Automated Radiology-Operative Note Communication Tool; Closing the Loop in Musculoskeletal Imaging

William Moore, Ankur Doshi, Priya Bhattacharji, Soterios Gyftopoulos, Gina Ciavarra, Danny Kim, Michael Recht

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Rationale and Objectives: Correlation of imaging studies and reference standard outcomes is a significant challenge in radiology. This study evaluates the effectiveness of a new communication tool by assessing the ability of this system to correctly match the imaging studies to arthroscopy reports and qualitatively assessing radiologist behavior before and after the implementation of this system. Materials and Methods: Using a commercially available communication or educational tool and applying a novel matching rule algorithm, radiology and arthroscopy reports were matched from January 17, 2017 to March 1, 2017 based on anatomy. The interpreting radiologist was presented with email notifications containing the impression of the imaging report and the entire arthroscopy report. Total correlation rate of appropriate report pairings, modality-specific correlation rate, and the anatomy-specific correlation rate were calculated. Radiologists using the system were given a survey. Results: Overall correlation rate for all musculoskeletal imaging was 83.1% (433 or 508). Low correlation was found in fluoroscopic procedures at 74.4%, and the highest correlation was found with ultrasound at 88.4%. Anatomic location varied from 51.6% for spine to 98.8% for hips and pelvis studies. Survey results revealed 87.5% of the respondents reporting being either satisfied or very satisfied with the new communication tool. The survey also revealed that some radiologists reviewed more cases than before. Conclusions: Matching of radiology and arthroscopy reports by anatomy allows for excellent report correlation (83.1%). Automated correlation improves the quality and efficiency of feedback to radiologists, providing important opportunities for learning and improved accuracy.

Original languageEnglish
Pages (from-to)244-249
Number of pages6
JournalAcademic Radiology
Volume25
Issue number2
DOIs
StatePublished - Feb 2018
Externally publishedYes

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