Jacke, C. O. and Kalder, M. and Koller, M. and Wagner, U. and Albert, U. S. (2012) Systematic assessment and improvement of medical data quality. BUNDESGESUNDHEITSBLATT-GESUNDHEITSFORSCHUNG-GESUNDHEITSSCHUTZ, 55 (11-12). pp. 1495-1503. ISSN 1436-9990,
Full text not available from this repository. (Request a copy)Abstract
Public health research depends on empirical information that is based on data of high quality. The aim of this study was to apply the current guidelines developed by the Technology and Methodology Platform for Networked Medical Research (TMF) for the independent assessment and enhancement of data quality. A clinical register of female breast cancer patients from two periods (N = 389 of 1996-1997 and N = 488 of 2003-2004) was used. To check the plausibility, organization, and correctness of the data quality levels, data quality indicators (DQI) were chosen, operationalized, and the variance ratios of normative-analytic-defined thresholds were calculated. Significant deviations led to data improvement, which included the commonly known source data verification (SDV). A summary data quality score was calculated before and after application of the guidelines. Eleven out of 24 DQIs were tested. Data quality systematically increased from 51.6 to 67.7%. The guidelines facilitate a systematic assessment and improvement of data quality with a reasonable use of resources. This target-oriented procedure allows for a high transparency of the available data quality, which is essential for health research.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | BREAST-CANCER THERAPY; PROOF-OF-CONCEPT; GERMANY; CARE; CENTERS; CERTIFICATION; Data quality; Cohort studies; Guidelines; Source data verification; Data quality indicators (DQI) |
| Subjects: | 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Zentren des Universitätsklinikums Regensburg > Zentrum für Klinische Studien |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 04 May 2020 10:18 |
| Last Modified: | 04 May 2020 10:18 |
| URI: | https://pred.uni-regensburg.de/id/eprint/17872 |
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