Aerts Hannelore, Kalra Dipak, Sáez Carlos, Ramírez-Anguita Juan Manuel, Mayer Miguel-Angel, Garcia-Gomez Juan M, Durà-Hernández Marta, Thienpont Geert, Coorevits Pascal
Medical Informatics and Statistics Unit, Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
The European Institute for Innovation through Health Data (i~HD), Ghent, Belgium.
JMIR Med Inform. 2021 Aug 4;9(8):e27842. doi: 10.2196/27842.
There is increasing recognition that health care providers need to focus attention, and be judged against, the impact they have on the health outcomes experienced by patients. The measurement of health outcomes as a routine part of clinical documentation is probably the only scalable way of collecting outcomes evidence, since secondary data collection is expensive and error-prone. However, there is uncertainty about whether routinely collected clinical data within electronic health record (EHR) systems includes the data most relevant to measuring and comparing outcomes and if those items are collected to a good enough data quality to be relied upon for outcomes assessment, since several studies have pointed out significant issues regarding EHR data availability and quality.
In this paper, we first describe a practical approach to data quality assessment of health outcomes, based on a literature review of existing frameworks for quality assessment of health data and multistakeholder consultation. Adopting this approach, we performed a pilot study on a subset of 21 International Consortium for Health Outcomes Measurement (ICHOM) outcomes data items from patients with congestive heart failure.
All available registries compatible with the diagnosis of heart failure within an EHR data repository of a general hospital (142,345 visits and 12,503 patients) were extracted and mapped to the ICHOM format. We focused our pilot assessment on 5 commonly used data quality dimensions: completeness, correctness, consistency, uniqueness, and temporal stability.
We found high scores (>95%) for the consistency, completeness, and uniqueness dimensions. Temporal stability analyses showed some changes over time in the reported use of medication to treat heart failure, as well as in the recording of past medical conditions. Finally, the investigation of data correctness suggested several issues concerning the characterization of missing data values. Many of these issues appear to be introduced while mapping the IMASIS-2 relational database contents to the ICHOM format, as the latter requires a level of detail that is not explicitly available in the coded data of an EHR.
Overall, results of this pilot study revealed good data quality for the subset of heart failure outcomes collected at the Hospital del Mar. Nevertheless, some important data errors were identified that were caused by fundamentally different data collection practices in routine clinical care versus research, for which the ICHOM standard set was originally developed. To truly examine to what extent hospitals today are able to routinely collect the evidence of their success in achieving good health outcomes, future research would benefit from performing more extensive data quality assessments, including all data items from the ICHOM standards set and across multiple hospitals.
人们越来越认识到，医疗保健提供者需要关注他们对患者健康结果的影响，并以此作为评判标准。将健康结果的测量作为临床文档的常规部分，可能是收集结果证据的唯一可扩展方法，因为二次数据收集成本高且容易出错。然而，电子健康记录（EHR）系统中常规收集的临床数据是否包含与测量和比较结果最相关的数据，以及这些项目收集的数据质量是否足以用于结果评估，仍存在不确定性，因为多项研究指出了EHR数据可用性和质量方面的重大问题。
在本文中，我们首先基于对现有健康数据质量评估框架的文献综述和多利益相关方咨询，描述一种健康结果数据质量评估的实用方法。采用这种方法，我们对充血性心力衰竭患者的21项国际健康结果测量协会（ICHOM）结果数据项的子集进行了一项试点研究。
从一家综合医院的EHR数据存储库中提取所有与心力衰竭诊断兼容的可用登记数据（142345次就诊和12503名患者），并将其映射到ICHOM格式。我们将试点评估重点放在5个常用的数据质量维度上：完整性、正确性、一致性、唯一性和时间稳定性。
我们发现一致性、完整性和唯一性维度的得分较高（>95%）。时间稳定性分析表明，治疗心力衰竭的药物使用报告以及既往病史记录随时间有一些变化。最后，对数据正确性的调查提出了几个关于缺失数据值特征的问题。许多这些问题似乎是在将IMASIS-2关系数据库内容映射到ICHOM格式时出现的，因为后者要求的详细程度在EHR的编码数据中没有明确体现。
总体而言，这项试点研究的结果显示，在德尔马医院收集的心力衰竭结果子集中数据质量良好。然而，我们发现了一些重要的数据错误，这些错误是由常规临床护理与研究中根本不同的数据收集做法导致的，而ICHOM标准集最初就是为研究制定的。为了真正检验如今医院在多大程度上能够常规收集其在实现良好健康结果方面成功的证据，未来的研究将受益于进行更广泛的数据质量评估，包括ICHOM标准集中的所有数据项并涵盖多家医院。
