Application of a four-dimensional framework to evaluate the quality of the HIV/AIDS data collection process in China. (January 2021)

• Record Type: Journal Article
• Authors: Chen, Hong; Yu, Ping; Hailey, David; Cui, Tingru
• Is Part Of: International journal of medical informatics. Volume 145(2021)
• Publication Date: 2021-01
• Subjects: Data quality -- Data collection process -- HIV/AIDS information management systems -- China -- 4D framework; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2020.104306
• Languages: English
• ISSNs: 1386-5056

Abstract

Abstract: Objective: To qualitatively evaluate the quality of the data collection process used by the Chinese national HIV/AIDS data repository (CRIMS), using a four-dimensional (4D) framework. The process is vital for the acquisition of high-quality data for ending the HIV/AIDS epidemic in China. Methods: The study was carried out in China from September 2014 to April 2015. Stratified convenient sampling was conducted to recruit 28 study participants including health administrators, public health professionals and clinicians. Data were collected through semi-structured interviews with the participants and from field observations in six hospitals. Content analysis was conducted following the 4D Framework. Results: 61 percent of the facilitators and 74 percent of the barriers of the 4D Framework were confirmed in the CRIMS data collection process. The CRIMS achieved better-quality data collection management. The perceived gaps primarily included: impractical data collection protocol and invalid quality assessment mechanism for data collection management; weak leadership and unsupportive organizational policy for data collection environment; poor communication and job fatigue for data collection personnel; and inflexibility and inaccessibility of data collection system. Areas for improvement included: engaging frontline staff in the design of data collection protocol, standardizing quality assurance procedures, strengthening leadership, recognizing data collector's contributions, and meeting end-users' needs for the CRIMS. Conclusion: The findings generated knowledge about the quality of the CRIMS data collection process. The 4D Framework has potential as an evaluation tool for decision-makers on the improvement of the public health data collection process.