| Literature DB >> 31438195 |
Vojtech Huser1, Xiaochun Li2, Zuoyi Zhang2, Sungjae Jung3, Rae Woong Park3, Juan Banda4, Hanieh Razzaghi5, Ajit Londhe6, Karthik Natarajan7.
Abstract
Large healthcare datasets of Electronic Health Record data became indispensable in clinical research. Data quality in such datasets recently became a focus of many distributed research networks. Despite the fact that data quality is specific to a given research question, many existing data quality platform prove that general data quality assessment on dataset level (given a spectrum of research questions) is possible and highly requested by researchers. We present comparison of 12 datasets and extension of Achilles Heel data quality software tool with new rules and data characterization measures.Keywords: data quality; observational study
Mesh:
Year: 2019 PMID: 31438195 DOI: 10.3233/SHTI190498
Source DB: PubMed Journal: Stud Health Technol Inform ISSN: 0926-9630