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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Sep 12, 2022
Date Accepted: Dec 31, 2022

The final, peer-reviewed published version of this preprint can be found here:

Digital Health Data Quality Issues: Systematic Review

Rehan S, Eden R, Makasi T, Chukwudi I, Mamudu A, Kamalpour M, Kapugama Geeganage D, Sadeghianasl S, Leemans SJJ, Goel K, Andrews R, Thandar Wynn M, ter Hofstede A, Myers T

Digital Health Data Quality Issues: Systematic Review

J Med Internet Res 2023;25:e42615

DOI: 10.2196/42615

PMID: 37000497

PMCID: 10131725

Digital Health Data Quality Issues: Systematic Review

  • Syed Rehan; 
  • Rebekah Eden; 
  • Tendai Makasi; 
  • Ignatius Chukwudi; 
  • Azumah Mamudu; 
  • Mostafa Kamalpour; 
  • Dakshi Kapugama Geeganage; 
  • Sareh Sadeghianasl; 
  • Sander J. J. Leemans; 
  • Kanika Goel; 
  • Robert Andrews; 
  • Moe Thandar Wynn; 
  • Arthur ter Hofstede; 
  • Trina Myers

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

Please cite as:

Rehan S, Eden R, Makasi T, Chukwudi I, Mamudu A, Kamalpour M, Kapugama Geeganage D, Sadeghianasl S, Leemans SJJ, Goel K, Andrews R, Thandar Wynn M, ter Hofstede A, Myers T

Digital Health Data Quality Issues: Systematic Review

J Med Internet Res 2023;25:e42615

DOI: 10.2196/42615

PMID: 37000497

PMCID: 10131725

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