Digital Health Data Quality Issues: Systematic Review.

ABSTRACT:

Background

The promise of digital health is principally dependent on the ability to electronically capture data that can be analyzed to improve decision-making. However, the ability to effectively harness data has proven elusive, largely because of the quality of the data captured. Despite the importance of data quality (DQ), an agreed-upon DQ taxonomy evades literature. When consolidated frameworks are developed, the dimensions are often fragmented, without consideration of the interrelationships among the dimensions or their resultant impact.

Objective

The aim of this study was to develop a consolidated digital health DQ dimension and outcome (DQ-DO) framework to provide insights into 3 research questions: What are the dimensions of digital health DQ? How are the dimension

SUBMITTER: Syed R 

PROVIDER: S-EPMC10131725 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature