Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Sep 12, 2022
Date Accepted: Dec 31, 2022
Digital Health Data Quality Issues: Systematic Review
ABSTRACT
Background:
The promise of digital health is principally dependent on the ability to electronically capture data which can be analysed to improve decision making. Yet, the ability to effectively harness data has proven elusive, which has largely been due to the quality of data captured.
Objective:
The aim of this study was to identify the dimensions of digital health data quality and their outcomes.
Methods:
A developmental systematic literature review was conducted of peer-reviewed literature focusing on digital health data quality in predominately hospital settings. A total of 227 relevant articles were retrieved that were inductively analysed to identify digital health data quality dimensions and outcomes. Through constant comparison the dimensions and outcomes were consolidated and a digital health data quality dimensions and outcomes (DQ-DO) framework was developed.
Results:
The digital health DQ-DO framework consists of six dimensions of data quality: accessibility, accuracy, completeness, consistency, contextual validity, and currency, with interrelationships existing amongst the dimensions. Six digital health data quality outcomes were also identified: clinical, clinician, data reusability, research-related, business processes, and organizational outcomes.
Conclusions:
The digital health data quality framework developed in this study demonstrates the complexity of digital health data quality and the necessity for reducing digital health data quality issues.
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.