AHIMA's 10 Characteristics of Data Quality

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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:


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