Eliminating Handwriting From The Lab Is Key To Best Lab Informatics


Every laboratory contains a variety of quantitative data and qualitative data spread across many media platforms and a number of physical locations, and practically every researcher and administrator has a writing utensil within arm’s reach. Handwriting is a useful construct in everyday life, but in the laboratory, it’s not particularly helpful with effective collaborative research.

Whether it’s the handwritten “lab cleaning duty” board or the heavily scrawled-in laboratory notebook, handwriting is holding back the laboratories of the 21st century from complete digitization. But by using the right software, hardware and data aggregation tools, the laboratories of today can begin eliminating handwriting and experiencing greater productivity and fewer errors as a result.1

Cutting Handwriting Cuts Down On Mistakes Of All Varieties

Most scientists have found themselves in the position of hunting around for an important experimental item that has gone missing, peering at many illegible labels written by other people in an attempt to locate the right thing. Eventually, the scientist will settle on the handwriting that appears to denote what they’re looking for while remembering that they too have a collection of items and samples that are labeled with their handwriting that someone else will one day seek.

There’s reason to believe that very frequently, scientists find the wrong thing when confronted with this common situation. In a study performed in a clinical serology laboratory, 10% of handwritten request documents contained transcription and subsequent interpretation errors due to misread handwriting.2 These sorts of errors are bound to be much higher in the laboratory, where samples are first labeled messily with a sharpie, then stored in liquid nitrogen, only later to be scrounged out, covered in frost and steaming vapor.

Likewise, elsewhere in biomedical laboratories, decontamination protocols used on sample test tubes typically utilize ethanol or isopropanol, both of which have a habit of smearing and even removing handwriting. Even printed labels, which may be more readable, can slip off or become worse for the wear.

If a staggeringly high rate of error like 10% is directly attributable to handwriting in an analytical context where a greater level of care is taken when handling samples, the question remains: how many errors occur daily in laboratories due to messy handwriting which causes an incorrect interpretation? The number is hard to estimate, but there is data which suggests that (tautologously) transitioning to an electronic information system in which there are no handwritten entries results in a total elimination of illegible handwriting as a source of error. 3 This transition could potentially end many silent errors in a given lab’s experimentation, drastically increasing its efficiency and rate of success.

Electronic Regulatory Compliance Sans Signature

Analytical laboratories bear the brunt of regulatory compliance issues caused by handwritten forms, but laboratories operating in a Good Manufacturing Practice (GMP) or Good Laboratory Practice (GLP) environment could also suffer the burden depending on how their regulatory systems are implemented. One of the largest recurring issues with filling out analytical forms, GMP, and GLP forms is not directly related to handwriting, but could be solved by removing handwriting: people simply forget to fill out certain parts of the form.4

This breaks the problem of handwriting into several distinct categories:

  • The problems of illegibility which causes the mistaking of one thing for another
  • The problems of unfilled data spaces which causes a paucity of information
  • The problems of data spaces that require corrections or updates multiple times which leads to illegibility or lack of space to write in, requiring a new form
  • The problems of losing the entire paper with handwriting on it

In a analytical laboratory, if a patient fails to fill out a part of the form, they can be prompted by one of the analysts. In a regulatory paperwork setting during GMP or GLP lab work in research, development, or manufacturing, there is no check or balance to prevent skipped entries. There is a mechanism for witnessing by a second party in the GMP system, but many laboratories do not require witnessing to be performed on the same day or time of the original experimental entry, nor do many employees take witnessing very seriously, meaning that an error caused by handwriting could easily persist.5 This means that if those entries are later audited by the federal government during a compliance investigation, there will be a hefty fine to pay.6

Implementing A Writing-Free System

If a lab is to transition to a writing-free system, it will need:

  • Ubiquitous label printing linked to database software
  • Barcode printing which creates database entries
  • Premeditated experimental design which involves producing labels before starting
  • A software platform to tie together all of the physical components being tracked and all of the database entries that correspond to the items that are labeled and barcoded

Electronic Laboratory Notebooks (ELNs) are rapidly becoming a core part of every laboratory operation in industries from pharmaceuticals, to chemicals, to consumer goods and more. ELNs streamline the documentation and protection of intellectual property, help scientists collaborate in increasingly global and networked activities from discovery to manufacturing, and make scientific data and observations associated with experimentation easier to search, find and use.  Contact us today to find out how we can help you use our software to tidy up the lab’s most important metadata spaces by being handwriting free as a policy.


  1. “Clinical Laboratory Order Entry and Errors Before and After Implementation of an Electronic Health Record.” 2015, https://search.proquest.com/openview/c032de11da542a46feeb5d9e1271c8db/1?pq-origsite=gscholar&cbl=18750&diss=y
  2.  “Data Quality Associated with Handwritten Laboratory Test Requests: Classification and Frequency of Data-Entry Errors for Outpatient Serology Tests.” October 2015, http://journals.sagepub.com/doi/abs/10.1177/183335831504400302
  3.  “Laboratory Order Errors Before and After Implementation of Electronic Health Record.” 2016, http://web.b.ebscohost.com/abstract?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=0894959X&AN=118129777&h=NZcqA1%2b2xJqK2NHMVTNlGFuIzCuNVdaBuBeLeioLGE1da1UViBhL9LtN0MGsp3AVjG7dg%2fOcBrhhiy9lJgv9%2bA%3d%3d&crl=c&resultNs=AdminWebAuth&resultLocal=ErrCrlNotAuth&crlhashurl=login.aspx%3fdirect%3dtrue%26profile%3dehost%26scope%3dsite%26authtype%3dcrawler%26jrnl%3d0894959X%26AN%3d118129777
  4.  “The impact of automating laboratory request forms on the quality of healthcare services.” April 2016, http://www.sciencedirect.com/science/article/pii/S1876034116301411
  5. “Good manufacturing practices for medicinal products for human use.” June 2015, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4399016/
  6.  “Good Documentation Practices.” 2014, https://s3.amazonaws.com/academia.edu.documents/36095680/2_Good_Documentation_Practices.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1513645182&Signature=1%2Fq%2FTxKvWc97WfZ3Dc%2BUq1AFgI0%3D&response-content-disposition=inline%3B%20filename%3DGood_Documentation_Practices.pdf