AHIMA's 10 Characteristics of Data Quality

definition

Clear definitions should be provided so that current and future data users know what the data means? Also, Each data element should have clear meaning and acceptable values:

relevancy

Data are meaningful to the performance of the process or application for which they are collected:

accessibility

Data items should be easily obtainable and legal to access:

consistency/reliability

Data quality needs to be consistent and reliable across applications:

currency

Data should be up to date:

accuracy

Data that is free from error. Ensuring that data are the correct values, valid, and attached to the correct patient record:

granularity

Individual data elements cannot be further subdivided. Attributes and values of data should be defined at the correct level of detail:

precision

Often relates to numerical data. It denotes how close to an actual size, weight, or other standard a particular measurement is:

comprehensiveness

Required data items are included and organizations must ensure that the entire scope of data is collected:

timeliness

Timeliness is determined by how the data are being used and their context: