Cultivating Data Quality in Healthcare: Strategies, Challenges, and Impact on Decision-Making

Manaswini Davuluri

Abstract


In the healthcare sector, data quality plays a critical role in shaping patient care, operational efficiency, and decision-making processes. This study explores the strategies healthcare organizations can adopt to enhance data quality, the challenges they face in maintaining accurate and reliable data, and the impact of high-quality data on clinical and administrative decision-making. The research delves into the importance of data governance, data integration, and continuous monitoring to ensure that data is both accurate and accessible. It highlights key issues such as data silos, inconsistencies, and the complexities of integrating data from diverse healthcare sources, including electronic health records (EHRs), medical devices, and wearables. The paper also discusses how leveraging advanced analytics and machine learning can help healthcare providers derive actionable insights from high-quality data, leading to better clinical outcomes, improved patient experiences, and cost-efficiency. By addressing these challenges and implementing robust data management strategies, healthcare organizations can foster a data-driven culture that supports more informed, timely, and effective decision-making across all levels of care.


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References


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