Identification of the essential components of quality in the data collection process for public health information systems. (March 2020)

• Record Type: Journal Article
• Authors: Chen, Hong; Yu, Ping; Hailey, David; Cui, Tingru
• Other Names: Bian Jiang guest-editor.; Modave Francois guest-editor.
• Is Part Of: Health informatics journal. Volume 26:Number 1(2020)
• Page Start: 664
• Page End: 682
• Publication Date: 2020-03
• Subjects: data collection -- data quality -- measurement instrument -- process assessment -- public health information systems; Medical informatics -- Periodicals; 610.285
• DOI: 10.1177/1460458219848622
• Languages: English
• ISSNs: 1460-4582

Abstract

This study identifies essential components in the data collection process for public health information systems based on appraisal and synthesis of the reported factors affecting this process in the literature. Extant process assessment instruments and studies of public health data collection from electronic databases and the relevant institutional websites were reviewed and analyzed following a five-stage framework. Four dimensions covering 12 factors and 149 indicators were identified. The first dimension, data collection management, includes data collection system and quality assurance. The second dimension, data collector, is described by staffing pattern, skill or competence, communication and attitude toward data collection. The third, information system, is assessed by function and technology support, integration of different data collection systems, and device. The fourth dimension, data collection environment, comprises training, leadership, and funding. With empirical testing and contextual analysis, these essential components can be further used to develop a framework for measuring the quality of the data collection process for public health information systems.