Huser, VojtechLi, XiaochunZhang, ZuoyiJung, SungjaeWoong Park, RaeBanda, JuanRazzaghi, HaniehLondhe, AjitNatarajan, Karthik2021-02-052021-02-052019Huser, V., Li, X., Zhang, Z., Jung, S., Park, R. W., Banda, J., Razzaghi, H., Londhe, A., & Natarajan, K. (2019). Extending Achilles Heel Data Quality Tool with New Rules Informed by Multi-Site Data Quality Comparison. Studies in Health Technology and Informatics, 264, 1488–1489. https://doi.org/10.3233/SHTI190498https://hdl.handle.net/1805/25160Large 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.enAttribution 4.0 Internationaldata qualityobservational studysoftwareArticle