Validating and Updating GRASP: A New Evidence-Based Framework for Grading and Assessment of Clinical Predictive Tools
Mohamed Khalifa, Farah Magrabi, Blanca Gallego

TL;DR
This study validates and updates the GRASP framework, an evidence-based tool for grading clinical predictive tools, demonstrating its reliability and expert acceptance for assessing predictive performance, usability, and impact.
Contribution
The paper introduces an updated, reliable version of the GRASP framework, incorporating expert feedback to improve evaluation criteria for clinical predictive tools.
Findings
Experts strongly agreed on core evaluation criteria
GRASP framework showed high interrater reliability
Updated framework effectively grades predictive tools
Abstract
Background: When selecting predictive tools, for implementation in clinical practice or for recommendation in guidelines, clinicians are challenged with an overwhelming and ever-growing number of tools. Many of these have never been implemented or evaluated for comparative effectiveness. The authors developed an evidence-based framework for grading and assessment of predictive tools (GRASP), based on critical appraisal of published evidence. The objective of this study is to validate, update GRASP, and evaluate its reliability. Methods: We aimed at validating and updating GRASP through surveying a wide international group of experts then evaluating GRASP reliability. Results: Out of 882 invited experts, 81 valid responses were received. Experts overall strongly agreed to GRASP evaluation criteria of predictive tools (4.35/5). Experts strongly agreed to six criteria; predictive…
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Taxonomy
TopicsCardiac, Anesthesia and Surgical Outcomes
