What term best describes a comprehensive and systematic review of patient data to ensure accuracy?

The term that best describes a comprehensive and systematic review of patient data to ensure accuracy is "Data Audit." This process involves a thorough examination of data to assess its accuracy, completeness, and overall quality. Audits typically involve verification of the collected data against original sources or expected standards, making it a critical aspect of ensuring that the information used for decision-making and reporting is reliable.

A data audit goes beyond simple checks and engages in a structured approach that can identify inconsistencies, errors, or areas for improvement in data management processes. This systematic approach helps healthcare organizations maintain high standards of data quality, which is essential in a field where decisions can significantly impact patient care and outcomes.

While the other terms also pertain to data accuracy and quality, they do not encompass the full scope of a comprehensive review. For instance, a data integrity check may involve examining specific aspects of data accuracy but lacks the broad systemic approach that defines an audit. Quality assurance could be more about overall processes and practices and may not specifically focus on the data review itself. Data validation typically refers to the process of ensuring that data input is correct and meaningful but does not include the depth of review associated with an audit.