AHIMA Data Quality Model

The American Health Information Management Association

Data Quality Characteristics

1. Data Accuracy

The data reflect correct, accurate and valid values.

2. Data Accessibility

Data is available to decision makers.

3. Data Comprehensiveness

All of the data required for a decision are available.

4. Data Consistency

Data are consistent.

5. Data Currency

Data are current and not obsolete.

6. Data Definition

Clear definitions of data elements are available for current and future users.

7. Data Granularity

Data atomicity; cannot be divided further.

8. Data precision

Closeness to actual size, weight or other standard of a particular measurement.

9. Data relevancy

Data must relevant to the purpose (e.g. hair color in oncology is not relevant).

10. Data timeliness

Producing accurate results too late has little or no value to the patient.

Wager, K. A., Lee, F. W., Glaser, J. P., & Wager, K. A. (2009). Health care information systems: A practical approach for health care management. San Francisco, CA: Jossey-Bass.

p. 178-184