| Title |
Quantifying Analysis of Uncertainty in Medical Reporting: Creation of User and Context-Specific Uncertainty Profiles
|
|---|---|
| Published in |
Journal of Imaging Informatics in Medicine, February 2018
|
| DOI | 10.1007/s10278-018-0057-z |
| Pubmed ID | |
| Authors |
Bruce I. Reiner |
| Abstract |
While uncertainty is ubiquitous in medical practice, minimal work to date has been performed to analyze the cause and effect relationship between uncertainty and patient outcomes. In medical imaging practice, uncertainty in the radiology report has been well documented to be a source of clinician dissatisfaction. Before one can effectively create intervention strategies aimed at reducing uncertainty, it must first be better understood through context- and user-specific analysis. One strategy for accomplishing this task is to characterize the source of uncertainty and create user-specific uncertainty profiles which take into account a number of provider-specific variables which may contribute to report uncertainty. The resulting data can in turn be used to create real-time report uncertainty metrics aimed at providing uncertainty analytics at the point of care, for the combined purposes of decision support, improved communication, and enhanced clinical/economic outcomes. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 2 | 17% |
| Student > Master | 2 | 17% |
| Student > Postgraduate | 1 | 8% |
| Student > Ph. D. Student | 1 | 8% |
| Unknown | 6 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 17% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Economics, Econometrics and Finance | 1 | 8% |
| Computer Science | 1 | 8% |
| Unknown | 7 | 58% |
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 14 February 2018.
All research outputs
#22,979,729
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Outputs from Journal of Imaging Informatics in Medicine
#100
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#393,723
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Outputs of similar age from Journal of Imaging Informatics in Medicine
#1
of 1 outputs
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