Login / Signup

Developing a framework for evidence-based grading and assessment of predictive tools for clinical decision support.

Mohamed KhalifaFarah MagrabiBlanca Gallego
Published in: BMC medical informatics and decision making (2019)
GRASP framework builds on widely accepted concepts to provide standardised assessment and evidence-based grading of predictive tools. Unlike other methods, GRASP is based on the critical appraisal of published evidence reporting the tools' predictive performance before implementation, potential effect and usability during implementation, and their post-implementation impact. Implementing the GRASP framework as an online platform can enable clinicians and guideline developers to access standardised and structured reported evidence of existing predictive tools. However, keeping GRASP reports up-to-date would require updating tools' assessments and grades when new evidence becomes available, which can only be done efficiently by employing semi-automated methods for searching and processing the incoming information.
Keyphrases
  • primary care
  • clinical decision support
  • quality improvement
  • healthcare
  • machine learning
  • working memory
  • systematic review
  • risk assessment
  • single cell
  • meta analyses
  • clinical evaluation