Diagnostic errors in uncommon conditions: a systematic review of case reports of diagnostic errors.

IF 2.2 Q2 MEDICINE, GENERAL & INTERNAL
Diagnosis Pub Date : 2023-08-10 eCollection Date: 2023-11-01 DOI:10.1515/dx-2023-0030
Yukinori Harada, Takashi Watari, Hiroyuki Nagano, Tomoharu Suzuki, Kotaro Kunitomo, Taiju Miyagami, Tetsuro Aita, Kosuke Ishizuka, Mika Maebashi, Taku Harada, Tetsu Sakamoto, Shusaku Tomiyama, Taro Shimizu
{"title":"Diagnostic errors in uncommon conditions: a systematic review of case reports of diagnostic errors.","authors":"Yukinori Harada, Takashi Watari, Hiroyuki Nagano, Tomoharu Suzuki, Kotaro Kunitomo, Taiju Miyagami, Tetsuro Aita, Kosuke Ishizuka, Mika Maebashi, Taku Harada, Tetsu Sakamoto, Shusaku Tomiyama, Taro Shimizu","doi":"10.1515/dx-2023-0030","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>To assess the usefulness of case reports as sources for research on diagnostic errors in uncommon diseases and atypical presentations.</p><p><strong>Content: </strong>We reviewed 563 case reports of diagnostic error. The commonality of the final diagnoses was classified based on the description in the articles, Orphanet, or epidemiological data on available references; the typicality of presentation was classified based on the description in the articles and the judgment of the physician researchers. Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC), and Generic Diagnostic Pitfalls (GDP) taxonomies were used to assess the factors contributing to diagnostic errors.</p><p><strong>Summary and outlook: </strong>Excluding three cases in that commonality could not be classified, 560 cases were classified into four categories: typical presentations of common diseases (60, 10.7 %), atypical presentations of common diseases (35, 6.2 %), typical presentations of uncommon diseases (276, 49.3 %), and atypical presentations of uncommon diseases (189, 33.8 %). The most important DEER taxonomy was \"Failure/delay in considering the diagnosis\" among the four categories, whereas the most important RDC and GDP taxonomies varied with the categories. Case reports can be a useful data source for research on the diagnostic errors of uncommon diseases with or without atypical presentations.</p>","PeriodicalId":11273,"journal":{"name":"Diagnosis","volume":" ","pages":"329-336"},"PeriodicalIF":2.2000,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diagnosis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/dx-2023-0030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/11/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0

Abstract

Objectives: To assess the usefulness of case reports as sources for research on diagnostic errors in uncommon diseases and atypical presentations.

Content: We reviewed 563 case reports of diagnostic error. The commonality of the final diagnoses was classified based on the description in the articles, Orphanet, or epidemiological data on available references; the typicality of presentation was classified based on the description in the articles and the judgment of the physician researchers. Diagnosis Error Evaluation and Research (DEER), Reliable Diagnosis Challenges (RDC), and Generic Diagnostic Pitfalls (GDP) taxonomies were used to assess the factors contributing to diagnostic errors.

Summary and outlook: Excluding three cases in that commonality could not be classified, 560 cases were classified into four categories: typical presentations of common diseases (60, 10.7 %), atypical presentations of common diseases (35, 6.2 %), typical presentations of uncommon diseases (276, 49.3 %), and atypical presentations of uncommon diseases (189, 33.8 %). The most important DEER taxonomy was "Failure/delay in considering the diagnosis" among the four categories, whereas the most important RDC and GDP taxonomies varied with the categories. Case reports can be a useful data source for research on the diagnostic errors of uncommon diseases with or without atypical presentations.

罕见情况下的诊断错误:对诊断错误病例报告的系统回顾。
目的:评估病例报告作为研究罕见疾病和非典型表现诊断错误的来源的有用性。内容:我们回顾了563例诊断错误报告。最终诊断的共性根据文献描述、孤儿院或现有参考文献的流行病学数据进行分类;根据文献的描述和医师研究者的判断,对表现的典型性进行分类。诊断错误评估与研究(DEER)、可靠诊断挑战(RDC)和通用诊断缺陷(GDP)分类法用于评估导致诊断错误的因素。总结与展望:560例病例除3例共性不能分的病例外,共分为典型常见病(60例,10.7 %)、不典型常见病(35例,6.2 %)、典型不常见病(276例,49.3 %)、不典型不常见病(189例,33.8 %)四类。在4个分类中,最重要的分类是“失败/延迟考虑诊断”,而最重要的RDC和GDP分类因类别而异。病例报告可作为研究具有或不具有非典型表现的罕见疾病的诊断错误的有用数据源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Diagnosis
Diagnosis MEDICINE, GENERAL & INTERNAL-
CiteScore
7.20
自引率
5.70%
发文量
41
期刊介绍: Diagnosis focuses on how diagnosis can be advanced, how it is taught, and how and why it can fail, leading to diagnostic errors. The journal welcomes both fundamental and applied works, improvement initiatives, opinions, and debates to encourage new thinking on improving this critical aspect of healthcare quality.  Topics: -Factors that promote diagnostic quality and safety -Clinical reasoning -Diagnostic errors in medicine -The factors that contribute to diagnostic error: human factors, cognitive issues, and system-related breakdowns -Improving the value of diagnosis – eliminating waste and unnecessary testing -How culture and removing blame promote awareness of diagnostic errors -Training and education related to clinical reasoning and diagnostic skills -Advances in laboratory testing and imaging that improve diagnostic capability -Local, national and international initiatives to reduce diagnostic error
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信