Data integrity can be thought of as a component of a larger process ensuring the security, traceability and quality of an organization’s results over their whole lifecycle. The principles outlined in ALCOA and ALCOA+ support efforts toward data integrity, and include ensuring that data is attributable and traceable, among others.
Here are seven ways to achieve Data Integrity with ALCOA
Ready for Data Integrity?
Data has surpassed oil as the world‘s most valuable resource and ensuring its integrity in laboratories worldwide is crucial to comply with GLP and GMP regulations. The acronym “ALCOA+“ defines a framework to achieve data integrity and is especially important for regulated industries. Based on 9 points, ALCOA+ is designed to overcome the challenges in maintaining data integrity. Our innovative competence tools and solutions support this approach.
How to Manage Data Correctly?
After processing, data can be used for many subsequent processes inside a laboratory. It‘s crucial therefore that data are traceable, permanent, readable and understandable by anyone reviewing the record throughout its lifecycle. Archiving data is key for long-term retention.
How to Capture Data?
The initial measurement is the origin of all data sets. Errors at this early stage can influence the following data processing chain.
Advanced weighing systems provide a range of features to ensure process data are accurately captured and securely stored or transferred to a company’s data management systems.
How to Avoid Transcription Errors?
Manual data transcription is a major source of error and other data integrity violations.
By eliminating the need for manual transcription, automated or partially-automated solutions from Mettler-Toledo lower the risk of transcription errors, transfer metadata and provide centralized data storage.
Is Your Data Following SOPs?
Creating accurate data is important but so is ensuring it remains accurate over time.
Security and user access rights help to promote data integrity by identifying and documenting any individuals who make changes to the original data set. Managing calibrations for all devices, including pipettes, can avoid fundamental errors.
Are Your Data Sets Complete?
Missing information inside a data set can massively reduce the value of data, as well as waste laboratory analysts‘ time as they seek to gather missing data and recreate results or reports. Complete and consistent data includes data from calibration or routine test results based on your regulations and SOPs.
How to Ensure Data Sets Endurance?
Creating data with all relevant metadata and storing this data in a compliant way is a good starting point. However, for compliance, active data management is crucial to ensure data can be accessed for review and audit or inspection over the lifetime of the record. Various procedures such as backups and data archiving are essential at least for the defined retention period.
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