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: