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Background: When selecting predictive tools, for implementation in clinicalpractice or for recommendation in guidelines, clinicians are challenged with anoverwhelming and ever-growing number of tools. Many of these have never beenimplemented or evaluated for comparative effectiveness. The authors developedan evidence-based framework for grading and assessment of predictive tools(GRASP), based on critical appraisal of published evidence. The objective ofthis study is to validate, update GRASP, and evaluate its reliability. Methods:We aimed at validating and updating GRASP through surveying a wideinternational group of experts then evaluating GRASP reliability. Results: Outof 882 invited experts, 81 valid responses were received. Experts overallstrongly agreed to GRASP evaluation criteria of predictive tools (4.35/5).Experts strongly agreed to six criteria; predictive performance (4.87/5),predictive performance levels (4.44/5), usability (4.68/5), potential effect(4.61/5), post-implementation impact (4.78/5) and evidence direction (4.26/5).Experts somewhat agreed to one criterion; post-implementation impact levels(4.16/5). Experts were neutral about one criterion; usability is higher thanpotential effect (2.97/5). Experts also provided recommendations to sixopen-ended questions regarding adding, removing or changing evaluationcriteria. The GRASP concept and its detailed report were updated then theinterrater reliability of GRASP was tested and found to be reliable. Discussionand Conclusion: The GRASP framework grades predictive tools based on thecritical appraisal of the published evidence across three dimensions: 1) Phaseof evaluation; 2) Level of evidence; and 3) Direction of evidence. The finalgrade of a tool is based on the highest phase of evaluation, supported by thehighest level of positive evidence, or mixed evidence that supports positiveconclusion.

Validating and Updating GRASP: A New Evidence-Based Framework for Grading and Assessment of Clinical Predictive Tools