Data Quality Management Model

Data applications
The purpose for which data is collected
Data collection
The process by which data is collected
Data warehousing
The process and systems by which data are archived
Data analysis
The process by which data are translated into information that can be used for designated application
Data Quality Management Mode
Is based on 4 domains
Data Applications
Data Collection
Data warehousing
Data Analysis
10 Characteristics for the 4 domains
Accuracy Accessibility
Comprehensiveness Consistency
Currency Definition
Granularity Precision
Relevancy Timeliness
Data accuracy
All data is correct
Data accessibility
Easily accessed when needed
Data comprehensiveness
All required elements are in the record. It is complete
Health record should include
Patient identification
Consents for treatment
Advance directives
Problem list
Diagnoses
Clinical history
Diagnostic test results
Treatments and outcome
Conclusions and follow up requirements
Data Consistency
Data is reliable, the same across applications and systems
Data Currency
Healthcare data is current
Data Timeliness
Data is being recorded at or near the time of the event.(this has legal ramifications if not followed)
Data Definition
Data and information documented in the health record is defined. Users must be able to understand what the data is and what it represents. Every data element should have a clear definition and range of acceptable values
Data Granularity
The attributes and values of data be defined at the correct level of detail for the intended use of the data
Data Precision
Expected data values
Ie: data definition related to gender would include 3 values: male, female and unknown
Data Relevancy
Data in the health record is useful // easily interpretable format