Credible lab results depend on the quality and reliability of your data, regardless of which industry or function your lab serves. The complexities of ensuring data integrity can be overwhelming, but we are here to assist you and optimise your lab’s performance.
The final phase of the analytical process is perhaps the most critical stage for assuring data integrity. This is where raw data, factors, and dilutions come together to create reportable values, and labs must consider and respond to the potential for improper manipulation — in all its various forms.
There are a few critical choices to be made around calculation and reporting that impact compliance, the trustworthiness of results, and even the reputation of the lab.
No lab wants to go through all the work of setting up methods, conducting analysis and gathering data only for it to be for nought or at risk because the data integrity system wasn’t up to par. Here is our advice for maximising lab efficiency and data integrity simultaneously:
No matter where calculations happen, it must be possible to see the original data, calculation procedure (method), and outcome. In addition, there must be sufficient transparency to capture any changes to factors, values, or the calculation procedure for review. To meet these requirements, there are three primary options to consider:
A spreadsheet: This remains the least efficient, least compliant, and least effective option for data integrity. A spreadsheet typically has manual data entry and permits an analyst to recalculate results before printing and saving the desired result values for the permanent batch record. Why do so many labs continue to choose it? Not simply to support the paper industry but because it is familiar and comfortable. It is time to move on to better options.
A LIMS or ELN application: If configured correctly, many of these applications have audit trail capabilities, access controls to prevent unauthorised actions and versioning of calculations, the ability to perform calculations that are problematic for chromatography applications, and more. However, their ability to interface is a process strength and data integrity weakness. Data sent into LIMS or ELN can be manipulated externally and then sent to the LIMS or ELN for calculation.
A CDS application: The chromatography data system is often the best calculation location. It usually provides access control to prevent unauthorised changes, versioning of calculations, and audit trail reviews for changes in calculated values and the calculations themselves. In addition, the calculations are in the same system that holds the original (raw) data, so that review is usually within one system.
Focus on the highest risks and use a CDS application to accelerate the reporting process. Interestingly, the greatest data integrity risks are sometimes indicated by a lack of out-of-specification (OOS), out-of-trend (OOT), or out-of-expectation (OOE) results. In many cases, falsification activities are directed at making test results that would fail the specification into passing results through various forms of data manipulation. This makes it prudent to carefully review results near specification limits (say, within 5%) to verify that all changes and calculations are scientifically justified.
To accelerate your reporting process, don’t print all your data; print a summary. An exhaustive printout makes it harder for the second person to review. Instead, leave most data electronic, print the summary, and facilitate a quicker review process.
Management can inadvertently create a climate where personnel are encouraged to manipulate test results. Mandates such as “zero deviations,” “no product failures,” and “meeting production targets” can encourage data manipulation. Throw in the possibility of a demotion or dismissal for failure to meet any of these mandates, and the environment is ripe for data manipulation.
The irony is that two losers are created: the patient who receives a sub-standard product, and the company that no longer knows its true capability or process trend—or worse, suffers reputational damage. This phenomenon is recognised by the Pharmaceutical Inspection Convention and Pharmaceutical Inspection Co-operation Scheme (PIC/S) data integrity guidance, warning that management should not institute metrics that cause changes in behaviour to the detriment of data integrity.
The newest release of OpenLab CDS software helps you strengthen data integrity while accelerating calculation and reporting processes. To cite just a few key features and capabilities:
The Custom Calculator tool: automatically computes unique values directly within the software, removing error-prone calculation steps and allowing you to meet compliance requirements faster and with less effort. Custom Calculator can also flag changes made after initial use of the calculation procedure — telling the reviewer that audit trails should be checked to assess the scientific merit of the change or changes. Download the Technical Overview
Automated reporting: with OpenLab CDS, analysts no longer have to enter data manually or print everything. If you analyse approximately 500 samples per month at 10 minutes per sample, including data review time, manual data entry takes about 1000 hours per year or about 25, 40-hour weeks—half of an analyst’s time. Using OpenLab CDS, reporting time can be reduced to 5 minutes per sample for time savings of 500 hours or 12.5 weeks per year.
Technical controls: within the audit trail give analysts the ability to highlight data changes and deletions to facilitate the review process, enable review by exception and create efficient search routines within an individual project or the whole database to identify data trends and inconsistencies. The application also documents that audit trail entries have been reviewed.
To learn more about OpenLab CDS for your lab and the preservation of your data integrity, learn more about the software on our Solutions page.