Ensuring Data Integrity Through ALCOA

data-integrity

Ensuring Data Integrity Through ALCOA

The acronym ALCOA has been around since the 1990’s, is used by regulated industries as a framework for ensuring data integrity, and is key to Good Documentation Practice (GDP). ALCOA relates to data, whether paper or electronic, and is defined by US FDA guidance as Attributable, Legible, Contemporaneous, Original and Accurate. These simple principles should be part of your data life cycle, GDP and data integrity initiatives. Data integrity and access control issues featured heavily within the warning letters issued by the FDA in 2015 so here is a timely refresh on the fundamentals.

validation exerciseAttributable

All data generated or collected must be attributable to the person generating the data. This should include who performed an action and when. This can be recorded manually by initialling and dating a paper record or by audit trail in an electronic system.

Note: It is important to ensure a signature log is maintained to identify the signatures, initials and/or aliases of people completing paper records.

For example:

  • During a validation exercise, test results should be initialed and dated by the person executing the test.
  • Adjustment of a setpoint on a process or monitoring system should be made by an authorised user and the details of the change logged in an audit trail.
  • A correction on a lab record should be initialled and dated to show when and who made the adjustment.

 

Legible

All data recorded must be legible (readable) and permanent. Ensuring records are readable and permanent assists with its accessibility throughout the data lifecycle. This includes the storage of human-readable metadata that may be recorded to support an electronic record.

For example:

  • GDP will always promote the use of indelible ink when completing records.
  • When making corrections to a record, ensure a single line is used to strike out the old record. This ensures the record is still legible.
  • Controlling your paper records/forms and formatting them such that there is ample room for the information to be recorded.

 

data measurementsContemporaneous

Contemporaneous means to record the result, measurement or data at the time the work is performed. Date and time stamps should flow in order of execution for the data to be credible. Data should never be back dated.

For example:

  • If executing a validation protocol, tests should be performed and their results recorded as they happen on the approved protocol.
  • Data that is logged, or testing that is performed electronically, should have a date/time stamp attached to the record.
  • Ensure electronic systems that log data have their system clocks synchronised.
  • Consider the use of a master clock system that synchronises to the IT network so wall clocks within labs and processing areas are syncronised.

 

Original

Original data, sometimes referred to as source data or primary data, is the medium in which the data point is recorded for the first time. This could be a database, an approved protocol or form, or a dedicated notebook. It is important to understand where your original data will be generated so that its content and meaning are preserved.

For example:

  • Ensure validation test results are recorded on the approved protocol. Recording results in a notebook for transcription later can introduce errors.
  • If your original data is hand written and needs to be stored electronically, ensure a “true copy” is generated, the copy is verified for completeness and then migrated into the 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.

 

ALCOA3-1Common Issues

Finally, here are a couple of common examples where ALCOA is not used resulting in poor documentation and data integrity issues:

  • It is very common to see data being quickly jotted down on a sticky note or on a note pad during testing. This data is then transferred onto the approved protocol or form. Doing this, whether it be for lab results or a validation exercise, means the data is no longer original, contemporaneous and potentially inaccurate.
  • When making a correction to information it is common to see the old data scribbled out, overwritten or removed using correction fluid and sometimes without an initial and date of who made the correction. This means the data is no longer legible, original and the correction is not attributable.

 

Data Integrity Training

Since last year’s GMP and Validation Forum where PharmOut hosted one of the world’s leading experts in this area, Sion Wyn, we have been working hard on developing a practical in the trenches experiences Data Integrity Training Course to be held in Melbourne and Sydney.

Data integrity, Quality Metrics, Continuous Product Quality Review and other industry hot topics will be discussed in detail at this year’s GMP and Validation Forum.

Other posts and presentations on Data Integrity

You can read more about Data Integrity in a presentation our expert Trevor Schoerie gave at a PDA dinner on Success by Design.

Data Integrity Post – Everything you wanted to know but too scared to ask by Trevor Schoerie

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