ABSTRACT

Completeness is a measure that in healthcare is primarily directed at missing data. Auditability can be improved by addressing incorrect and missing data anomalies and by following data governance practices that can minimize the introduction of data issues into the healthcare data set. Data governance, at its simplest, is the set of concepts, processes, and mechanisms that provides a standardized focus on data quality for an organization. Data integrity is the maintenance, and the assurance, of the accuracy and consistency of data over its entire life cycle and is a critical aspect of the design, implementation, and usage of any system that stores, processes, or retrieves data. Many issues with the accuracy and interpretation of data are related to problems with the definition of data terms. Data that is inaccurate, inconsistent, or incomplete will be of low or even no relevance depending on the degree of error exhibited.