Literature DB >> 24833644

The discrepancy rate between preliminary and official reports of emergency radiology studies: a performance indicator and quality improvement method.

Ghada Issa1, Bedros Taslakian1, Malak Itani1, Eveline Hitti2, Nicholas Batley2, Miriam Saliba2, Fadi El-Merhi3.   

Abstract

BACKGROUND: At teaching hospitals, radiology residents give preliminary reports for imaging studies requested from the Emergency Department (ED). Discrepancy rates between preliminary and final reports represent an important performance indicator.
PURPOSE: To present a system for feedback and follow-up of discrepancies, identify the variables associated with the rate and severity of such discrepancies, target the weaknesses, and suggest the need of a standard reference value for comparison among institutions.
MATERIAL AND METHODS: A monitoring and communication system between the Department of Diagnostic Radiology and Emergency Department was initiated to mark and follow all studies from the ED for which the official reading was different than the preliminary interpretation. Data analysis was performed on all studies from 1 June 2011 to 31 May 2012, based on the severity of the discrepancy, imaging modality, resident training level, and organ system. The distribution of the number of discrepancies among the different resident levels and imaging modalities was determined, as well as the distribution of three severity scores in correlation with other variables.
RESULTS: The overall discrepancy rate was 1.62%. The discrepancy rate was higher for first and second year residents (1.62% and 1.96%) than for third and fourth year residents (1.35% and 1.24%). It was higher for computed tomography (2.13%) than for radiographs (1.29%) and ultrasound (0.8%) (P value < 0.01), and higher for musculoskeletal (1.61%) than non-musculoskeletal (0.99%) radiographs (P value = 0.0003). Discrepancies with severity score one constituted 35.5% of the total discrepancies, those with severity scores two and three constituted 22.9% and 41.6%, respectively.
CONCLUSION: We have demonstrated a system for follow-up of discrepancy in interpreting emergency radiology studies, and recorded the discrepancy rate, with further analysis based on different variables. In terms of quality assurance, a periodical analysis might help to reduce the number of discrepant reports by targeted intervention. © The Foundation Acta Radiologica 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Keywords:  Diagnostic imaging; discrepancy; emergency radiology; misdiagnosis; preliminary report; resident reporting

Mesh:

Year:  2014        PMID: 24833644     DOI: 10.1177/0284185114532922

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  8 in total

1.  Comparison-Bot: an Automated Preliminary-Final Report Comparison System.

Authors:  Amit D Kalaria; Ross W Filice
Journal:  J Digit Imaging       Date:  2016-06       Impact factor: 4.056

2.  Implementation and Validation of PACS Integrated Peer Review for Discrepancy Recording of Radiology Reporting.

Authors:  A W Olthof; P M A van Ooijen
Journal:  J Med Syst       Date:  2016-07-21       Impact factor: 4.460

3.  Risk factors for computed tomography interpretation discrepancy in emergently transferred patients.

Authors:  Hyun Sim Lee; Jinwoo Myung; Min Ji Choi; Hye Jung Shin; Incheol Park; Sung Phil Chung; Ji Hoon Kim
Journal:  World J Emerg Med       Date:  2022

4.  Patient recalls associated with resident-to-attending radiology report discrepancies: predictive factors for risky discrepancies.

Authors:  A Yeon Son; Gil-Sun Hong; Choong Wook Lee; Ju Hee Lee; Won Jung Chung; Jung Bok Lee
Journal:  Insights Imaging       Date:  2022-06-04

5.  Assigning responsibility to close the loop on radiology test results.

Authors:  Janice L Kwan; Hardeep Singh
Journal:  Diagnosis (Berl)       Date:  2017-06-15

6.  Performance of overnight on-call radiology residents in interpreting unenhanced abdominopelvic magnetic resonance imaging studies performed for pediatric right lower quadrant abdominal pain.

Authors:  David M Sawyer; Raza Mushtaq; Srinivasan Vedantham; Faryal Shareef; Sara M Desoky; Hina Arif-Tiwari; Dorothy L Gilbertson-Dahdal; Unni K Udayasankar
Journal:  Pediatr Radiol       Date:  2021-03-10

7.  Deep Learning-Based Natural Language Processing in Radiology: The Impact of Report Complexity, Disease Prevalence, Dataset Size, and Algorithm Type on Model Performance.

Authors:  A W Olthof; P M A van Ooijen; L J Cornelissen
Journal:  J Med Syst       Date:  2021-09-04       Impact factor: 4.460

8.  [Analysis of the Rate of Discrepancy between Preliminary Reports by Radiology Residents and Final Reports by Certified Radiologists for Emergency Radiology Studies in a University Hospital].

Authors:  Younbeom Jeong; Cheong-Il Shin; Hwan Jun Jae; Jung Hoon Kim; Jin Wook Chung
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2021-06-16
  8 in total

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