Ronilda Lacson1, Ali S Raja2, David Osterbur3, Ivan Ip4, Louise Schneider5, Paul Bain3, Carol Mita3, Julia Whelan3, Patricia Silveira6, David Dement6, Ramin Khorasani7. 1. Center for Evidence Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA Harvard Medical School, Boston, MA 02115, USA rlacson@partners.org. 2. Harvard Medical School, Boston, MA 02115, USA Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA 02114, USA. 3. Harvard Medical School, Boston, MA 02115, USA Countway Library of Medicine, Boston, MA 02115, USA. 4. Center for Evidence Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA Harvard Medical School, Boston, MA 02115, USA Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA. 5. Harvard Medical School, Boston, MA 02115, USA Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA. 6. Center for Evidence Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA. 7. Center for Evidence Based Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA Harvard Medical School, Boston, MA 02115, USA.
Abstract
OBJECTIVE: For health information technology tools to fully inform evidence-based decisions, recommendations must be reliably assessed for quality and strength of evidence. We aimed to create an annotation framework for grading recommendations regarding appropriate use of diagnostic imaging examinations. METHODS: The annotation framework was created by an expert panel (clinicians in three medical specialties, medical librarians, and biomedical scientists) who developed a process for achieving consensus in assessing recommendations, and evaluated by measuring agreement in grading the strength of evidence for 120 empirically selected recommendations using the Oxford Levels of Evidence. RESULTS: Eighty-two percent of recommendations were assigned to Level 5 (expert opinion). Inter-annotator agreement was 0.70 on initial grading (κ = 0.35, 95% CI, 0.23-0.48). After systematic discussion utilizing the annotation framework, agreement increased significantly to 0.97 (κ = 0.88, 95% CI, 0.77-0.99). CONCLUSIONS: A novel annotation framework was effective for grading the strength of evidence supporting appropriate use criteria for diagnostic imaging exams.
OBJECTIVE: For health information technology tools to fully inform evidence-based decisions, recommendations must be reliably assessed for quality and strength of evidence. We aimed to create an annotation framework for grading recommendations regarding appropriate use of diagnostic imaging examinations. METHODS: The annotation framework was created by an expert panel (clinicians in three medical specialties, medical librarians, and biomedical scientists) who developed a process for achieving consensus in assessing recommendations, and evaluated by measuring agreement in grading the strength of evidence for 120 empirically selected recommendations using the Oxford Levels of Evidence. RESULTS: Eighty-two percent of recommendations were assigned to Level 5 (expert opinion). Inter-annotator agreement was 0.70 on initial grading (κ = 0.35, 95% CI, 0.23-0.48). After systematic discussion utilizing the annotation framework, agreement increased significantly to 0.97 (κ = 0.88, 95% CI, 0.77-0.99). CONCLUSIONS: A novel annotation framework was effective for grading the strength of evidence supporting appropriate use criteria for diagnostic imaging exams.
Authors: Zihao Yan; Ronilda Lacson; Ivan Ip; Vladimir Valtchinov; Ali Raja; David Osterbur; Ramin Khorasani Journal: AMIA Annu Symp Proc Date: 2017-02-10