Impact of Data Governance on Data Quality in Healthcare Institutions

Abstract

Purpose: The aim of the study was to assess the impact of data governance on data quality in healthcare institutions. Materials and Methods: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that institutions with robust data governance protocols experience fewer instances of data inconsistency and errors. This, in turn, improves the reliability of clinical decision-making processes and patient outcomes. Moreover, compliant data governance practices contribute to better data integration across various healthcare systems and departments, facilitating comprehensive patient care and longitudinal health monitoring. By promoting transparency and accountability in data management, healthcare institutions can mitigate risks associated with data breaches and ensure compliance with regulatory standards, thereby fostering trust among patients and stakeholders alike. Implications to Theory, Practice and Policy: Control theory, information theory and agency theory may be used to anchor future studies on assessing the impact of data governance on data quality in healthcare institutions. Healthcare institutions should prioritize the adoption of comprehensive data governance frameworks that integrate policy development, stakeholder engagement, and technological infrastructure. Policymakers should align regulatory frameworks with evolving data governance standards to promote interoperability and data exchange across healthcare networks.