AI for reducing claims and compensation payments from missed fractures on radiographs.

Published in European radiology. Abstract: To evaluate the potential of BoneView, an artificial intelligence (AI) tool for fracture detection on radiographs in claims cases related to missed fractures that resulted in financial compensation. This retrospective, multicenter study included all patients who submitted a claim and received financial compensation for missed fractures on radiographs between January 2013 and December 2019 across the 38 university hospitals of the Greater Paris area (AP-HP-France). For each claimant, 5 control patients were selected from a contemporary single-center cohort of patients who underwent radiographs of the same anatomical regions (with or without fracture) performed in the emergency department of a university hospital, irrespective of fracture status. Three radiologists (musculoskeletal fellow, 5-year fellowship-trained radiologist, and > 20-year expert) independently performed blinded, unassisted, and AI-assisted interpretations following a 3-month washout. Sensitivity, specificity, and accuracy were calculated with and without AI and for standalone AI. Compensation amounts were used to estimate potentially avoidable payouts. 156 patients (mean age, 42.2 years; 113 (72.4%) males), including 26 claimants with missed fractures on radiographs and 130 controls, were evaluated. 27/130 (20.8%) of the control cohort had fractures. Standalone AI sensitivity was 80.8% (21/26; 95% CI [60.7-93.5]) for claimants and 96.3% (26/27; 95% CI [81.0-99.9]) for the control cohort (p = 0.10). AI assist...