Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Aug 18, 2022
Open Peer Review Period: Jul 26, 2022 - Sep 20, 2022
Date Accepted: Jul 14, 2023
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Data Quality in health research: an integrative literature review
ABSTRACT
Background:
Decision-making and strategies to improve service delivery need to be supported by reliable health data to generate consistent evidence on health status, so the data quality management process must ensure the reliability of the data collected. Consequently, various methodologies to improve the quality of services have been applied in the health field. Likewise, research in scientific communities about new strategies is constantly evolving to improve research quality through better reproducibility and empowerment of researchers and patient groups with tools for secure data sharing and privacy compliance
Objective:
Through an integrative literature review, the main objective of this work is to identify and evaluate digital health technology interventions designed to support the conduct of health research based on data quality.
Methods:
A search was carried out in six electronic scientific databases in January 2022 at: PubMed, SCOPUS, Web of Science, IEEE Digital Library, CINAHL, and LILACS. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist and flowchart were used for graphical visualization of the results of the search strategy in the databases
Results:
After analyzing and extracting the results of interest, 33 articles were included in the review. The studies covered the years 2017 to 2021 and involved 22 countries. The main barriers reported in relation to the theme of research in the area of health data quality cite circumstances regarding a) use, b) systems and c) health services. Such barriers are influenced by technical, organizational, behavioral, and environmental factors that cover large contexts of information systems, specific knowledge and multidisciplinary techniques.The quality of each data element can be assessed by checking their adherence to institutional norms or by comparing and validating them with external sources
Conclusions:
This transdisciplinarity may be reaching the threshold of significant growth and thus forcing the need for a metamorphosis of the area from focusing on the measurement and evaluation of data quality, today focused on content, to a direction focused on use and context In general, the main barriers reported in relation to the theme of research in the area of health data quality cite circumstances regarding a) use, b) systems and c) health services. The resources presented can help guide medical decisions that do not only involve medical professionals, and indirectly contribute to avoiding decisions based on low-quality information that can put patients’ lives at risk
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.