A Framework for Visualizing Data Quality for Predictive Models and Clinical Quality Measures.
AMIA Jt Summits Transl Sci Proc
; 2019: 630-638, 2019.
Article
in En
| MEDLINE
| ID: mdl-31259018
ABSTRACT
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.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Type of study:
Guideline
/
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
AMIA Jt Summits Transl Sci Proc
Year:
2019
Document type:
Article