Tuble Sigrid C
Department of Cardiac and Thoracic Surgery, Flinders Medical Centre, Adelaide, Australia.
J Extra Corpor Technol. 2011 Mar;43(1):P44-51.
Maintaining a high quality clinical database is critical to obtain reliable information upon which to base clinical and institutional decisions, and to preserve the public and the user's confidence in the quality of the data. The success of the Perfusion Downunder Collaboration (PDUC) Database, a dataset for cardiopulmonary bypass procedures, can only be guaranteed through the assurance of the quality of its data. This paper presents the evaluation of the data quality in the PDUC Database. Three participating centers located in Adelaide, Australia were audited: Flinders Private Hospital (FPH), Flinders Medical Center (FMC), and Ashford Hospital (AH). Ten perCent of the cases submitted from the first year of data harvest were audited (2008: FPH and FMC, 2009: AH). A total of 57 variables were reviewed and rates of discrepancies (inaccurate, missing, not entered, cannot be validated) categorized as 0-25%, 25-50%, 51-75%, and 75-100% of cases (% = cases with discrepancy/total cases audited) evaluated. Sixty randomly selected cases were audited, comprising of 13 cases from FPH, 31 cases from FMC, and 16 cases from AH. Of a total of 3420 data points evaluated, 6.9% were found to be inaccurate and 3.2% were missing. For each participating center, the great majority of variables have discrepancies in few (0-25%) of the cases audited. The discrepancies found can be attributed to systematic errors (e.g., error in date difference calculation for length of stays, data transformation error for postoperative dialysis) and random errors (e.g., use of incorrect unit for creatinine, transcription error for discharge date). The PDUC Database is currently reasonably accurate and complete. This evaluation is part of a complex system of data quality assurance, and when conducted routinely, could provide a continuous feedback loop towards a high quality PDUC Database.
维护高质量的临床数据库对于获取可靠信息至关重要,这些信息是临床和机构决策的依据,同时也能维护公众和用户对数据质量的信心。体外循环程序数据集——澳大利亚灌注协作(PDUC)数据库的成功,只能通过确保其数据质量来保证。本文介绍了对PDUC数据库数据质量的评估。对位于澳大利亚阿德莱德的三个参与中心进行了审核:弗林德斯私立医院(FPH)、弗林德斯医疗中心(FMC)和阿什福德医院(AH)。对数据收集第一年提交的病例的10%进行了审核(2008年:FPH和FMC,2009年:AH)。共审查了57个变量,并将差异率(不准确、缺失、未录入、无法验证)分类为审核病例的0 - 25%、25 - 50%、51 - 75%和75 - 100%(% = 有差异的病例数/审核的病例总数)进行评估。随机抽取了60例病例进行审核,其中包括来自FPH的13例、来自FMC的31例和来自AH的16例。在总共评估的3420个数据点中,发现6.9%不准确,3.2%缺失。对于每个参与中心,绝大多数变量在少数(0 - 25%)审核病例中存在差异。发现的差异可归因于系统误差(例如,住院时间日期差计算错误、术后透析数据转换错误)和随机误差(例如,肌酐单位使用错误、出院日期转录错误)。PDUC数据库目前相当准确和完整。该评估是数据质量保证复杂系统的一部分,定期进行时,可以为高质量的PDUC数据库提供持续的反馈循环。