Pathology and Laboratory Medicine, University of Rochester Medical Center, Rochester, NY, USA.
Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA.
Diagnosis (Berl). 2023 Oct 5;10(4):375-382. doi: 10.1515/dx-2023-0010. eCollection 2023 Nov 1.
Current autopsy practice guidelines do not provide a mechanism to identify potential causes of diagnostic error (DE). We used our autopsy data registry to ask if gender or race were related to the frequency of diagnostic error found at autopsy.
Our autopsy reports include International Classification of Diseases (ICD) 9 or ICD 10 diagnostic codes for major diagnoses as well as codes that identify types of error. From 2012 to mid-2015 only 2 codes were used: UNDOC (major undocumented diagnoses) and UNCON (major unconfirmed diagnoses). Major diagnoses contributed to death or would have been treated if known. Since mid-2015, codes included specific diagnoses, i.e. undiagnosed or unconfirmed myocardial infarction, infection, pulmonary thromboembolism, malignancy, or other diagnosis as well as cause of death. Adult autopsy cases from 2012 to 2019 were assessed for DE associated with reported sex or race (nonwhite or white). 528 cases were evaluated between 2012 and 2015 and 699 between 2015 and 2019.
Major DEs were identified at autopsy in 65.9 % of cases from 2012 to 2015 and in 72.1 % from 2015 to 2019. From 2012 to 2015, female autopsy cases showed a greater frequency in 4 parameters of DE, i.e., in the total number of cases with any error (p=0.0001), in the number of cases with UNDOC errors (p=0.0038) or UNCON errors (p=0.0006), and in the relative proportions of total numbers of errors (p=0.0001). From 2015 to 2019 undocumented malignancy was greater among males (p=0.0065); no other sex-related error was identified. In the same period some DE parameters were greater among nonwhite than among white subjects, including unconfirmed cause of death (p=0.035), and proportion of total error diagnoses (p=0.0003), UNCON diagnoses (p=0.0093), and UNDOC diagnoses (p=0.035).
Coding for DE at autopsy can identify potential effects of biases on diagnostic error.
现行尸检实践指南并未提供识别诊断错误（DE）潜在原因的机制。我们利用尸检数据登记系统，询问性别或种族是否与尸检时发现的 DE 频率有关。
我们的尸检报告包括国际疾病分类（ICD）第 9 或第 10 版主要诊断的诊断代码，以及确定错误类型的代码。从 2012 年到 2015 年年中，仅使用了 2 个代码：未记录的主要诊断（UNDOC）和未确认的主要诊断（UNCON）。主要诊断导致死亡或已知情况下会进行治疗。自 2015 年年中以来，代码包括特定诊断，即未诊断或未确认的心肌梗死、感染、肺血栓栓塞、恶性肿瘤或其他诊断以及死亡原因。评估了 2012 年至 2019 年的成人尸检病例，以评估与报告的性别或种族（非白人或白人）相关的 DE。在 2012 年至 2015 年期间评估了 528 例病例，在 2015 年至 2019 年期间评估了 699 例病例。
2012 年至 2015 年期间，尸检中发现主要 DE 的比例为 65.9%，而 2015 年至 2019 年期间为 72.1%。在 2012 年至 2015 年期间，女性尸检病例在 4 个 DE 参数中显示出更高的频率，即任何错误病例总数（p=0.0001）、未记录错误病例数（p=0.0038）或未确认错误病例数（p=0.0006），以及总错误数量的相对比例（p=0.0001）。在 2015 年至 2019 年期间，男性未记录的恶性肿瘤更多（p=0.0065）；未发现其他与性别相关的错误。同期，一些 DE 参数在非白人中高于白人，包括未确认的死因（p=0.035）、总错误诊断比例（p=0.0003）、未确认诊断（p=0.0093）和未记录诊断（p=0.035）。
尸检中 DE 的编码可以识别诊断错误潜在偏倚的影响。
