Zillery Fortner , Product Advisor, QA/RA Life Sciences, Sparta Systems, a Honeywell company09.01.22
The analytics revolution has inundated the life sciences with data, and organizations must manage massive amounts of information daily. Access to this data is essential to making business-critical decisions and nurturing the health of your organization now and in the future. A single error in your data can be a recipe for disaster, with the impact felt throughout the business.
The future is trustworthy data and manual processes are not integrated, which is a risk not worth taking. Poor data can arise from replicating or transferring data—resulting in altered or partial information and leading to duplicate data, lost data, and poor decision-making. Poor data integrity practices can have regulatory and non-regulatory consequences like product approval suspensions, damage to reputation, lack of strategic insights, and criminal enforcement.¹
Organizations can prevent poor data integrity by following the ALCOA+ principles. Data Integrity refers to the quality of the data concerning accuracy and consistency. Various organizations have tried to define standards and frameworks to define data integrity. Among these standards, the one defined by the U.S Food and Drug Administration (FDA) is called ALCOA+.
Data integrity is an essential component of the industry’s responsibility to ensure the safety, efficacy, and quality of products and is a fundamental element of effective quality management.
According to Deloitte, regulatory bodies have elevated expectations in terms of data integrity and data quality. Good data practices improve data quality, enabling organizations to make more strategic decisions backed by data-driven insights and analytics.1
Data quality refers to the reliability of your data. This includes complete, unique, valid, timely, and consistent data. While they are two different ideas, maintaining data integrity is the first step toward achieving data quality.
Data integrity compliance safeguards patient safety and protects organizations from the financial consequences of enforcement action from the FDA, including product recalls, facility shutdown, import and distribution bans, and remediation costs.2
However, those using manual or siloed quality management processes will find meeting ALCOA+ data quality standards challenging. This is because of the risks posed by manual systems like human error, duplicate entries, and disparate data resulting from disconnected systems.
When a manufacturer relies on disparate, stand-alone systems that are not integrated and lack seamless data sharing, the resulting output of information is typically uncoordinated and outdated.
Life sciences manufacturers that use a digital, enterprise-wide platform for quality management that integrates with other critical systems (like ERP, LIMS, MES) and automates processes have the visibility and control needed to meet each of the nine ALCOA+ principles.
Immediate access to comprehensive and accurate data enables manufacturers to maintain regulatory compliance and identify and address issues faster to reduce costs, avoid recalls, and ensure patient safety.
A centralized, cloud-based system puts organizations in a position to achieve ALCOA+ compliance and reduce manual effort. Most importantly, it enables organizations to use the data efficiently to improve decision-making across the enterprise.
Integration: Because the QMS (quality management system) integrates with many other systems that a quality team needs for quality management, they can perform tasks in collaboration with relevant stakeholders, including research and development (R&D) and suppliers, on a single platform.
This aligns with the following ALCOA+ elements:
This meets the following principles:
Trustworthy data is the key to a company’s future survival. Data-driven organizations understand the impact data has on their success. Lack of data integrity can lead to poor decision making, damage brand reputation, have a financial impact, and affect product and patient safety. Get a hold of your data by following the ALCOA+ principles with the help of a digital QMS.
It is not enough to have visibility into your data. Data integrity relies on data that is accurate and complete and the process will provide you with high-quality data that can be used to make critical business decisions, benefiting you now and in the future.
The bottom line is that data integrity is more than an elaborate system that guides crucial decisions and workflows; it is the method your industry uses to ensure and maintain the data and is essential to shaping the future of the life sciences industry.
References
Zillery A. Fortner is the Product Advisor, QA/RA Life Sciences at Sparta Systems, a Honeywell company. She earned a bachelor’s degree in health science from South University. Fortner has 20 years of experience in the medical device arena related to quality assurance, regulatory affairs, and JACHO. She served 10 years in the military as a certified surgical technician. Fortner is an active member of ASQ and AAMI.
The future is trustworthy data and manual processes are not integrated, which is a risk not worth taking. Poor data can arise from replicating or transferring data—resulting in altered or partial information and leading to duplicate data, lost data, and poor decision-making. Poor data integrity practices can have regulatory and non-regulatory consequences like product approval suspensions, damage to reputation, lack of strategic insights, and criminal enforcement.¹
Organizations can prevent poor data integrity by following the ALCOA+ principles. Data Integrity refers to the quality of the data concerning accuracy and consistency. Various organizations have tried to define standards and frameworks to define data integrity. Among these standards, the one defined by the U.S Food and Drug Administration (FDA) is called ALCOA+.
ALCOA+ in Data Integrity
FDA defines data integrity as the completeness, consistency, and accuracy of data. Complete, consistent, and accurate data should be attributable, legible, contemporaneously recorded, original, and accurate—and also be complete, consistent, enduring, and available (ALCOA+).Data integrity is an essential component of the industry’s responsibility to ensure the safety, efficacy, and quality of products and is a fundamental element of effective quality management.
