Objective

To evaluate the completeness of diagnosis recording in problem lists in a hospital electronic health record (EHR) system during the COVID-19 pandemic.

Design

Retrospective chart review with manual review of free text electronic case notes.

Setting

Major teaching hospital trust in London, one year after the launch of a comprehensive EHR system (Epic), during the first peak of the COVID-19 pandemic in the UK.

Participants

516 patients with suspected or confirmed COVID-19.

Main outcome measures

Percentage of diagnoses already included in the structured problem list.

Results

Prior to review, these patients had a combined total of 2841 diagnoses recorded in their EHR problem lists. 1722 additional diagnoses were identified, increasing the mean number of recorded problems per patient from 5.51 to 8.84. The overall percentage of diagnoses originally included in the problem list was 62.3% (2841 / 4563, 95% confidence interval 60.8%, 63.7%).

Conclusions

Diagnoses and other clinical information stored in a structured way in electronic health records is extremely useful for supporting clinical decisions, improving patient care and enabling better research. However, recording of medical diagnoses on the structured problem list for inpatients is incomplete, with almost 40% of important diagnoses mentioned only in the free text notes.

中文翻译：

---

电子健康记录 (EHR) 系统中的数据缺口：对 COVID-19 大流行期间问题列表完整性的审计

客观的

评估 COVID-19 大流行期间医院电子健康记录 (EHR) 系统问题列表中诊断记录的完整性。

设计

回顾性图表审查，人工审查自由文本电子病例记录。

环境

在英国 COVID-19 大流行的第一个高峰期，在全面 EHR 系统 (Epic) 启动一年后，伦敦的主要教学医院信任。

参加者

516 名疑似或确诊 COVID-19 患者。

主要观察指标

已包含在结构化问题列表中的诊断百分比。

结果

在审查之前，这些患者的 EHR 问题列表中总共记录了 2841 项诊断。确定了 1722 项额外诊断，将每位患者记录的问题平均数从 5.51 增加到 8.84。最初包含在问题列表中的诊断的总体百分比为 62.3%（2841 / 4563，95% 置信区间 60.8%，63.7%）。

结论

以结构化方式存储在电子健康记录中的诊断和其他临床信息对于支持临床决策、改善患者护理和促进更好的研究非常有用。然而，住院患者结构化问题列表中的医疗诊断记录并不完整，近 40% 的重要诊断仅在自由文本注释中提及。