Literature DB >> 21997979

Informatics in radiology: Measuring and improving quality in radiology: meeting the challenge with informatics.

Daniel L Rubin1.   

Abstract

Quality is becoming a critical issue for radiology. Measuring and improving quality is essential not only to ensure optimum effectiveness of care and comply with increasing regulatory requirements, but also to combat current trends leading to commoditization of radiology services. A key challenge to implementing quality improvement programs is to develop methods to collect knowledge related to quality care and to deliver that knowledge to practitioners at the point of care. There are many dimensions to quality in radiology that need to be measured, monitored, and improved, including examination appropriateness, procedure protocol, accuracy of interpretation, communication of imaging results, and measuring and monitoring performance improvement in quality, safety, and efficiency. Informatics provides the key technologies that can enable radiologists to measure and improve quality. However, few institutions recognize the opportunities that informatics methods provide to improve safety and quality. The information technology infrastructure in most hospitals is limited, and they have suboptimal adoption of informatics techniques. Institutions can tackle the challenges of assessing and improving quality in radiology by means of informatics.

Mesh:

Year:  2011        PMID: 21997979     DOI: 10.1148/rg.316105207

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  9 in total

1.  Online Error Reporting for Managing Quality Control Within Radiology.

Authors:  Pedram Golnari; Daniel Forsberg; Beverly Rosipko; Jeffrey L Sunshine
Journal:  J Digit Imaging       Date:  2016-06       Impact factor: 4.056

2.  Dose estimation of ultra-low-dose chest CT to different sized adult patients.

Authors:  Tony M Svahn; Tommy Sjöberg; Jennifer C Ast
Journal:  Eur Radiol       Date:  2018-12-17       Impact factor: 5.315

3.  Detecting Technical Image Quality in Radiology Reports.

Authors:  Thusitha Mabotuwana; Varun S Bhandarkar; Christopher S Hall; Martin L Gunn
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

4.  [No exchange of information without technology : modern infrastructure in radiology].

Authors:  H Hupperts; K-G A Hermann
Journal:  Radiologe       Date:  2014-01       Impact factor: 0.635

Review 5.  The Enterprise Imaging Value Proposition.

Authors:  Cheryl A Petersilge
Journal:  J Digit Imaging       Date:  2020-02       Impact factor: 4.056

Review 6.  Building for tomorrow today: opportunities and directions in radiology resident research.

Authors:  John-Paul J Yu; Akash P Kansagra; Ashesh Thaker; Andrew Colucci; Steven J Sherry; Rathan M Subramaniam
Journal:  Acad Radiol       Date:  2014-10-14       Impact factor: 3.173

7.  Collaborative Development of a PACS-Integrated Quality Control Dashboard: a Single Institutional Experience.

Authors:  Jonathan D Pierce; Vijaya Kosaraju; Beverly Rosipko; Jeffrey L Sunshine; Ian Judd; Jennifer Sommer
Journal:  J Digit Imaging       Date:  2022-04-20       Impact factor: 4.903

8.  Using automatically extracted information from mammography reports for decision-support.

Authors:  Selen Bozkurt; Francisco Gimenez; Elizabeth S Burnside; Kemal H Gulkesen; Daniel L Rubin
Journal:  J Biomed Inform       Date:  2016-07-04       Impact factor: 6.317

9.  A holistic overview of deep learning approach in medical imaging.

Authors:  Rammah Yousef; Gaurav Gupta; Nabhan Yousef; Manju Khari
Journal:  Multimed Syst       Date:  2022-01-21       Impact factor: 2.603

  9 in total

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