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Abstract
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Background
Planning for injury prevention and control activities relies upon good quality data from Road Traffic Injury Registry System (RTIRS). This study aimed at performing a meta-synthesis through a scoping review approach that sought a more comprehensive understanding of the existing global experiences on how to manage and assess data quality in the RTIRS.
Methods
This meta-synthesis study was conducted as a scoping review based on Arksey and O'Malley's framework, 2005. Ten international and national databases, including PubMed/MEDLINE, Scopus, Science Direct and Web of Science, Scientific Information Database (SID), Safety Literature of Iran (SafeLir), SafetyLit, Magiran, IranMedex, and Barakat knowledge network system (BKNS), were searched for studies up to 31 December 2021. References were independently screened by two researchers based on title and abstract, full-text review, and manual bibliography of included studies. Disputes that could not be resolved through discussion between the researchers were arbitrated by the lead researcher. The findings were synthesized through the meta-narrative analysis method.
Results
Out of 3487 studies, 33 studies were included for data synthesis. The synthesis of literature resulted in the emergence of four themes and 14 sub-themes. The main themes included dimensions of quality measurement (Individual approach to data quality measurement and systemic approach to quality measurement of the registry system); data quality strategies (data quality assurance strategies and data quality control strategies); challenges and solutions for each data quality characteristic (physical resources, human resources, guidelines and protocols, and training); and barriers and facilitators of data quality (equipment and technology, human resources, organization, management, and support processes, infrastructure, and individual factors).
Conclusion
This review provides a meta-synthesis of existing evidence related to the experiences of different countries on how to manage and evaluate the quality of data in the RTIRS, as well as identify the features that are effective in measuring data quality.
Language: en |