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Quantifying Analysis of Uncertainty in Medical Reporting: Creation of User and Context-Specific Uncertainty Profiles.
- Source :
-
Journal of digital imaging [J Digit Imaging] 2018 Aug; Vol. 31 (4), pp. 379-382. - Publication Year :
- 2018
-
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.
- Subjects :
- Data Mining
Delivery of Health Care standards
Delivery of Health Care trends
Female
Humans
Male
Practice Patterns, Physicians' trends
Radiology trends
Research Design trends
Risk Assessment
United States
Outcome Assessment, Health Care
Practice Patterns, Physicians' standards
Radiology standards
Research Design standards
Uncertainty
Subjects
Details
- Language :
- English
- ISSN :
- 1618-727X
- Volume :
- 31
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Journal of digital imaging
- Publication Type :
- Academic Journal
- Accession number :
- 29427140
- Full Text :
- https://doi.org/10.1007/s10278-018-0057-z