Location

Grand Rapids, Michigan

Start Date

16-5-2024 10:30 AM

End Date

16-5-2024 11:00 AM

Description

Data Quality Assessment of a Long Running QA Program – The Domino Effect of a Pandemic Authors Ms. Amanda Cover - United States - Environmental Standards Mr. Rock Vitale - United States - Environmental Standards Ms. Jennifer Gable - United States - Environmental Standards Ms. Veronica Barredo - United States - TVA Abstract Keywords: Quality Assurance, Data Quality It should be no secret that a full-cycle quality assurance (QA) program for Groundwater Monitoring Programs establishes a “well-oiled machine” that results in high quality, legally defensible data sets that can be reliably used to make critical decisions. Under normal conditions, a QA program will encounter and resolve laboratory analytical issues at a relatively low frequency -- but what happens when laboratories encounter significant obstacles beyond their control? The QA program goes into overdrive. This presentation will discuss the data quality trends observed over a five-year period and the challenges presented during and after a global pandemic. This presentation will provide a case study of changes in frequency of QA issues due to external challenges caused by the pandemic. This presentation will also highlight the benefits of a robust QA program which identified and corrected data quality issues through stringent technical requirements, laboratory audits, and critical data validation.

Document Type

Presentation

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May 16th, 10:30 AM May 16th, 11:00 AM

The Domino Effect of a Pandemic-​ Data Quality Impact to a Full Cycle QA Program

Grand Rapids, Michigan

Data Quality Assessment of a Long Running QA Program – The Domino Effect of a Pandemic Authors Ms. Amanda Cover - United States - Environmental Standards Mr. Rock Vitale - United States - Environmental Standards Ms. Jennifer Gable - United States - Environmental Standards Ms. Veronica Barredo - United States - TVA Abstract Keywords: Quality Assurance, Data Quality It should be no secret that a full-cycle quality assurance (QA) program for Groundwater Monitoring Programs establishes a “well-oiled machine” that results in high quality, legally defensible data sets that can be reliably used to make critical decisions. Under normal conditions, a QA program will encounter and resolve laboratory analytical issues at a relatively low frequency -- but what happens when laboratories encounter significant obstacles beyond their control? The QA program goes into overdrive. This presentation will discuss the data quality trends observed over a five-year period and the challenges presented during and after a global pandemic. This presentation will provide a case study of changes in frequency of QA issues due to external challenges caused by the pandemic. This presentation will also highlight the benefits of a robust QA program which identified and corrected data quality issues through stringent technical requirements, laboratory audits, and critical data validation.