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Health Information Technology and Healthcare Information System01:30

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Common data quality elements for health information systems: a systematic review.

Hossein Ghalavand1, Saied Shirshahi2, Alireza Rahimi2

  • 1Department of Medical library and Information Science, Abadan University of Medical Sciences, Abadan, Iran. Hosseinghalavand@gmail.com.

BMC Medical Informatics and Decision Making
|September 2, 2024
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Summary

This study identified 14 common data quality dimensions for health information systems, highlighting Accuracy, Completeness, and Timeliness as most critical. Standardizing these dimensions is crucial for consistent evaluation.

Keywords:
Data qualityHealth Information SystemSystematic review

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Area of Science:

  • Health Informatics
  • Information Systems
  • Data Management

Background:

  • Health information systems (HIS) data quality is complex, with multiple dimensions.
  • Identifying common data quality elements is essential for HIS improvement.

Purpose of the Study:

  • To identify and categorize common data quality dimensions for health information systems.
  • To address the lack of uniformity in evaluating HIS data quality.

Main Methods:

  • Conducted a comprehensive literature review across multiple scientific databases.
  • Screened 760 papers, with 58 selected after rigorous abstract and full-text review.

Main Results:

  • Identified 14 key data quality dimensions: Accuracy, Consistency, Security, Timeliness, Completeness, Reliability, Accessibility, Objectivity, Relevancy, Understandability, Navigation, Reputation, Efficiency, and Value-added.
  • Accuracy, Completeness, and Timeliness emerged as the most frequently cited dimensions in the literature.

Conclusions:

  • A lack of uniformity exists in current HIS data quality dimensions and evaluation methods.
  • Standardizing the definition and assessment of data quality dimensions is imperative for consistent HIS evaluation.