title: Measuring Data Quality: A Review of the Literature between 2005 and 2013.
abstract: A literature review was done within a revision of a guideline concerned with data quality management in registries and cohort studies. The review focused on quality indicators, feedback, and source data verification. Thirty-nine relevant articles were selected in a stepwise selection process. The majority of the papers dealt with indicators. The papers presented concepts or data analyses. The leading indicators were related to case or data completeness, correctness, and accuracy. In the future, data pools as well as research reports from quantitative studies should be obligatory supplemented by information about their data quality, ideally picking up some indicators presented in this review.
authors.affiliation: Essen, Germany.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Stausberg
authors.affiliation: IBE, Ludwig-Maximilians-Universität München, Germany.
authors.forename: Daniel
authors.initials: D
authors.lastname: Nasseh
authors.affiliation: IMIBE, Universitätsklinikum Essen, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Nonnemacher
mesh_terms: D015331:Cohort Studies; D000068598:Data Accuracy; D011785:Quality Assurance, Health Care / Q000379:methods* / Q000458:organization & administration*; D019984:Quality Indicators, Health Care / Q000592:standards*; D012042:Registries / Q000592:standards*