Literature DB >> 18270779

Maintaining quality control using a radiological digital X-ray dashboard.

Todd R Minnigh1, Jacqueline Gallet.   

Abstract

Repeats are indicators for the quality-imaging manager to schedule additional training and to be used as a basis for dialog with the reading radiologists to improve the service and quality to patients and referring physicians. Through the thoughtful application of software and networking, dose management, X-ray usage, and repeat analysis data can be made available centrally. This provides clinically useful technologist-centric results greatly benefiting an enterprise. This study tracked a radiology department's use of a digital X-ray dashboard software application. It was discovered that 80% of the exams were performed by only 21% of the technologists and that the technologist with the highest throughput had a personal repeat rate of 6.5% compared to the department average of 7.6%. This study indicated that useful information could be derived and used as a basis for improving the radiology department's operations and in maintaining high quality standards.

Entities:  

Mesh:

Year:  2008        PMID: 18270779      PMCID: PMC3043675          DOI: 10.1007/s10278-007-9098-4

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  15 in total

1.  SCAR Radiologic Technologist Survey: analysis of the impact of digital technologies on productivity.

Authors:  Bruce I Reiner; Eliot L Siegel; John A Carrino; Mitchell M Goldburgh
Journal:  J Digit Imaging       Date:  2002-12-17       Impact factor: 4.056

2.  An annual strategy for total quality.

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Journal:  Radiol Manage       Date:  1992

3.  An analysis of radiographic repeat and reject rates.

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Journal:  Radiol Technol       Date:  1992 May-Jun

4.  Digital repeat analysis; setup and operation.

Authors:  J Nol; G Isouard; J Mirecki
Journal:  J Digit Imaging       Date:  2006-06       Impact factor: 4.056

5.  Quality management in radiology: historical aspects and basic definitions.

Authors:  Sukru Mehmet Erturk; Silvia Ondategui-Parra; Pablo R Ros
Journal:  J Am Coll Radiol       Date:  2005-12       Impact factor: 5.532

6.  Effect of film-based versus filmless operation on the productivity of CT technologists.

Authors:  B I Reiner; E L Siegel; F J Hooper; D Glasser
Journal:  Radiology       Date:  1998-05       Impact factor: 11.105

7.  Continuing reject-repeat film analysis program.

Authors:  G Gadeholt; J T Geitung; J H Göthlin; T Asp
Journal:  Eur J Radiol       Date:  1989-08       Impact factor: 3.528

8.  Reject analysis: its role in quality assurance.

Authors:  S Watkinson; B M Moores; S J Hill
Journal:  Radiography       Date:  1984 Sep-Oct

9.  Six Sigma: not for the faint of heart.

Authors:  Anthony R Benedetto
Journal:  Radiol Manage       Date:  2003 Mar-Apr

10.  Analog to digital workflow improvement: a quantitative study.

Authors:  Catherine Wideman; Jacqueline Gallet
Journal:  J Digit Imaging       Date:  2006       Impact factor: 4.056

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  7 in total

1.  Using PACS audit data for process improvement.

Authors:  William Bill Gregg; Mark Randolph; Denise H Brown; Tommy Lyles; Sharrow Dinnia Smith; Horacio D'Agostino
Journal:  J Digit Imaging       Date:  2010-12       Impact factor: 4.056

2.  Investigation of the variability in the assessment of digital chest X-ray image quality.

Authors:  Jacquelyn S Whaley; Barry D Pressman; Jonathan R Wilson; Lionel Bravo; William J Sehnert; David H Foos
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

3.  From Information Management to Information Visualization: Development of Radiology Dashboards.

Authors:  Mahtab Karami; Reza Safdari
Journal:  Appl Clin Inform       Date:  2016-05-11       Impact factor: 2.342

4.  Emergency Department Quality Dashboard; a Systematic Review of Performance Indicators, Functionalities, and Challenges.

Authors:  Sohrab Almasi; Reza Rabiei; Hamid Moghaddasi; Mojtaba Vahidi-Asl
Journal:  Arch Acad Emerg Med       Date:  2021-06-17

5.  One year's results from a server-based system for performing reject analysis and exposure analysis in computed radiography.

Authors:  A Kyle Jones; Raimund Polman; Charles E Willis; S Jeff Shepard
Journal:  J Digit Imaging       Date:  2011-04       Impact factor: 4.056

6.  Optimizing the pathology workstation "cockpit": Challenges and solutions.

Authors:  Elizabeth A Krupinski
Journal:  J Pathol Inform       Date:  2010-10-01

7.  Reject rate analysis in digital radiography: an Australian emergency imaging department case study.

Authors:  Samantha Atkinson; Michael Neep; Deborah Starkey
Journal:  J Med Radiat Sci       Date:  2019-07-18
  7 in total

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