Which dimension of data quality is described as "data that is free of errors"?

The dimension of data quality that is described as "data that is free of errors" is accuracy. Accuracy refers to the extent to which data correctly reflects the real-world situation or truth that it is intended to represent. High accuracy means that the information has been collected and recorded correctly, without any mistakes or inaccuracies that could mislead users or analysts. This is crucial in healthcare data, where decisions based on flawed information can lead to serious consequences.

In the context of the other dimensions, validity refers to whether the data meets the specific rules and standards set forth for that data, such as being in an acceptable format. Completeness relates to whether all necessary data is present; missing data can lead to gaps in information. Consistency ensures that the data is stable and corroborates across different datasets or records. While these aspects are also vital for overall data quality, accuracy is specifically focused on the error-free nature of the data, making it the correct choice in this scenario.