When does human error or a fat finger moment slide down the slippery slope to falsification and fraud?
A central component of ensuring the integrity of data and results generated in any chromatography laboratory is the human
element, that is, the chromatographer or the analytical chemist who will be involved with developing and validating methods
or performing sample analysis. Mistakes or fat finger moments are part of human nature but where is the dividing line between
this and falsification and fraud? We will discuss this further in this article.
Deviations From Data Integrity
In the title of this column I have suggested that there are three types of data integrity deviation: fat finger, falsification
and fraud. Here are my definitions of the terms:
Fat Finger: an inadvertent mistake made by an analyst during the course of their work that can be made either on paper or electronically.
Falsification: an individual who deliberately writes or enters data or results with the intention to deceive.
Fraud: collusion between two or more individuals who deliberately write or enter data or results with the intention to deceive.
I have drawn a clear distinction in the definitions of falsification and fraud: falsification is perpetrated by an individual
and fraud by two or more people, however, the impact of both is the same — the intent to deceive.
In writing this column, I have made the following assumptions:
- Each chromatographer working in a laboratory has a minimum level of scientific and professional training to undertake their
work. For example, in method development, method validation, analysis of samples, or review of work and the preparation of
- All chromatographers will follow documented analytical methods and laboratory standard operating procedures (SOPs) or work
- The organization the individual works for has stated the ethical and professional standards expected of its staff at their
induction and via regular training sessions thereafter.
To Err Is Human
Mistakes and fat finger moments? If we are honest, we all make them. That is why any quality system for laboratories (e.g.
ISO 17025, Good Laboratory Practice and Good Manufacturing Practice) has the four eyes principle: one individual to perform
the work and a second one to review the data produced to see that the procedure was performed correctly and that there are
no typographical errors or mistakes with calculations. Errors are easy to make, you should see the number I'm making as I
type this column using a new PC that has a different keyboard than I am used to.
Many of the errors and mistakes that we make are self-corrected. For example, as you enter a number into a spreadsheet cell,
database field or report, often you will find that while the brain says enter 12.3 your fingers magically enter 13.2 instead.
This is a fat finger moment, but before committing the number to the cell or database you can correct this as you can see
and have realised your own error. The equivalent moment on paper is when you actually write the wrong numbers down in your
laboratory notebook and then correct it by striking through the original entry so as not to obscure it and entering the correct
value along with your initials and date and possibly the reason for change. This is the paper version of an audit trail.
Some other mistakes may not be noticed by a chromatographer but could be detected by the software application that they are
using such as a spell checker, or by verification that the data entered fails to meets certain criteria, such as within a
predefined range or specific format by a spreadsheet, Laboratory Information Management System (LIMS) or Chromatography Data
System (CDS). So, using the example above, if the data verification range was 11.0 to 13.0, the software would have picked
up the problem and warned you even if you had not noticed the error.
However, that still leaves the mistakes you don't realise you have made. For example, if the entry in the case above was
11.3, data verification would be useless and the error would have been entered without you or the software realizing that
there was a problem.
Don't assume that you will spot all of your own mistakes because we are all human and error prone, which is why we need the
second pair of eyes to check our analytical data and calculated results. From my experience as a laboratory manager and as
an auditor, supervisors know which members of their staff are diligent about their work and how well they check it and those
individuals who are slapdash. A supervisor will adjust their second person reviews accordingly. So if you don't want a dubious
reputation to precede you, be diligent and try your best to find and correct your own errors before passing your work over
to be checked.