Data Quality-Driven Improvement in Health Care: Systematic Literature Review.

ABSTRACT:

Background

The promise of real-world evidence and the learning health care system primarily depends on access to high-quality data. Despite widespread awareness of the prevalence and potential impacts of poor data quality (DQ), best practices for its assessment and improvement are unknown.

Objective

This review aims to investigate how existing research studies define, assess, and improve the quality of structured real-world health care data.

Methods

A systematic literature search of studies in the English language was implemented in the Embase and PubMed databases to select studies that specifically aimed to measure and improve the quality of structured real-world data within any clinical setting. The time frame for the analysis was from January 1945 to June 2023. We

SUBMITTER: Lighterness A 

PROVIDER: S-EPMC11377907 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature