Objective: Harmonized data quality (DQ) assessment terms, methods, and reporting
practices can establish a common understanding of the strengths and limitations of …

BACKGROUND: Evaluating surgical outcomes is an important tool to compare providers
and institutions and to drive process improvements. Differing methodologies, however, may …

Introduction: Poor data quality can be a serious threat to the validity and generalizability of
clinical research findings. The growing availability of electronic administrative and clinical …

Paper-based and electronic patient records generally are used in parallel to support
different tasks. Many studies comparing their quality do not report sufficiently on the methods …

OBJECTIVE: Reliability of diagnoses coding is essential for the use of routine data in a
national health care system. The present investigation compares reliability of diagnoses …

Methods: Findings are based on 6 exploratory site visits conducted under naturalistic inquiry
in the spring of 2011. Themes, challenges, and innovations were identified in the visit …

Background Multisite research networks such as the project “Collaboration on Rare
Diseases” connect various hospitals to obtain sufficient data for clinical research. However …

Background Many research initiatives aim at using data from electronic health records
(EHRs) in observational studies. Participating sites of the German Medical Informatics …

Objective Development of systematic approaches for understanding and assessing data
quality is becoming increasingly important as the volume and utilization of health data …

Data quality is of highest importance for quantitative medical research. A common set of
indicators for data quality is needed to cope with the future challenges in data management …