Data integrity ensures the completeness, consistency, and accuracy of data. It is defined by the ALCOA principle of data being Attributable, Legible, Contemporaneous, Original, and Accurate. Violations can occur through errors, falsification, or fraud. To reduce violations, facilities must address Motive, Opportunity, and Means - ensuring staff do not feel rushed, limiting single logins, and preventing edits to records. ALCOA was expanded to ALCOA+ by adding Complete, Consistent, Enduring, and Available to better ensure data integrity over the long-term.

1. DATA INTEGRITY
NAME : SIRSHENDU ROY

2. WHAT IS INTEGRITY ?
• Integrity is the practice of being honest and showing a consistent and
uncompromising adherence to strong moral and ethical principles and
values. In ethics, integrity is regarded as the honesty and truthfulness
or accuracy of one's actions.

3. WHAT IS DATA INTEGRITY ?
• Data Integrity is defined as, “the completeness, consistency, and
accuracy of data. Complete, consistent, and accurate data should be
Attributable, Legible, and contemporaneously recorded, Original or a
true copy, and Accurate.”
• This is also known as the ALCOA principle guiding Data Integrity.

4. DATA INTEGRITY VIOLATIONS
• Data Integrity violations or data errors can happen in 3 ways: fat finger
errors (an accidental lapse by an operator), falsification (a rogue operator
who enters false results) and fraud (collusion by a number of people). In
this blog post, we’ll investigate how to reduce the risk of all three.
• As a manager in a GMP facility, you are responsible and accountable for
data integrity. If a regulator detects data integrity violations at your facility,
then it will take a long time and a lot of work to regain that broken trust.
• This can only be achieved with proper design, the application of QRM
principles and the training of your staff.

5. WHERE TO START TO REDUCE DATA
INTEGRITY VIOLATIONS?
• To reduce the risk of data integrity violations, think MOM –
Motive, Opportunity and Means.

6. MOTIVE
• The motive to commit a data integrity violation can come from a
number of sources. Often it’s that drive to reach production targets and
get product out the door that can lead to disastrous unintentional
consequences.
• It could also be a lack of resources, so staff are rushed and make
mistakes. It could be due to personal issues for staff as such a crisis at
home or a health issue. One statistic published a few years ago claimed
that 25% of all products recalled in the US were batches released in the
last 3 days of a quarter.

7. OPPORTUNITY
• Opportunities for data integrity errors can be controlled, but must be
balanced with the practicalities of staff requiring access to perform their
duties.
• Auditors often see staff using a single log on (with the password written
on a Post It note beside the terminal for handy reference!), a lack of
group access policies with monitoring and enforcement is also common.
• Any computer system with GMP implications should have access level
rules established and enforced. These rules should define staff roles,
responsibilities and authorities, including those required for effective
data governance programs.

8. MEANS
• The means to change or falsify data is perhaps the easiest to control.
Technical controls such preventing operators from making time and date
changes (on any equipment), removing the Windows snipping tool (the
electronic equivalent of White Out), not allowing any PDF editing tools,
and preventing analysts from deleting files are all easy to implement.

9. ALCOA TO ALCOA PLUS FOR DATA
INTEGRITY
• ALCOA was coined by Stan Woollen in early 1990’s. FDA guidance in
the year of 1999.
• ALCOA was an tool to implement the data integrity in pharmaceutical
manufacturing facility but ALCOA+ made this tool more powerful and
sharp.
• The term ALCOA is an Acronym, which stands for Attributable,
Legible, Contemporaneous, Original and Accurate. ALCOA was then
expanded to ALCOA +, by addition of few more concepts which are;
Complete, Consistent, Enduring and Available.

10. ATTRIBUTABLE
• Attributable dictates that any data should be easily identified to the
person who did the data collection, place of origin and the time of data
collection should also be noted down. In the case of alteration of data,
the person making the corrections should also be noted down.

11. 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.

12. CONTEMPORANEOUS
• Data recorded should be contemporary in nature. The dictates that the
time of data collection should correspond accurately with the time of
data recording. Any data collection should have a date and time, and the
same should be ensured in the case any later corrections.

13. ORIGINAL
In order to preserve the meaning and integrity of data, the original records
should be preserved, meaning the material used should be durable. In the
case of duplicates, the creator of original records should confirm the
authenticity of the copies.

14. ACCURATE
For any data to be viable, it should be error free. In the case of any
amendments, there should be accompanying documents to support the
changes. The data should be complete and viable. Data quality must be
maintained.

15. COMPLETE
When data is complete in nature, it means there is no deletion that has
taken place from the date of documenting. This includes any changes that
have been made during the life of the data.

16. CONSISTENT
The data should be chronologically arranged, with time stamps included
for any addition to the original data. Consistency should be ensured by
applying various audits over the life of the data.

17. ENDURING
The material used to record the data should be in a manner which will last
a long duration of time without losing the readability.

18. AVAILABLE
Data should be accessible whenever needed, over the life of the data.
Availability ensures the data meets its use, since it can be applied when the
need arises.