Data quality and hygiene are essential in healthcare as organizations make use of artificial intelligence (AI) and machine learning (ML) to uncover new insights. Data hygiene ensures that data is clean and consistent, free from duplicates and errors. Poor data quality can cost organizations millions and lead to inefficiencies. Clean data is crucial for accurate analytics and algorithms, such as risk score analyses and clinical trial recruitment. Additionally, AI must be used to assist healthcare decisions and not replace human expertise. Moving forward, the convergence of clean data, AI, and human expertise will drive advancements in patient care and resource management in healthcare.
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Data-Driven Transformation: The Role of Data Quality in Accelerating Healthcare Performance
