Today's advanced imaging modalities are acquiring more and more images that must be interpreted in less time. Concerns have been raised that radiologist workloads are so demanding that fatigue and reduced time for interpretation are negatively impacting diagnostic accuracy. Inadequate knowledge about the frequency, cause and impact of errors, as well as effective methods for error prevention is a major obstacle for improving health care quality. The failure to report abnormal radiographic findings accounts for about half the errors made. Avoiding false- negative errors is critical - with such errors treatmen does not occur. In the previous funding period we demonstrated that fatigue significantly reduces detection accuracy in simple detection tasks and that oculomotor strain is a contributing factor. The goal of the proposed research is to determine whether cognitive fatigue can more accurately and fully account for increases in errors in complex radiologic decision tasks. The long-term goal is to reduce diagnostic errors by studying an obvious but serious problem, fatigue, to determine whether it is indeed a root cause of error. This research will address the problem by applying comprehensive measures of cognitive fatigue and determining whether they generate diagnostic errors. At the end of the project, we will understand the influence of cognitive fatigue on diagnostic accuracy, which will help us in our general goal of reducing diagnostic errors thereby improving patient care. Our overall hypothesis is that the current practice of radiology produces cognitive fatigue that reduces diagnostic accuracy. Progress in understanding the causes of error in diagnostic radiology has been achieved by experiments focusing on error-prone situations such as Satisfaction of Search (SOS), but to date the role of fatigue in SOS has yet to be examined and thus the first aim will discover ways to help radiologists obviate SOS errors by testing whether cognitive fatigue exacerbates the SOS phenomenon. Our second and third aims relate cognitive fatigue to radiological performance using two types of complex imaging tasks studied before and after long hours of image interpretation work. The accuracy and efficiency of radiologist's reports will be analyzed and correlated with measures of cognitive fatigue.

Public Health Relevance

Concerns have been raised that radiologist workloads are so demanding that fatigue is leading to increased error rates and missed opportunities for early treatment. Inadequate knowledge about the frequency, cause and impact of errors, as well as effective methods for error prevention is a major obstacle for improving health care quality. The goal of the proposed research is to determine whether cognitive fatigue can more accurately and fully account for increases in errors in complex radiologic decision tasks.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
2R01EB004987-05A1
Application #
8573836
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Pai, Vinay Manjunath
Project Start
2005-07-01
Project End
2017-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
5
Fiscal Year
2013
Total Cost
$340,465
Indirect Cost
$73,669
Name
University of Arizona
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
806345617
City
Tucson
State
AZ
Country
United States
Zip Code
85721
Krupinski, Elizabeth A; Berbaum, Kevin S; Caldwell, Robert T et al. (2010) Long radiology workdays reduce detection and accommodation accuracy. J Am Coll Radiol 7:698-704
Krupinski, Elizabeth A (2010) Current perspectives in medical image perception. Atten Percept Psychophys 72:1205-17
Krupinski, Elizabeth A; Berbaum, Kevin S (2009) Measurement of visual strain in radiologists. Acad Radiol 16:947-50
Krupinski, Elizabeth A (2009) Virtual slide telepathology workstation-of-the-future: lessons learned from teleradiology. Semin Diagn Pathol 26:194-205
Krupinski, Elizabeth A (2009) Virtual slide telepathology workstation of the future: lessons learned from teleradiology. Hum Pathol 40:1100-11
Krupinski, Elizabeth A; Jiang, Yulei (2008) Anniversary paper: evaluation of medical imaging systems. Med Phys 35:645-59