Validation of 4D Components for Measuring Quality of the Public Health Data Collection Process: Elicitation Study.
Hong Chen1,2, Ping Yu1,3, David Hailey1
1School of Computing and Information Technology, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, Australia.
Journal of Medical Internet Research
|May 10, 2021
Summary
This study validated a 4D framework for public health data collection quality, identifying key components like management, personnel, system, and environment. The refined framework will aid in developing better data quality management strategies.
Area of Science:
- Public Health
- Information Systems
- Data Quality Management
Background:
- Effective data quality management is crucial for public health information systems.
- A preliminary 4D framework (data collection management, personnel, system, environment) was developed from literature.
- Empirical validation of this framework is necessary for research and practice.
Purpose of the Study:
- To empirically validate and refine the preliminary 4D framework for public health data collection quality.
- To confirm the essential components of the data collection process.
Main Methods:
- Expert elicitation was employed using the Chinese National HIV/AIDS Comprehensive Response Information Management System.
- A mixed-methods approach involved qualitative data analysis of interviews and quantitative comparative analysis.
- 3 public health administrators, 15 public health workers, and 10 health care practitioners participated.
Main Results:
- The validated 4D framework comprises 116 indicators (82 facilitators, 34 barriers).
- Significant revisions occurred: 46 new indicators emerged, 24.8% were deleted, and 28.2% were merged.
- Component proportions shifted, with 'data collection environment' increasing and 'data collection management' and 'data collection system' decreasing.
Conclusions:
- The expert elicitation study successfully validated and improved the 4D framework.
- The refined framework can guide the development of survey instruments for assessing public health data collection quality.
- Further validation of psychometric properties and item reduction is recommended for survey instrument development.
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