Developing a Framework for Data Quality Assurance in Electronic Health Record (EHR) Systems in Healthcare Institutions

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@article{1709252,
      author = {Damilola Oluyemi Merotiwon, Opeyemi Olamide Akintimehin, Opeoluwa Oluwanifemi Akomolafe},
      title = {Developing a Framework for Data Quality Assurance in Electronic Health Record (EHR) Systems in Healthcare Institutions},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {12},
      pages = {335-349},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709252.pdf},
      abstract = {The accuracy, completeness, and reliability of Electronic Health Records (EHRs) are foundational to delivering safe, effective, and coordinated healthcare. As digital health infrastructures evolve, challenges related to inconsistent data entry, fragmented systems, and variable institutional standards have heightened the need for robust data quality assurance (DQA) frameworks. This paper proposes a comprehensive, multidimensional framework designed to ensure data integrity in EHR systems across healthcare institutions. The framework integrates technical, organizational, and governance dimensions of data quality and aligns with global standards such as HL7, ISO/TS 18308, and the WHO?s data quality review guidelines. Employing a mixed-methods approach incorporating a systematic review of 105 peer-reviewed sources (2010?2020), expert interviews, and case analysis across 15 hospitals?the study identifies core quality indicators (e.g., timeliness, validity, consistency), evaluates the impact of poor-quality EHRs on clinical outcomes, and validates the proposed model using simulation data. Key findings indicate a 37% improvement in diagnostic accuracy and a 25% reduction in duplicate testing when the framework is applied. This study contributes to the informatics and public health literature by presenting a scalable, standards-driven model applicable in both high-resource and low-resource healthcare settings. The framework also provides actionable strategies for policymakers, health IT vendors, and clinical data stewards seeking to strengthen EHR performance and health system interoperability.},
      keywords = {Data Accuracy, Data Completeness, Health Interoperability, EHR Governance, Clinical Informatics, Health Compliance},
      month = {June},
  }