Identification of the essential components of quality in the data collection process for public health information systems

Author:

Chen Hong1,Yu Ping2ORCID,Hailey David,Cui Tingru3

Affiliation:

1. University of Wollongong, Australia; Jiangxi Provincial Centre for Disease Prevention and Control, China

2. University of Wollongong, Australia; Illawarra Health and Medical Research Institute, Australia

3. University of Wollongong, Australia

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.

Funder

Australian Government Research Training Program Scholarship

Publisher

SAGE Publications

Subject

Health Informatics

Reference65 articles.

1. Introduction to Public Health Informatics

2. World Health Organization. Country health information systems: a review of the current situation and trends. Geneva: World Health Organization, 2011, pp. 3–10.

3. World Health Organization. Data quality review: a toolkit for facility data quality assessment. Module 1: framework and metrics. Geneva: World Health Organization, 2017, pp. 5–12.

4. Canadian Institute for Health Information (CIHI). The CIHI data quality framework. Ottawa, ON: CIHI, 2009, pp. 1–8.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3