug Prescriptions / statistics & numerical data*
  • Female
  • France / epidemiology
  • Guidelines as Topic
  • Humans
  • Inappropriate Prescribing / statistics & numerical data*
  • Male
  • Middle Aged
  • Pediatrics*
  • Pharmacists / statistics & numerical data
  • Physicians / statistics & numerical data
  • Practice Patterns, Physicians' / statistics & numerical data*
  • Prevalence
  • Reproducibility of Results