%0 Journal Article
%T A Framework for Visualizing Data Quality for Predictive Models and Clinical Quality Measures
%A Alexander Hoff
%A Bonnie L. Westra
%A Gy£¿rgy J. Simon
%A Lisiane Pruinelli
%A Michael Steinbach
%A Steven G. Johnson
%A Vipin Kumar
%J Archive of "AMIA Summits on Translational Science Proceedings".
%D 2019
%X The ability to assess data quality is essential for secondary use of EHR data and an automated Healthcare Data Quality Framework (HDQF) can be used as a tool to support a healthcare organization¡¯s data quality initiatives. Use of a general purpose HDQF provides a method to assess and visualize data quality to quickly identify areas for improvement. The value of the approach is illustrated for two analytics use cases: 1) predictive models and 2) clinical quality measures. The results show that data quality issues can be efficiently identified and visualized. The automated HDQF is much less time consuming than a manual approach to data quality and the framework can be rerun repeatedly on additional datasets without much effort
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6568139/