Validation of an electronic trigger to measure missed diagnosis of stroke in emergency departments.
Validation of an electronic trigger to measure missed diagnosis of stroke in emergency departments.
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验证电子触发器以测量急诊室中风的漏诊情况。
DOI：
10.1093/jamia/ocab121
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Singh,Hardeep
中科院分区：
文献类型：
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作者：
Vaghani,Viralkumar;Wei,Li;Mushtaq,Umair;Sittig,DeanF;Bradford,Andrea;Singh,Hardeep
目的诊断错误是造成可预防的患者伤害的主要原因。我们验证了使用基于电子健康记录 (EHR) 的触发器 (e-trigger) 来衡量急诊科 (ED) 中风诊断中错失的机会。方法使用两个框架，即 Safer Dx 触发工具框架和诊断错误框架的症状-疾病对分析框架，我们应用基于症状-疾病对的电子触发器来识别因中风住院的患者，这些患者在过去 30 天内因良性头痛或良性头痛而出院。头晕诊断。该算法已应用于退伍军人事务部国家企业数据仓库中 2016 年 1 月 1 日至 2017 年 12 月 31 日期间就诊的患者。训练有素的审查人员评估医疗记录中是否存在中风诊断和中风相关危险信号、危险因素、神经系统检查和临床干预方面错过的机会。审核人员还评估了 ED 就诊索引中的临床记录质量。结果我们将电子触发应用于 7,752,326 名独特患者，并确定了 46,931 例中风相关入院病例，其中 398 条记录被标记为触发阳性并进行了审核。其中，124 个错过了机会（“错过”的阳性预测值 = 31.2%），93 个（23.4%）没有错过机会（未错过），162 个（40.7%）编码错误，19 个（4.7%）不确定。审稿人一致度很高（87.3%，Cohen’s kappa = 0.81）。与未漏诊组相比，漏诊组有更多的中风危险因素（平均 3.2 比 2.6）、危险信号（平均 0.5 比 0.2）以及更高的记录不充分率（66.9% 比 28.0%）。结论在大型国家 EHR 存储库中，基于症状 - 疾病对的电子触发程序识别出具有适度阳性预测值的中风漏诊，强调需要图表审查验证程序来识别大数据集中的诊断错误。
ObjectiveDiagnostic errors are major contributors to preventable patient harm. We validated the use of an electronic health record (EHR)-based trigger (e-trigger) to measure missed opportunities in stroke diagnosis in emergency departments (EDs).MethodsUsing two frameworks, the Safer Dx Trigger Tools Framework and the Symptom-disease Pair Analysis of Diagnostic Error Framework, we applied a symptom–disease pair-based e-trigger to identify patients hospitalized for stroke who, in the preceding 30 days, were discharged from the ED with benign headache or dizziness diagnoses. The algorithm was applied to Veteran Affairs National Corporate Data Warehouse on patients seen between 1/1/2016 and 12/31/2017. Trained reviewers evaluated medical records for presence/absence of missed opportunities in stroke diagnosis and stroke-related red-flags, risk factors, neurological examination, and clinical interventions. Reviewers also estimated quality of clinical documentation at the index ED visit.ResultsWe applied the e-trigger to 7,752,326 unique patients and identified 46,931 stroke-related admissions, of which 398 records were flagged as trigger-positive and reviewed. Of these, 124 had missed opportunities (positive predictive value for “missed” = 31.2%), 93 (23.4%) had no missed opportunity (non-missed), 162 (40.7%) were miscoded, and 19 (4.7%) were inconclusive. Reviewer agreement was high (87.3%, Cohen’s kappa = 0.81). Compared to the non-missed group, the missed group had more stroke risk factors (mean 3.2 vs 2.6), red flags (mean 0.5 vs 0.2), and a higher rate of inadequate documentation (66.9% vs 28.0%).ConclusionIn a large national EHR repository, a symptom–disease pair-based e-trigger identified missed diagnoses of stroke with a modest positive predictive value, underscoring the need for chart review validation procedures to identify diagnostic errors in large data sets.