Download Quality Assurance Program Presenter: Erin Mustain 1

Quality Assurance Program
Presenter: Erin Mustain
1
Recommendation 5
Benchmarks

Data quality issues have been categorized and quantified.

A detailed plan exists for addressing sources of continuing
errors and correcting historical errors.

The plan has been validated with representative data samples

Substantive progress has been made toward correcting major
categories of errors.

The Steering Committee agrees that progress is being made
and that there is a high probability that existing data problems
will be resolved.
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Progress
 Institutionalized
 Business Rules
 Error chart
Quality Assurance
 Steering
committee and User groups
collaboration
 Eliminated system-generated
violations for paper tracking SMRs
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Total Study
Error
Data Population
Migration
Manual Data
Entry
Business
Rules not
followed
Field autopopulated
incorrectly
Typos
Difficulty
Data
Mining
Selecting
the wrong
link
Data doesn’t
follow
business
rules
Training
System
Limitations
Field not
populated
Field not
appearing
Data Generation
Duplicate
entry
Non-numeric data
(ND, QND, etc.) not
handled by eSMR
System can’t
handle unique
orders (several
facilities under one
permit)
No place to store
data (enrollee
history)
SMRs
Training
Manuals
don’t follow
Business
Rules
Instruction
not
consistent
Lack of
Training
Manual
Lab
errors
Sampling
Errors
Errors in
data entry
form
Calculation
errors
Intentional
manual
errors
Doesn’t enforce all
of the Business
Rules
Can’t easily delete
records
Data entered
into SWIM
incorrectly
System generated
duplicates (SMARTS)
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Current vs. Historical
Data
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What decisions will be
made with this
data?
SOPs
QAP
Audits
Data
Validation
DQOs
Business rules
CIWQS
QA
Program
Data
Verification
Data
Cleanup
Training
Communication
Corrective
Action
Integration with
State Water Board
QMP
QA
Reports
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Plan and Procedures
 Quality
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Assurance Plan
Scope
Roles and responsibilities
Data quality indicators
Quality objectives
Assurance activities
Problem reporting and corrective action
Audits
Migration and future projects
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Plan and Procedures
 Standard

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Operating Procedures
Data Cleanup
Training
Document Management
Corrective Action
Quality Assurance Reports
Audit
End-user-layer enhancements and testing
Database enhancement prioritization
Report prioritization
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Plan and Procedures
 DIT Standard Procedures Document
 Maintenance & Documentation Requirements
 System Environment
 Data model, database, data integration, &
maintenance
 Application source code integration &
maintenance
 Application and database source code & scripts
repository CVS Database tools & scripts
standards
 Issue routing
 Maintenance implementation
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External Audit
Onsite audit of
Regional Boards and
State Board programs
Policies and
procedures for data
entry
Onsite audit of
Division of Information
Technology
Security, performance,
and policies and
procedures
Data audit using
stratified random
design approach
Accuracy of records
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Next Steps

Quantifying the data quality issues – Audit

Correcting historical data – recommendations to
management after audit results

Validate the QAP and SOPs with representative data
samples

Implement training program

Continuing process improvement at all levels (QA
Program is not static)

Establish a mechanism for communication between
QA Program and panel
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