HMIS DATA QUALITY Flashcards
The overall utility of a dataset(s) as a function of its ability to be processed easily and analyzed for a database, data warehouse, or data analytics system
DATA QUALITY
Perception of the data’s
appropriateness to serve its
purpose in a given context
data quality
aspects of data quality
accuracy accessibility appropriate presentation completeness consistency relevance reliability update status
LQAS means
LOT QUALITY ASSESSMENT SAMPLING
Tool that allows the use of small random samples to distinguish between different groups of data elements with high and low data quality
LOT QUALITY ASSESSMENT SAMPLING
RDQA means
ROUTINE DATA QUALITY ASSESSMENT
Simplified version of the Data Quality Audit (DQA) which allows programs and projects to verify and assess the quality of their reported data
ROUTINE DATA QUALITY ASSESSMENT
RDQA
RDQA OBJECTIVES
- verify rapidly
- implement
- monitor
the quality of reported data for key indicators at selected sites and the ability of data-management systems to collect, manage, and report quality data
verify rapidly
corrective measures with action plans (one of RDQA Objectives)
implement
capacity improvements and performance of the data management and reporting system to produce quality data (under RDQA objectives)
monitor
A project management tool that shows how a project will evolve at a high level
IMPLEMENTATION PLAN
Helps ensure that a development team is working to deliver and complete tasks on time
IMPLEMENTATION PLAN
IMPLEMENTATION PLAN KEY
CONCEPTS
(1) Define Goals/Objectives
(2) Schedule Milestones
(3) Allocate Resources
(4) Designate Team Member Responsibilities
(5) Define Metrics for Success
Answers the question
“What do you want to accomplish?”
Define Goals/Objectives:
Outline the high level
schedule in the implementation phase.
• Schedule Milestones:
Determine whether you
have sufficient resources, and decide how you will
procure what’s missing.
Allocate Resources
Create a general team plan with the overall roles that each team member will play.
Designate Team Member Responsibilities
How will you determine if you have achieved your goal?
Define Metrics for Success:
ANALYZES INFORMATION AND
IDENTIFIES INCOMPLETE OR
INCORRECT DATA
DATA QUALITY TOOL
refers to the decomposition of fields into component parts and formatting the values into consistent layouts based on industry standards and patterns and user-defined business rule
Parsing and Standardization
- Modification of data values to meet domain restrictions
- Constraints on the integrity of other rules that define data quality as sufficient for the organization
generalized “cleansing”
This is the identification and merging related entries within or across data sets
matching
Refers to the analysis of data to capture statistics or metadata to determines the quality of the data and identify data quality issues
profiling