Data Quality in Health Care: Main Concepts and Assessment Methodologies

Area of Science:

• Healthcare Informatics
• Data Management
• Health Services Research

Background:

• Healthcare generates vast amounts of data daily.
• Challenges in data collection, storage, sharing, and analysis lead to incomplete, inaccurate, and untimely health data.
• Data quality issues are increasingly recognized as critical concerns.

Purpose of the Study:

• To define data quality in healthcare.
• To identify key dimensions of data quality.
• To review methodologies for assessing health data quality.

Main Methods:

• A scoping literature review was conducted.
• Relevant articles published between January 1, 2012, and September 31, 2022, were identified.
• Narrative reporting of findings from 23 included studies.

Main Results:

• Data quality dimensions and assessment methodologies vary significantly across studies.
• Quantitative methods, applied to both paper-based and electronic health records, were predominantly used.
• Few studies explored respondent perceptions of data quality.

Conclusions:

• High-quality health data is essential for patient care, service improvement, and informed decision-making.
• Implementing technical and non-technical solutions is recommended.
• Continuous assessment and supervision are vital for maintaining data quality.