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Systematic Layout Planning of a Radiology Reporting Area to Optimize Radiologists’ Performance

Overview of attention for article published in Journal of Digital Imaging, November 2017
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Title
Systematic Layout Planning of a Radiology Reporting Area to Optimize Radiologists’ Performance
Published in
Journal of Digital Imaging, November 2017
DOI 10.1007/s10278-017-0036-9
Pubmed ID
Authors

Guilherme Brittes Benitez, Flavio Sanson Fogliatto, Ricardo Bertoglio Cardoso, Felipe Soares Torres, Carlo Sasso Faccin, José Miguel Dora

Abstract

Optimizing radiologists' performance is a major priority for managers of health services/systems, since the radiologists' reporting activity imposes a severe constraint on radiology productivity. Despite that, methods to optimize radiologists' reporting workplace layout are scarce in the literature. This study was performed in the Radiology Division (RD) of an 850-bed University-based general hospital. The analysis of the reporting workplace layout was carried out using the systematic layout planning (SLP) method, in association with cluster analysis as a complementary tool in early stages of SLP. Radiologists, architects, and hospital managers were the stakeholders consulted for the completion of different stages of the layout planning process. A step-by-step description of the proposed methodology to plan an RD reporting layout is presented. Clusters of radiologists were defined using types of exams reported and their frequency of occurrence as clustering variables. Sectors with high degree of interaction were placed in proximity in the new RD layout, with separation of noisy and quiet areas. Four reporting cells were positioned in the quiet area, grouping radiologists by subspecialty, as follows: cluster 1-abdomen; cluster 2-musculoskeletal; cluster 3-neurological, vascular and head & neck; cluster 4-thoracic and cardiac. The creation of reporting cells has the potential to limit unplanned interruptions and enhance the exchange of knowledge and information within cells, joining radiologists with the same expertise. That should lead to improvements in productivity, allowing managers to more easily monitor radiologists' performance.

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Geographical breakdown

Country Count As %
Unknown 100 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 19 19%
Student > Master 15 15%
Student > Ph. D. Student 6 6%
Professor 6 6%
Student > Doctoral Student 5 5%
Other 14 14%
Unknown 35 35%
Readers by discipline Count As %
Engineering 33 33%
Medicine and Dentistry 6 6%
Computer Science 4 4%
Design 4 4%
Social Sciences 3 3%
Other 11 11%
Unknown 39 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 December 2017.
All research outputs
#20,453,782
of 23,009,818 outputs
Outputs from Journal of Digital Imaging
#941
of 1,061 outputs
Outputs of similar age
#373,477
of 438,547 outputs
Outputs of similar age from Journal of Digital Imaging
#14
of 18 outputs
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So far Altmetric has tracked 1,061 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.