Philadelphia – Linda B. Sullivan, MCC’s Co-Founder & President, generated a lot of conversation after her presentation, Apply the Total Cost of Quality Model to Clinical Trials to Quantify the Cost of Poor Quality to Gain Insights About Investing in Quality, and how the MCC Cost of Poor Quality (CoPQ) Estimator Tool can help during the Clinical Performance Metrics Summit, December 4, 2017.
Stressing that the cost of quality matters, Sullivan described the Total Cost of Quality Model as investing in quality through value-added prevention and appraisal activities (e.g. quality by design, in-process checks, scheduled audits, inspection, reviewing reports, monitoring) and reducing non value-added activities (e.g. major protocol amendments, non-enrolling sites, data queries, subject dropouts, “fire-fighting” activities).
“The Cost of Quality Model has been used by many industries as a tool to balance investing in quality versus fixing quality problems when they occur,” said Sullivan. “It is time for the drug development industry to use the Cost of Quality Model to help them make quality investment decisions.”
Acknowledging that quantifying the cost of poor quality can be difficult, Sullivan discussed the development and value of the MCC CoPQ Estimator Tool – an Excel-based tool developed with input from the MCC Study Quality Trailblazer Team Work Group. The CoPQ Estimator tool can be used to estimate the financial impact that poor quality has on study costs. Specifically, the tool considers three categories of poor quality costs:
- Direct, operational costs (16 items total)
- Cost of study extension (time x $)
- Delay to market costs
The flexible tool includes “default” values derived from industry studies for seven direct cost items, which users can override if company-specific data is available.
Click here to view Sullivan’s presentation and to learn more about the MCC Study Quality Trailblazer Team Work Group.
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