Trend Analysis: Making the Most of Meaningful Quality Data
NOTE: Master Control GxP Lifeline first published article on November 13, 2020. Click here to read the original publication.
Every life sciences company’s quality department generates and consumes a seemingly infinite amount of data. It’s the fuel that feeds the quality engine. Yet meaningful, current and high-quality data is difficult to come by. Still, good data is the key to effectively analyzing quality trends and sparking changes that stimulate business improvements.
The Purpose of Trend Analysis in Quality Management
Trend analysis in quality management is especially useful for monitoring process changes, particularly for activities indirectly related to manufacturing. These assessments inform risk-based decisions, primarily those to determine whether an issue should be escalated to a formal corrective and preventive action (CAPA).
Common applications of CAPA trending analysis include quality processes and outputs such as:
- Customer complaints.
- Audit findings.
- Maintenance and service reports.
Trend Analysis Methods Used in Quality Management
There are two types of trend analysis methods typically used to assess quality in life sciences manufacturing:
- Process trending.
- Performance trending.
Both methods entail the use of statistically based control charts for monitoring processes and activities. Trend analysis control charts are commonly formulated to monitor limits for relevant thresholds, actions or alerts. In a recent Pharmaceutical Online article, Mark Durivage, American Society of Quality (ASQ) fellow and managing principal consultant of Quality Systems Compliance LLC, outlined two general classifications of control charts that life sciences manufacturers should employ for trend analysis in quality control:
- Variables charts: Used to assess aspects that can be measured (e.g., weight, temperature, length, etc.).
- Attributes charts: Used for anything that can be quantified or rated as pass/fail. (1)
The limits recorded in these charts should first and foremost be consistent, according to Durivage. They should also be dictated by regulatory requirements, industry best practices and the organization’s risk acceptance thresholds.
“There is no one perfect way to analyze data trends,” Durivage wrote. “However, for a trending program to be successful, consistency is important. Pick a method and stick with it.”
Enhancing Trend Analysis With Advanced Digital Tools
Despite the obvious and wide-ranging advantages of digital quality management system (QMS) solutions, far too many companies continue to manually enter trending data into spreadsheets that are maintained in disparate systems. Is your company one of these organizations that is still reliant on disconnected systems and time-consuming manual reporting processes? If so, it’s likely you relate with the following scenario that’s all too familiar for most life sciences companies: In preparation for an upcoming quarterly management review session, your team works for weeks to create a presentation that will inform management about the state of quality in your organization. By the time the information has passed through multiple systems, spreadsheets and reviewers and configured in a user-friendly format, the reports are outdated.
Analyzing trends with attributes and variables charts can help you tell an accurate story about your organization’s performance, but getting those charts to reflect a comprehensive and exact “pulse check” of quality performance depends on your organization’s ability to extract data that is current, comprehensive and accurate. If you expect immediate and continual access to up-to-date trend analysis data, you need an integrated QMS platform that’s up to the task.
Platforms are the remedy for outdated trend analysis data. In a recent webinar titled “Using Big Data to Take Quality Beyond Compliance,” MasterControl Product Management Director Sue Marchant explained how digital platforms that feature robust trend analysis capabilities are the ultimate mechanism for connecting data and elevating performance.
“We have so much information across the entire product life cycle. We need to be able to access and analyze it in our quality data platforms, and we need to be able to extract meaning and actionable, predictive insight that helps us to transform our business practices,” Marchant said. “Ideally, that extraction of meaning isn’t work your individual organization will have to take on — that should be the work of your QMS partner. Your job will be to ensure that you’re adopting the right platforms and processes, and giving your people access to tools that are tailored to their specific needs and concerns.” (2)
The next generation of advanced QMS platforms are now enabling organizations to successfully leverage quality data intelligence via prescriptive and predictive models that facilitate real-time trend analysis, according to Marchant. She believes that when decisionmakers can rely on an advanced platform to provide extensive trend analysis data, they’re consistently prepared to make informed judgment calls that are based on facts rather than gut feel.
“When you’re effectively leveraging the data intelligence, you understand the past, you know what’s happening today and you understand what your future looks like,” she said. “You know how to improve, how to be more productive and how to beat your competition.”
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