Literature DB >> 17579143

Computed radiography dose data mining and surveillance as an ongoing quality assurance improvement process.

Brent K Stewart1, Kalpana M Kanal, James R Perdue, Frederick A Mann.   

Abstract

OBJECTIVE: A data-mining program extracts computed radiography (CR) sensitivity-number (S-number) information from the PACS at our institution on a monthly basis as an ongoing quality assurance (QA) improvement project. These data are compared with the previous month's data and departmental S-number goals. The results are presented at monthly QA meetings. The S-number trends are then used by technologists to modify radiographic technique charts to reach the departmental S-number target range goals.
CONCLUSION: This cyclic QA improvement process shows that mining PACS data can be useful in reducing patient radiation dose and interexamination dose variance.

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Year:  2007        PMID: 17579143     DOI: 10.2214/AJR.06.1232

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  3 in total

1.  Normalizing Heterogeneous Medical Imaging Data to Measure the Impact of Radiation Dose.

Authors:  Luís A Bastião Silva; Luís S Ribeiro; Milton Santos; Nuno Neves; Dulce Francisco; Carlos Costa; José Luis Oliveira
Journal:  J Digit Imaging       Date:  2015-12       Impact factor: 4.056

2.  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

3.  Implementation of a patient dose monitoring system in conventional digital X-ray imaging: initial experiences.

Authors:  Christina Heilmaier; Niklaus Zuber; Dominik Weishaupt
Journal:  Eur Radiol       Date:  2016-06-23       Impact factor: 5.315

  3 in total

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