What is Data Integrity?
Data integrity is the maintenance of, and the assurance of, data accuracy and consistency over its entire life-cycle and is a critical aspect to the design, implementation, and usage of any system that stores, processes, or retrieves data.
Data integrity is a key approach in the pharmaceutical quality control system. ALCOA is (Attributable, Legible, Contemporaneous, Original, and Accurate) was introduced in the 1990s for ensuring the pharma industry as a framework for data integrity and Good documentation practice (GDP). Then further introduced ALCOA plus is (Complete, Consistent, Enduring and Available) Currently used by the FDA, WHO, PIC/S, and GAMP. So overtime periods, data integrity concepts expand from ALCOA to ALCOA plus for ensuring data security and integrity ( data protection) are observed and maintained.
ALCOA+
ALCOA has five basic principles (Attributable, Legible, Contemporaneous, Original, and Accurate) to stop data integrity issues.
The collected data must be attributed, who performs the action and when, if a record is changed, who did it and why? For example, when during conducting of validation, the test result must be dated, and the initial should be done by the person involved in conducting the test. If any change in the monitoring system, the change detail should be in the audit trail and any correction made by the person should be recorded and dated. A signature log must be for the identification of initials and the person who completed the paper record.
Legible:
Legible data means the data can be easily read. This attribute should be ensured both in the short and long term, therefore the materials used in recording and collecting the data should be durable.
Contemporaneous:
The data should be recorded at the time and date of work performed. The timestamp should we follow in order.
For example, when conducting validation protocol, the result of the test performed should be recorded in an online sequence. Recording the results should be dated with a timestamp then logged in the electronic system.
Original:
The information must be recorded as original or in a certified true or original copy; this may be an acceptable protocol or a database or a notebook.
For example validation test is being recorded on a given protocol because recording test results in a Notebook may be a chance of error. If the original data is handwritten, it must be stored in an electronic system.
Accurate
For data and records to be accurate, they should be free from errors, complete, truthful and reflective of the observation. Editing should not be performed without documenting and annotating the amendments.
For example:
- Use a witness check for critical record collection to confirm accuracy of data.
- Consider how to capture data electronically and verify its accuracy. Build accuracy checks into the design of the electronic system.
- Place controls/verification on manual data entry, for example, temperature results can only be entered within a predefined range of 0-100°C.
ALCOA PLUS (+)
Complete:- All data should be complete including, test repeat or re-analysis performed on the sample.
Consistent:- Consistent in a generation of record and application of date and time stamps in the expected sequence.
Enduring:- Data should be recorded in a controlled worksheet in laboratory notebooks or invalidated Electronic systems.