Advertisement

Quantifying Analysis of Uncertainty in Medical Reporting: Creation of User and Context-Specific Uncertainty Profiles

Article

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.

Keywords

Uncertainty Data mining Profiling Outcomes analysis 

References

  1. 1.
    Carney PA, Yi JP, Abraham LA et al.: Reactions to uncertainty and the accuracy of diagnostic mammography. J Gen Intern Med 22:234–241, 2007CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Wang SY, Chan WP: Uncertainty and its consequences in clinical practice. J Korean Med Sci 30:1710–1712, 2015CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Reiner B: Quantitative analysis of uncertainty in medical reporting. J Digit Imaging 2017 (Submitted for publication)Google Scholar
  4. 4.
    Woodhams J, Toye K: An empirical test of the assumptions of case linkage and offender profiling with serial commercial robberies. Psychology, Public Policy, and Law 13:59–85, 2007CrossRefGoogle Scholar
  5. 5.
    Argamon S, Koppel M: A systematic functional approach to automated authorship analysis. Journal of law and Policy 21:299–316, 2013Google Scholar
  6. 6.
    Van Halteren H: Linguistic profiling for authorship recognition and verification. In: Proceedings of the 42nd conference of the ACL. East Stroudsburg: PA:ACL, pp. 199–206Google Scholar
  7. 7.
    Douglas JE, Burgess AE: Criminal profiling: a viable investigative tool against violent crime. FBL Law Enforcement Bulletin 55:9–13, 1986Google Scholar
  8. 8.
    Reiner B: Contextualizing causation of uncertainty in medical reporting. J Am Coll Radiol 2017 (in press)Google Scholar

Copyright information

© Society for Imaging Informatics in Medicine 2018

Authors and Affiliations

  1. 1.Maryland VA Healthcare SystemBaltimoreUSA

Personalised recommendations