Maier Birga, Wagner Katrin, Behrens Steffen, Bruch Leonhard, Busse Reinhard, Schmidt Dagmar, Schühlen Helmut, Thieme Roland, Theres Heinz
Berlin Myocardial Infarction Registry, Technische Universität, Berlin, Germany.
Department of Cardiology, Vivantes Humboldt Klinikum, Berlin, Germany.
BMC Health Serv Res. 2016 Oct 21;16(1):605. doi: 10.1186/s12913-016-1840-5.
Assessment of quality of care in patients with myocardial infarction (MI) should be based on data that effectively enable determination of quality. With the need to simplify measurement techniques, the question arises whether routine data can be used for this purpose. We therefore compared data from a German sickness fund (AOK) with data from the Berlin Myocardial Infarction Registry (BMIR).
We included patients hospitalised for treatment of MI in Berlin from 2009-2011. We matched 2305 patients from AOK and BMIR by using deterministic record linkage with indirect identifiers. For matched patients we compared the frequency in documentation between AOK and BMIR for quality assurance variables and calculated the kappa coefficient (KC) as a measure of agreement.
There was almost perfect agreement in documentation between AOK and BMIR data for matched patients for: catheter laboratory (KC: 0.874), ST elevation MI (KC: 0.826), diabetes (KC: 0.818), percutaneous coronary intervention (KC: 0.860) and hospital mortality (KC: 0.952). The remaining variables compared showed moderate or less than moderate agreement (KC < 0.6), and were grouped in Category II with less frequent documentation in AOK for risk factors and aspects of patients' history; in Category III with more frequent documentation in AOK for comorbidities; and in Category IV for medication at and after hospital discharge.
Routine data are primarily collected and defined for reimbursement purposes. Quality assurance represents merely a secondary use. This explains why only a limited number of variables showed almost perfect agreement in documentation between AOK and BMIR. If routine data are to be used for quality assessment, they must be constantly monitored and further developed for this new application. Furthermore, routine data should be complemented with registry data by well-established methods of record linkage to realistically reflect the situation - also for those quality-associated variables not collected in routine data.
对心肌梗死（MI）患者的医疗质量评估应基于能够有效确定质量的数据。鉴于需要简化测量技术，于是产生了常规数据是否可用于此目的的问题。因此，我们将德国一家疾病基金组织（AOK）的数据与柏林心肌梗死登记处（BMIR）的数据进行了比较。
我们纳入了2009年至2011年在柏林因MI治疗而住院的患者。我们通过使用带有间接标识符的确定性记录链接，将来自AOK和BMIR的2305名患者进行匹配。对于匹配的患者，我们比较了AOK和BMIR在质量保证变量文档记录方面的频率，并计算了kappa系数（KC）作为一致性的度量。
对于匹配的患者，AOK和BMIR数据在以下方面的文档记录几乎完全一致：导管实验室（KC：0.874）、ST段抬高型心肌梗死（KC：0.826）、糖尿病（KC：0.818）、经皮冠状动脉介入治疗（KC：0.860）和医院死亡率（KC：0.952）。所比较的其余变量显示出中等或低于中等的一致性（KC < 0.6），并分为以下几类：第二类是AOK中危险因素和患者病史方面的文档记录频率较低；第三类是AOK中共存疾病的文档记录频率较高；第四类是出院时及出院后的用药情况。
常规数据主要是为报销目的而收集和定义的。质量保证仅仅是次要用途。这就解释了为什么只有有限数量的变量在AOK和BMIR之间的文档记录中显示出几乎完全一致。如果要将常规数据用于质量评估，就必须对其进行持续监测并针对这一新应用进行进一步完善。此外，常规数据应通过成熟的记录链接方法与登记处数据相结合，以切实反映实际情况——对于常规数据中未收集的那些与质量相关的变量也是如此。
