Data Integrity

Data Integrity Is Not A New Problem

Since the inception of the production Batch Record, data integrity has been an issue. Before Supervisory Control and Data Acquisition (SCADA), Electronic Batch Record (EBR), and Manufacturing Execution Systems (MES), a production batch record was the official document to confirm a product was produced based on a defined process. How a Batch Record was designed determined the effectiveness of how process(s) were documented and could provide insight into how well an organization managed these process(s).

As FDA inspection activity and scrutiny increased, industry responded by adding more complexity to Batch Records. This complexity incorporated non-value-added steps, with workflow inconsistencies and unnecessary redundancy, leading to missed cGMP requirements, and causing support system interface issues. Associated work procedures (SOPs) often did not align with the Batch Record or workflow and were written without user input. Supporting systems like Laboratory Information and Electronic Document Management Systems were slowly evolving.

In 1997, to comply with 21 CFR Part 11, companies saw an opening and jumped on EBR as the solution for human errors, data integrity, batch release, and system interface issues with MRP, SCADA, LIMS, and EDMS.

Over 20 years later, even with FDA guidance, lapses in data integrity has expanded throughout organizations. Questionable documentation practices and cGMP violations involving data integrity continue to increase as evidenced by the results of present-day FDA inspections.

In 2018, the most cited data integrity violations were associated with laboratory records, batch production and control records, testing and release for distribution records, production record review, and automatic, mechanical, and electronic equipment.

Data integrity issues linger when unnecessary redundancy and complexity make knowledge and data hard to understand and maintain. It is therefore vital to asses and understand the workflow (processes), real data requirements (manual and electronic), procedures, and employee competencies, before consistency and data accuracy can be improved.

Our Approach to Address Data Integrity Issues for Over 30 Years

We focus on REDUCING the complexity of Batch Records, data, SOPs, and supporting systems.

Our Batch Record redesign and simplification approach:

• Defines the rules and guidelines for Batch Record creation, workflow, data and documentation requirements (see our Batch Record guidance).
• Assesses and identifies process, workflow, and compliance gaps, (between what you need and what you have) and unnecessary redundancies.
• Tests and confirms the Batch Record and supporting system improvements.
• Provides justification history for improved changes to support routing and approval.
• Is first step to migrate from a paper-based system to MES/EBR, LIMS, and Data Acquisition and Monitoring systems.

Malcolm’s Simplification methodology prevents redundant representation of information, e.g. data (manual and electronic), Batch Records, forms, log books, procedures, labels, testing, methods, trends, etc.

Along with Batch Record simplification, Batch Record guidelines help to improve human knowledge and ensure complete, accurate, and consistent data that supports compliance with the ALCOA guidance.

ALCOA is:

• Attributable data explains the what, when, and who. What is the data about, who collected and documented the data, and when did the data documentation process take place?
• Legible data, in its original and duplicate form, is easily understood.
• Contemporaneous data is recorded in real-time and precisely accurate.
• Original data should be accessible from its original source.
• Accurate data is error-free and follows a defined protocol.