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identified during the audits. Problems that could impact data quality are immediately communicated to
the Program Coordinator and the MERC Director.
The results of the ADQ will be documented in a formal audit report:
•
The draft ADQ report with the completed checklist will be submitted to the Program Coordinator
and MERC Director within 10 days of the ADQ.
•
The Program Coordinator audit response is due 10 working days from delivery of the ADQ
report.
•
The final ADQ, with audit responses, is due to MERC within 10 days of receiving the response.
The final report with Program Coordinator responses accepted by QA Manager will be signed and
archived in the MERC database.
10.2.3.4.
Data Validation
Data validation assesses the overall quality of a data set based on the MQOs. Data validation is initially
conducted by the MERC Program Coordinator during the data review process. The Program Coordinator
review includes verifying that:
•
the raw data records are complete, understandable, well-labeled, and traceable;
•
all data identified in the QAPP and Test Plan has been collected;
•
instrument calibration and QC criteria were achieved;
•
data calculations are accurate.
The Program Coordinator review may deem a data set unusable, questionable, or semi-quantitative, based
on the results of the QC data and achievement of the DQIs. Data validation is also conducted during the
ADQ when the MERC QA Manager reviews the data vs. QAPP/Test Plan requirements and assessed
overall data quality. The ADQ verifies a percentage of the reported data vs. raw data, including any
calculations. In addition, during the ADQ, the MERC QA Manager assesses, as appropriate:
•
data completeness;
•
sample handling, holding times, and integrity;
•
instrument calibration;
•
quality control;
•
documentation.
Any limitations on the data and recommendations for limitations on data usability are documented in the
data audit report.
10.2.3.5.
Data Quality Assessment
The MERC Program Coordinator assesses data usability during the review of test data. This assessment
includes a statistical and scientific evaluation of the data to determine the validity of the test design and
the performance of the technology versus the performance measures specified in the QAPP and Test Plan
design process. By using DQA, a reviewer can answer four important questions:
1.
Can a decision (or estimate) be made with the desired level of certainty, given the quality of the data?
2.
How well did the sampling design perform?
3.
If the same sampling design strategy is used again for a similar study, would the data be expected to
support the same intended use with the desired level of certainty?