Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia.
Centre for Integrated Critical Care, University of Melbourne, Melbourne, Australia.
BMC Med Inform Decis Mak. 2021 Feb 2;21(1):37. doi: 10.1186/s12911-021-01393-1.
Data from clinical registries may be linked to gain additional insights into disease processes, risk factors and outcomes. Identifying information varies from full names, addresses and unique identification codes to statistical linkage keys to no direct identifying information at all. A number of databases in Australia contain the statistical linkage key 581 (SLK-581). Our aim was to investigate the ability to link data using SLK-581 between two national databases, and to compare this linkage to that achieved with direct identifiers or other non-identifying variables.
The Australian and New Zealand Society of Cardiothoracic Surgeons database (ANZSCTS-CSD) contains fully identified data. The Australian and New Zealand Intensive Care Society database (ANZICS-APD) contains non-identified data together with SLK-581. Identifying data is removed at participating hospitals prior to central collation and storage. We used the local hospital ANZICS-APD data at a large single tertiary centre prior to deidentification and linked this to ANZSCTS-CSD data. We compared linkage using SLK-581 to linkage using non-identifying variables (dates of admission and discharge, age and sex) and linkage using a complete set of unique identifiers. We compared the rate of match, rate of mismatch and clinical characteristics between unmatched patients using the different methods.
There were 1283 patients eligible for matching in the ANZSCTS-CSD. 1242 were matched using unique identifiers. Using non-identifying variables 1151/1242 (92.6%) patients were matched. Using SLK-581, 1202/1242 (96.7%) patients were matched. The addition of non-identifying data to SLK-581 provided few additional patients (1211/1242, 97.5%). Patients who did not match were younger, had a higher mortality risk and more non-standard procedures vs matched patients. The differences between unmatched patients using different matching strategies were small.
All strategies provided an acceptable linkage. SLK-581 improved the linkage compared to non-identifying variables, but was not as successful as direct identifiers. SLK-581 may be used to improve linkage between national registries where identifying information is not available or cannot be released.
临床注册数据可通过链接获取,以深入了解疾病过程、风险因素和结果。识别信息各不相同,包括全名、地址和唯一识别码、统计链接键,甚至完全没有直接识别信息。澳大利亚有多个数据库包含统计链接键 581(SLK-581)。我们的目的是调查使用 SLK-581 在两个国家数据库之间进行数据链接的能力,并比较这种链接与使用直接标识符或其他非识别变量实现的链接。
澳大利亚和新西兰心胸外科协会数据库(ANZSCTS-CSD)包含完整的识别数据。澳大利亚和新西兰重症监护协会数据库(ANZICS-APD)包含非识别数据和 SLK-581。在中央汇总和存储之前,参与医院会删除识别数据。我们使用一家大型三级医院的当地医院 ANZICS-APD 数据进行去识别,并将其与 ANZSCTS-CSD 数据链接。我们比较了使用 SLK-581 进行链接、使用非识别变量(入院和出院日期、年龄和性别)进行链接以及使用完整的唯一标识符进行链接的结果。我们比较了使用不同方法的不匹配患者的匹配率、不匹配率和临床特征。
ANZSCTS-CSD 中有 1283 名符合匹配条件的患者。使用唯一标识符匹配了 1242 名患者。使用非识别变量匹配了 1151/1242(92.6%)名患者。使用 SLK-581 匹配了 1202/1242(96.7%)名患者。将非识别数据添加到 SLK-581 中仅增加了 1211/1242(97.5%)名患者。未匹配的患者年龄较小,死亡率风险较高,非标准手术较多。使用不同匹配策略的未匹配患者之间的差异较小。
所有策略均提供了可接受的链接。与非识别变量相比,SLK-581 提高了链接,但不如直接标识符成功。在没有或无法发布识别信息的情况下,SLK-581 可用于改善国家登记处之间的链接。