Discordance Between Intraoperative Consultation by Frozen Section and Final Diagnosis: A Classification Model to Guide Quality Improvement

被引:21
作者
Sams, Sharon B. [1 ]
Wisell, Joshua A. [1 ]
机构
[1] Univ Colorado Denver, Aurora, CO USA
关键词
frozen section; quality assurance; quality improvement; PATHOLOGISTS Q-PROBES; SURGICAL PATHOLOGY; INSTITUTIONS; HOSPITALS; ACCURACY; ERRORS;
D O I
10.1177/1066896916662152
中图分类号
R36 [病理学];
学科分类号
100104 ;
摘要
Discrepancies between intraoperative consultations with frozen section diagnosis and the final pathology report have the potential to alter treatment decisions and affect patient care. Monitoring these correlations is a key component of laboratory quality assurance, however identifying specific areas for improvement can be difficult to attain. Our goal is to develop a standardized method utilizing root cause analysis and a modified Eindhoven classification schematic to identify the source of discrepancies and deferrals and subsequently to guide performance improvement initiatives. A retrospective review of intraoperative consultations performed at a tertiary level hospital and cancer center over a 6-month period identified deferrals and discrepancies between the intraoperative consult report and the final pathology report. We developed and applied a classification tool to identify the process errors and cognitive errors leading to discrepant results. A total of 48 (4.6%) discrepancies and 24 (2.3%) deferrals were identified from the 1042 frozen sections. Within the entire data set of frozen sections, the process errors (n = 26, 54.2%) were due to gross sampling (n = 16, 33.3%), histologic sampling (n = 8, 16.7%), and surgical sampling (n = 2, 4.2%). Interpretation errors (n = 22, 45.8%) included undercalls/false negatives (n=8, 16.7%), overcalls/false positives (n = 10, 20.8%), and misclassification errors (n = 4, 8.3%). Application of our classification tool demonstrated that the root cause of discrepancies and deferrals varied both between organ systems and by specific organs and that classification models may be utilized as a standardized method to identify focused areas for improvement.
引用
收藏
页码:41 / 50
页数:10
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