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Stud Health Technol Inform. 2019 Aug 21;264:1488-1489. doi: 10.3233/SHTI190498.

Extending Achilles Heel Data Quality Tool with New Rules Informed by Multi-Site Data Quality Comparison.

Author information

1
National Library of Medicine, MD, USA.
2
Indiana University, IN, USA.
3
Ajou University School of Medicine, Suwon, South Korea.
4
Georgia State University, GA, USA.
5
Children's Hospital of Philadelphia, PA, USA.
6
Janssen Research & Development, NJ, USA.
7
Columbia University, NY, USA.

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

PMID:
31438195
DOI:
10.3233/SHTI190498
[Indexed for MEDLINE]

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