Kindermann Aljoscha, Tute Erik, Benda Sebastian, Löpprich Martin, Richter-Pechanski Phillip, Dieterich Christoph
Section of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg.
Department of Internal Medicine III, University Hospital Heidelberg.
Stud Health Technol Inform. 2021 May 24;278:187-194. doi: 10.3233/SHTI210068.
The HiGHmed consortium aims to create a shared information governance framework to integrate clinical routine data. One challenge is the replacement of unstructured reporting (e.g. doctoral letters) with structured reporting in clinical routine. The Heidelberg cardiology department evaluates dynamic PDF forms for structured data reporting of heart failure (HF) patients. In this use case, we aim to identify potential caveats or shortcomings in data processing at an early stage. We employed data mining strategies to detect patterns related to incomplete or false data, which we found to be present among all data types. We then discuss the characteristics of the baseline patient cohort in Heidelberg to find out about specific peculiarities and potential biases, which may be site-specific. Briefly, our patient population is predominantly male (67%), NYHA I & II are the most common severity classes, NYHA IV is missing entirely. Most patients have a dilated cardiomyopathy (DCM) or coronary heart disease (CHD) diagnosed as their cause of HF. Finally, we also analyzed how comorbidities and risk factors relate to specific disease entities of heart failure patients. Family anamnesis was more frequent among cardiomyopathy patients than among CHD patients, who show a more dominating presence of dyslipidemia instead. Generally, the most dominant risk factor was arterial hypertension, while at the other end of the scale alcoholism appears to be underreported.
HiGHmed联盟旨在创建一个共享信息治理框架,以整合临床常规数据。其中一个挑战是在临床常规中用结构化报告取代非结构化报告(如博士信件)。海德堡心脏病学部门评估用于心力衰竭(HF)患者结构化数据报告的动态PDF表单。在此用例中,我们旨在早期识别数据处理中的潜在问题或缺点。我们采用数据挖掘策略来检测与不完整或错误数据相关的模式,我们发现这些模式存在于所有数据类型中。然后,我们讨论海德堡基线患者队列的特征,以了解可能因地点而异的特定特性和潜在偏差。简而言之,我们的患者群体主要为男性(67%),纽约心脏协会(NYHA)I级和II级是最常见的严重程度分级,NYHA IV级完全缺失。大多数患者被诊断为扩张型心肌病(DCM)或冠心病(CHD)导致HF。最后,我们还分析了合并症和危险因素与心力衰竭患者特定疾病实体的关系。心肌病患者的家族病史比冠心病患者更常见,而冠心病患者中血脂异常更为普遍。一般来说,最主要的危险因素是动脉高血压,而在另一端,酗酒似乎报告不足。