Using routine clinical and administrative data to produce a dataset of attendances at Emergency Departments following self-harm
Using routine clinical and administrative data to produce a dataset of attendances at Emergency Departments following self-harm
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DOI：
10.1186/s12873-015-0041-6
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发表时间：
2015-01-01
影响因子：
2.5
通讯作者：
Hotopf, M.
中科院分区：
文献类型：
--
作者：
Polling, C.;Tulloch, A.;Hotopf, M.
背景：自残是英国的一个重大公共卫生问题。这反映在英国公共卫生成果框架最近新增的自残后急诊科 (ED) 就诊率中。然而，目前没有数据来源来衡量这一结果。自残后住院的常规可用数据遗漏了大多数就诊的病例。我们的目的是调查（i）是否可以使用常规收集的临床和管理数据的组合来生成急诊科演示数据集，以及（ii）将该数据集与使用类似于以前研究中使用的方法生成的另一个数据集进行验证。方法：使用临床记录交互式搜索系统，将四个急诊室中使用的电子健康记录（EHR）与医院事件统计数据链接起来，以创建自残后就诊的数据集。将该数据集与通过手动搜索 ED 记录创建的 ED 出勤审计数据集进行比较。比较每个数据集检测到的总病例比例。结果：EHR 数据集检测到出勤人数为 1932 人，审计检测到出勤人数为 1906 人。 EHR 和审计数据集分别检测到了所有出勤率的 77% 和 76%，并且均检测到了 82% 的个体患者。使用 EHR 方法检测到的人和遗漏的人在年龄、性别、种族或婚姻状况方面没有差异。这两个数据集显示的自残事件数量比住院记录中识别的自残事件数量多出一倍多。 结论：可以使用常规收集的 EHR 数据来创建自残后急诊室就诊情况的数据集。该数据集检测到的出勤率和个人比例与审计数据集相同，事实证明比使用住院患者入院记录更全面，并且在漏掉的案例中没有表现出系统性偏差。
Background: Self-harm is a significant public health concern in the UK. This is reflected in the recent addition to the English Public Health Outcomes Framework of rates of attendance at Emergency Departments (EDs) following self-harm. However there is currently no source of data to measure this outcome. Routinely available data for inpatient admissions following self-harm miss the majority of cases presenting to services. We aimed to investigate (i) if a dataset of ED presentations could be produced using a combination of routinely collected clinical and administrative data and (ii) to validate this dataset against another one produced using methods similar to those used in previous studies.Methods: Using the Clinical Record Interactive Search system, the electronic health records (EHRs) used in four EDs were linked to Hospital Episode Statistics to create a dataset of attendances following self-harm. This dataset was compared with an audit dataset of ED attendances created by manual searching of ED records. The proportion of total cases detected by each dataset was compared.Results: There were 1932 attendances detected by the EHR dataset and 1906 by the audit. The EHR and audit datasets detected 77 % and 76 % of all attendances respectively and both detected 82 % of individual patients. There were no differences in terms of age, sex, ethnicity or marital status between those detected and those missed using the EHR method. Both datasets revealed more than double the number of self-harm incidents than could be identified from inpatient admission records.Conclusions: It was possible to use routinely collected EHR data to create a dataset of attendances at EDs following self-harm. The dataset detected the same proportion of attendances and individuals as the audit dataset, proved more comprehensive than the use of inpatient admission records, and did not show a systematic bias in those cases it missed.