  Background: Clinical predictive tools quantify contributions of relevant
patient characteristics to derive likelihood of diseases or predict clinical
outcomes. When selecting a predictive tool, for implementation at clinical
practice or for recommendation in clinical guidelines, clinicians are
challenged with an overwhelming and ever growing number of tools, most of which
have never been implemented or assessed for comparative effectiveness.
Objective: To develop a comprehensive framework to Grade and Assess Predictive
tools (GRASP), and provide clinicians with a standardised, evidence based
system to support their search for and selection of effective tools. Methods: A
focused review of literature was conducted to extract criteria along which
tools should be evaluated. An initial framework was designed and applied to
assess and grade five tools: LACE Index, Centor Score, Wells Criteria, Modified
Early Warning Score, and Ottawa knee rule. After peer review, by expert
clinicians and healthcare researchers, the framework was revised and the
grading of the tools was updated. Results: GRASP framework grades predictive
tools based on published evidence across three dimensions: 1) Phase of
evaluation; 2) Level of evidence; and 3) Direction of evidence. The final grade
of a tool is based on the highest phase of evaluation, supported by the highest
level of positive evidence, or mixed evidence that supports positive
conclusion. Discussion and Conclusion: the GRASP framework builds on well
established models and 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 predictive tools predictive performance before implementation,
potential effect and usability during implementation, and their post
implementation impact.
