HMIS DATA QUALITY (CHAPTER 8; PREFINALS) Flashcards
CRM
CUSTOMER RELATIONSHIP MANAGEMENT
the overall utility of a dataset as a function of its ability to be processed easily and analyzed for a database, data warehouse, or data analytics system
DATA QUALITY
aspects of data quality
1) ACCURACY
2) COMPLETENESS
3) UPDATE STATUS
4) RELEVANCE
5) CONSISTENCY
6) RELIABILITY
7) APPROPRIATE PRESENTATION
8) ACCESSIBILITY
can be done to raise the quality of available data
DATA CLEANSING
a tool that allows the use of small random samples to distinguish between different groups of data elements (LOTS) with high and low data quality
LOT QUALITY ASSESSMENT SAMPLING (LQAS)
LQAS technique has been adopted in the context of what data quality assurance
DISTRICT HEALTH INFORMATION SYSTEM (DHIS)
a simplified version of the Data Quality Audit (DQA); allows programs and projects to verify and assess the quality of reported data; aims to strengthen their data management and reporting systems
ROUTINE DATA QUALITY ASSESSMENT (RDQA) TOOL
objectives of RDQA
1) VERIFY RAPIDLY
2) IMPLEMENT
3) MONITOR
a project management tool that shows how a project will evolve at a high level; helps ensure that a development team is working to deliver and complete tasks on time
IMPLEMENTATION PLAN
analyzes information and identifies incomplete or incorrect data
DATA QUALITY TOOL
data quality tools
1) PARSING AND STANDARDIZATION
2) GENERALIZED “CLEANSING”
3) MATCHING
4) MONITORING
5) ENRICHMENT
ETL stands for:
EXTRACT, TRANSFORM, LOAD
integrate profiling, parsing, standardization, cleansing, and matching processes
DATA QUALITY MANAGEMENT (DQM)
a class of problem-solving methods aimed at identifying the root causes of the problems or events instead of simply addressing the obvious symptoms; use systematic ways
ROOT CAUSE ANALYSIS
practically done by identifying the problem at hand and progressively unveiling the underlying causes by asking “why” five times
ASK “WHY” 5 TIMES
technique used to identify the modes in a system failure
FAILURE MODE AND EFFECTS ANALYSIS (FMEA)
based on the Pareto principle, which states that 20% of the work creates 80% of the results; helpful when there are multiple causes to a problem
PARETO ANALYSIS
In Pareto Analysis, how many percent of the causes involved in the problem should the table reflect
80%
diagram shaped like an inverted tree; commonly used in risk analysis and safety analysis; starts by identifying the undesirable result and placing it at the top of the diagram
FAULT TREE ANALYSIS
in Fault Tree Analysis, root causes of an undesirable event are determined using this logic
BOOLEAN LOGIC
used to get to the root causes of all problems in a system all at once
CURRENT REALITY TREE (CRT)
what is the first step in CRT
identify the problem
are used in charting problems
‘IF-THEN’ STATEMENTS
other term for Fishbone diagram
ISHIKAWA/CAUSE-AND-EFFECT DIAGRAMS