According to Deloitte, regulatory bodies have elevated expectations in terms of data integrity and data quality. Good data practices improve data quality, enabling organizations to make more strategic decisions backed by data-driven insights and analytics.1
Data quality refers to the reliability of your data. This includes complete, unique, valid, timely, and consistent data. While they are two different ideas, maintaining data integrity is the first step toward achieving data quality.
Data integrity compliance safeguards patient safety and protects organizations from the financial consequences of enforcement action from the FDA, including product recalls, facility shutdown, import and distribution bans, and remediation costs.2
ALCOA+ Overview and Compliance
The ALCOA+ principles set the standards for data quality and are central to the FDA’s Current Good Manufacturing Practices (CGMP). Life sciences manufacturers must meet the nine elements of ALCOA+ to be compliant.However, those using manual or siloed quality management processes will find meeting ALCOA+ data quality standards challenging. This is because of the risks posed by manual systems like human error, duplicate entries, and disparate data resulting from disconnected systems.
When a manufacturer relies on disparate, stand-alone systems that are not integrated and lack seamless data sharing, the resulting output of information is typically uncoordinated and outdated.
Life sciences manufacturers that use a digital, enterprise-wide platform for quality management that integrates with other critical systems (like ERP, LIMS, MES) and automates processes have the visibility and control needed to meet each of the nine ALCOA+ principles.
Immediate access to comprehensive and accurate data enables manufacturers to maintain regulatory compliance and identify and address issues faster to reduce costs, avoid recalls, and ensure patient safety.
A centralized, cloud-based system puts organizations in a position to achieve ALCOA+ compliance and reduce manual effort. Most importantly, it enables organizations to use the data efficiently to improve decision-making across the enterprise.
Achieving ALCOA+ Compliance with a Quality Management System
Here is a breakdown of how an enterprise quality management system (EQMS) will enable life sciences and manufacturers to achieve ALCOA+ compliance.Integration: Because the QMS (quality management system) integrates with many other systems that a quality team needs for quality management, they can perform tasks in collaboration with relevant stakeholders, including research and development (R&D) and suppliers, on a single platform.
This aligns with the following ALCOA+ elements:
- Original and Contemporaneous: A quality team can perform its tasks within the QMS from development to approval, execution, and documentation. The result is data that is original and recorded contemporaneously, at the time the task is taking place.
- Legible, Accurate, and Attributable: With a single source of truth for quality management processes and data, where data from integrated systems flow into the platform, there is no copying or pasting of data from other sources, which increases data accuracy and ensures legibility. The QMS captures the original data sources, attributing the information to a specific system.
- Attributable: In the QMS, an audit trail includes user ID, old and new values, and time stamp. Whenever a new entry is made or an existing entry is modified or deleted, the QMS attributes the change to a user and records when and where the change was made.
- Complete and Enduring: The audit trail maintains a full record of activity in the QMS, including any reanalysis performed. Nothing is ever permanently deleted, even when a record change is made. Users can access the audit trail to see a complete history of all activities.
- Contemporaneous and Consistent: Because the audit trail is always running in the background, it documents activity as it happens, ascribing a date and time stamp in chronological order.
- Available: With all information recorded and tracked within the platform, data is available for review, audit, or inspection over the lifetime of the record.
This meets the following principles:
- Available: Quality data is always available to users through the system wherever and whenever they need it.
- Attributable: The QMS attributes actions to the user who performed them, from internal quality management team members to external suppliers, whether they use the platform from their desktop or a mobile device.
- Original and Contemporaneous: Because users can access the QMS via mobile devices, they can record original information about tasks as they are taking place, whether within the company's four walls or halfway around the world.
- Accurate: Direct data input into the QMS drives greater data accuracy than users having to record details after the fact.
- Available: With flexible reporting, QMS users can access information relevant to their specific needs, from a high-level view of process performance to more granular on a particular corrective action, and delivered on a pre-set schedule.
- Legible: The QMS enables the recording and reporting of information in readable terms per 21 CFR Part 11 regulations.
Trustworthy data is the key to a company’s future survival. Data-driven organizations understand the impact data has on their success. Lack of data integrity can lead to poor decision making, damage brand reputation, have a financial impact, and affect product and patient safety. Get a hold of your data by following the ALCOA+ principles with the help of a digital QMS.
It is not enough to have visibility into your data. Data integrity relies on data that is accurate and complete and the process will provide you with high-quality data that can be used to make critical business decisions, benefiting you now and in the future.
The bottom line is that data integrity is more than an elaborate system that guides crucial decisions and workflows; it is the method your industry uses to ensure and maintain the data and is essential to shaping the future of the life sciences industry.
References
Zillery A. Fortner is the Product Advisor, QA/RA Life Sciences at Sparta Systems, a Honeywell company. She earned a bachelor’s degree in health science from South University. Fortner has 20 years of experience in the medical device arena related to quality assurance, regulatory affairs, and JACHO. She served 10 years in the military as a certified surgical technician. Fortner is an active member of ASQ and AAMI.
