Quality data are at the heart of quality healthcare. It is well known that poor data can lead to incorrect diagnoses, prescription errors, or surgical errors with tragic consequences. Similarly, the day-in, day-out consequences of poor data are enormous as well, leading to added time and expense throughout the system. In short, improving data quality is essential.

There are many approaches to defining data. The one that is often used for data quality recognizes that data consist of two interrelated components: data models and data values. Data models define entities, which are real-world objects or concepts, attributes, which are characteristics associated with entities, and relationships among them. As an example, each reader is an entity, and his or her employer is interested in attributes such as ...

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