Department of Public and Occupational Health, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Quality of Care, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
BMJ Qual Saf. 2024 Sep 19;33(10):642-651. doi: 10.1136/bmjqs-2022-015876.
Although diagnostic errors have gained renewed focus within the patient safety domain, measuring them remains a challenge. They are often measured using methods that lack information on decision-making processes given by involved physicians (eg, record reviews). The current study analyses serious adverse event (SAE) reports from Dutch hospitals to identify common contributing factors of diagnostic errors in hospital medicine. These reports are the results of thorough investigations by highly trained, independent hospital committees into the causes of SAEs. The reports include information from involved healthcare professionals and patients or family obtained through interviews.
All 71 Dutch hospitals were invited to participate in this study. Participating hospitals were asked to send four diagnostic SAE reports of their hospital. Researchers applied the Safer Dx Instrument, a Generic Analysis Framework, the Diagnostic Error Evaluation and Research (DEER) taxonomy and the Eindhoven Classification Model (ECM) to analyse reports.
Thirty-one hospitals submitted 109 eligible reports. Diagnostic errors most often occurred in the diagnostic testing, assessment and follow-up phases according to the DEER taxonomy. The ECM showed human errors as the most common contributing factor, especially relating to communication of results, task planning and execution, and knowledge. Combining the most common DEER subcategories and the most common ECM classes showed that clinical reasoning errors resulted from failures in knowledge, and task planning and execution. Follow-up errors and errors with communication of test results resulted from failures in coordination and monitoring, often accompanied by usability issues in electronic health record design and missing protocols.
Diagnostic errors occurred in every hospital type, in different specialties and with different care teams. While clinical reasoning errors remain a common problem, often caused by knowledge and skill gaps, other frequent errors in communication of test results and follow-up require different improvement measures (eg, improving technological systems).
尽管诊断错误在患者安全领域重新引起了关注，但衡量这些错误仍然具有挑战性。它们通常使用缺乏相关医生决策过程信息的方法进行衡量（例如，记录审查）。本研究分析了荷兰医院的严重不良事件（SAE）报告，以确定医院医学中诊断错误的常见促成因素。这些报告是经过高度训练、独立的医院委员会对 SAE 原因进行彻底调查的结果。报告包括通过访谈从涉及的医疗保健专业人员和患者或家属获得的信息。
邀请所有 71 家荷兰医院参加这项研究。要求参与医院发送他们医院的四份诊断性 SAE 报告。研究人员应用了 Safer Dx Instrument、Generic Analysis Framework、Diagnostic Error Evaluation and Research (DEER) 分类法和 Eindhoven Classification Model (ECM) 来分析报告。
31 家医院提交了 109 份符合条件的报告。根据 DEER 分类法，诊断错误最常发生在诊断测试、评估和随访阶段。ECM 显示人为错误是最常见的促成因素，特别是与结果沟通、任务规划和执行以及知识相关。将最常见的 DEER 子类别和最常见的 ECM 类别结合起来表明，临床推理错误源于知识、任务规划和执行方面的失败。随访错误和测试结果沟通错误源于协调和监测方面的失败，通常伴随着电子病历设计中的可用性问题和缺少协议。
诊断错误发生在每种医院类型、不同专业和不同护理团队中。虽然临床推理错误仍然是一个常见问题，通常是由于知识和技能差距造成的，但沟通测试结果和随访方面的其他常见错误需要不同的改进措施（例如，改进技术系统）。
