Perfusion Downunder Collaboration Database—Data Quality Assurance: Towards a High Quality Clinical Database

Abstract

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.