In the age of AI, healthcare data quality is paramount. Accurate, complete, and relevant data ensures effective healthcare analytics, leading to better patient outcomes. Poor data quality can result in incorrect diagnoses and ineffective treatments, posing risks to patients and providers. By addressing data quality issues, healthcare managers can leverage AI and data analytics to enhance performance and outcomes. Key dimensions of data quality include accuracy, completeness, consistency, relevance, and integrity.
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