Otsa Kati, Talli Sandra, Harding Pille, Parsik Eevi, Esko Marge, Teepere Anti, Tammaru Marika
1Department of Rheumatology, East Tallinn Central Hospital, Tallinn, Estonia.
2Department of Rheumatology, North Estonia Medical Centre, Tallinn, Estonia.
BMC Rheumatol. 2019 Jul 25;3:26. doi: 10.1186/s41927-019-0074-7. eCollection 2019.
Administrative database research is widely applied in the field of epidemiology. However, the results of the studies depend on the type of database used and the algorithms applied for case ascertainment. The optimal methodology for identifying patients with rheumatic diseases from administrative databases is yet not known. Our aim was to describe an administrative database as a source for estimation of epidemiological characteristics on an example of systemic lupus erythematosus (SLE, ICD-10 code M32) prevalence assessment in the database of the Estonian Health Insurance Fund (EHIF).
Code M32 billing episodes were extracted from the EHIF database 2006-2010. For all cases where M32 was assigned by a rheumatologist less than four times during the study period, diagnosis verification process using health care providers' (HCP) databases was applied. For M32 cases assigned by a rheumatologist four times or more, diagnoses were verified for a randomly selected sample.
From 677 persons with code M32 assigned in EHIF database, 404 were demonstrated having "true SLE". The code M32 positive predictive value (PPV) for the whole EHIF database was 60%; PPV varies remarkably by specialty of a physician and repetition of the code assignment. The false positive M32 codes were predominantly initial diagnoses which were not confirmed afterwards; in many cases, a rheumatic condition other than SLE was later diagnosed.
False positive codes due to tentative diagnoses may be characteristic for conditions with a complicated diagnosis process like SLE and need to be taken into account when performing administrative database research.
行政数据库研究在流行病学领域中广泛应用。然而，研究结果取决于所使用的数据库类型以及用于病例确定的算法。目前尚不清楚从行政数据库中识别风湿病患者的最佳方法。我们的目的是以爱沙尼亚健康保险基金（EHIF）数据库中系统性红斑狼疮（SLE，ICD - 10编码M32）患病率评估为例，描述行政数据库作为估计流行病学特征来源的情况。
从EHIF数据库2006 - 2010年中提取编码为M32的计费记录。对于在研究期间由风湿病学家分配M32编码少于四次的所有病例，采用使用医疗服务提供者（HCP）数据库的诊断验证流程。对于由风湿病学家分配M32编码四次或更多次的病例，对随机选择的样本进行诊断验证。
在EHIF数据库中被分配M32编码的677人中，有404人被证实患有“真正的SLE”。整个EHIF数据库中M32编码的阳性预测值（PPV）为60%；PPV因医生专业和编码分配次数的不同而有显著差异。假阳性M32编码主要是最初诊断但后来未得到证实的情况；在许多情况下，后来诊断出的是除SLE之外的其他风湿性疾病。
由于初步诊断导致的假阳性编码可能是像SLE这种诊断过程复杂的疾病的特征，在进行行政数据库研究时需要考虑到这一点。
