Paul D Frederick1, Heidi D Nelson2, Patricia A Carney3, Tad T Brunyé4, Kimberly H Allison5, Donald L Weaver6, Joann G Elmore1. 1. Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA (PDF, JGE). 2. Providence Cancer Center, Providence Health and Services Oregon, and Departments of Medical Informatics and Clinical Epidemiology and Medicine, Oregon Health & Science University, Portland, OR, USA (HDN). 3. Department of Family Medicine, Oregon Health & Science University, Portland, OR, USA (PAC). 4. Center for Applied Brain & Cognitive Sciences, Tufts University, Medford, MA, USA (TTB). 5. Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA (KHA). 6. Department of Pathology, University of Vermont and UVM Cancer Center, Burlington, VT, USA (DLW).
Abstract
BACKGROUND: Medical decision making may be influenced by contextual factors. We evaluated whether pathologists are influenced by disease severity of recently observed cases. METHODS:Pathologists independently interpreted 60 breast biopsy specimens (one slide per case; 240 total cases in the study) in a prospective randomized observational study. Pathologists interpreted the same cases in 2 phases, separated by a washout period of >6 months. Participants were not informed that the cases were identical in each phase, and the sequence was reordered randomly for each pathologist and between phases. A consensus reference diagnosis was established for each case by 3 experienced breast pathologists. Ordered logit models examined the effect the pathologists' diagnoses on the preceding case or the 5 preceding cases had on their diagnosis for the subsequent index case. RESULTS: Among 152 pathologists, 49 provided interpretive data in both phases I and II, 66 from only phase I, and 37 from phase II only. In phase I, pathologists were more likely to indicate a more severe diagnosis than the reference diagnosis when the preceding case was diagnosed as ductal carcinoma in situ (DCIS) or invasive cancer (proportional odds ratio [POR], 1.28; 95% confidence interval [CI], 1.15-1.42). Results were similar when considering the preceding 5 cases and for the pathologists in phase II who interpreted the same cases in a different order compared with phase I (POR, 1.17; 95% CI, 1.05-1.31). CONCLUSION: Physicians appear to be influenced by the severity of previously interpreted test cases. Understanding types and sources of diagnostic bias may lead to improved assessment of accuracy and better patient care.
RCT Entities:
BACKGROUND: Medical decision making may be influenced by contextual factors. We evaluated whether pathologists are influenced by disease severity of recently observed cases. METHODS: Pathologists independently interpreted 60 breast biopsy specimens (one slide per case; 240 total cases in the study) in a prospective randomized observational study. Pathologists interpreted the same cases in 2 phases, separated by a washout period of >6 months. Participants were not informed that the cases were identical in each phase, and the sequence was reordered randomly for each pathologist and between phases. A consensus reference diagnosis was established for each case by 3 experienced breast pathologists. Ordered logit models examined the effect the pathologists' diagnoses on the preceding case or the 5 preceding cases had on their diagnosis for the subsequent index case. RESULTS: Among 152 pathologists, 49 provided interpretive data in both phases I and II, 66 from only phase I, and 37 from phase II only. In phase I, pathologists were more likely to indicate a more severe diagnosis than the reference diagnosis when the preceding case was diagnosed as ductal carcinoma in situ (DCIS) or invasive cancer (proportional odds ratio [POR], 1.28; 95% confidence interval [CI], 1.15-1.42). Results were similar when considering the preceding 5 cases and for the pathologists in phase II who interpreted the same cases in a different order compared with phase I (POR, 1.17; 95% CI, 1.05-1.31). CONCLUSION: Physicians appear to be influenced by the severity of previously interpreted test cases. Understanding types and sources of diagnostic bias may lead to improved assessment of accuracy and better patient care.
Authors: Joann G Elmore; Gary M Longton; Patricia A Carney; Berta M Geller; Tracy Onega; Anna N A Tosteson; Heidi D Nelson; Margaret S Pepe; Kimberly H Allison; Stuart J Schnitt; Frances P O'Malley; Donald L Weaver Journal: JAMA Date: 2015-03-17 Impact factor: 56.272
Authors: Kimberly H Allison; Lisa M Reisch; Patricia A Carney; Donald L Weaver; Stuart J Schnitt; Frances P O'Malley; Berta M Geller; Joann G Elmore Journal: Histopathology Date: 2014-04-02 Impact factor: 5.087
Authors: Famke Aeffner; Hibret A Adissu; Michael C Boyle; Robert D Cardiff; Erik Hagendorn; Mark J Hoenerhoff; Robert Klopfleisch; Susan Newbigging; Dirk Schaudien; Oliver Turner; Kristin Wilson Journal: ILAR J Date: 2018-12-01