Done Right, Labeling Improves Accuracy and Enables Data amd Resource Sharing
Labeling may seem like a simple task. The specimen information goes on the label, the label is placed on the sample, and that’s it ... right?
But when you think about it, your lab labels are an integral part of the success of your lab. They house critical data, and without them, your samples would be unreliable and simply irrelevant. Those labels are your source of identification, and—if implemented correctly—they are the foundation of your internal sample management process.
Are you making the most of them?
Whether you choose to implement large-scale identification automation, undertake continuous improvements or simply make a few small changes to improve your existing process, each outcome can advance results and optimize the efficiency of your labeling process.
Even if you’ve removed the high-occurrence error items, the tail end of the quality spectrum is all about squeezing out the errors throughout the process.
Here are five common mistakes related to item identification and labeling that are seen in today’s laboratories.
#1: Handwriting labels
Although this seems obvious, there is still a large percentage of labs that handwrite. The benefit of handwriting is that anyone can pick up a pen or pencil and write … but that’s about it. Handwritten labels are difficult to read and are unreliable. The ink can smear and the information can be easily misread—leading to repetitive errors.
Fortunately, it doesn’t take much to start printing at a basic level. For example, you can start by purchasing a small user-friendly printer with a keypad, or you could implement a computer labeling system that takes a simple Excel sheet and merges it with a label file, then prints the data.
Printed labels (even if they are simply alphanumeric) offer significant benefits over handwriting. The quality of print is reliable; the text is clear and legible for everyone to quickly read—not just those who know the technician’s handwriting. This reduces transcription errors and minimizes the time needed to manually interpret or rewrite the correct information, which often happens with handwritten samples.
#2: Purchasing the wrong label for your application
The technology of labels has become very sophisticated; there are many substrates or types of labels to choose from, which can make it difficult for labs to know which label is right for their specific applications. However, if you choose a label that is not sufficiently specific for your application, there could be a myriad of problems that result. The chart below lists the six main label characteristics that you should consider when selecting your laboratory labels.
To properly select a label for your application, examine the steps and environment of your lab—not only in your current process, but in any that you are planning to implement. Review this requirement with a trusted company representative and then request a sample from the manufacturer or your representative. Be sure to test it in your environment!
Label manufacturers will also provide Technical Data Sheets that document the parameters and testing protocols that were completed for the label type. This will give you the ISO documentation for auditing, as well as the assurance that the material had quality controls in place from the manufacturer.
#3: Creating “waste” in the labeling process
Are your technicians walking around the lab with specimens in order to get them to the next step in your process? Are numerous specimens batch processed at one time, creating a backlog too large for the technician to handle?
As defined by lean practices, these are all examples of “waste”— any activity that does not add value to a given process. Traditionally, there are seven types of waste in a lab: transportation, inventory, motion, waiting, overproduction, over processing and defective product.
There can be numerous examples of waste in your labeling process as well. For example, large-scale labeling of a batch of carriers or tubes means that a technician must then marry the carrier or tube to the specimen later on. This results in several different types of waste: the carrier or tube can be matched with the wrong specimen, resulting in erroneous identification (type of waste: defective product); additionally, all the samples need to then wait until the entire batch is complete before they can be moved to the next step (type of waste: waiting).
Instead, you could implement an on-demand printing solution at a designated specimen printing “work cell.” This would allow you to identify the carrier and then immediately match it to the appropriate specimen. It decreases the chances of placing the wrong label on the sample and greatly improves the integrity of the information. This also enables you to move smaller labeled quantities or single specimens to the next step of your process as soon as they are identified, thus eliminating potential bottlenecks in the labeling step.
#4: Forgetting the bar code on your label
Even your bottled water has a bar code, so why doesn’t that valuable specimen you hold in your hands have one?
Bar codes offer tremendous improvement opportunities for laboratory identification, particularly in reduction of errors and technician productivity levels. For example, it is estimated that an error is made once every 200 keystrokes. Previous methods of handwriting and tracking manually have an even higher error rate. Labs that implement bar coding, however, can significantly reduce the number of errors. In fact, it’s commonly estimated that bar coding has only one error in 3 million serial bar code scans and one in 10 million twodimensional bar code scans. A lab’s specimen integrity is greatly improved by scanning a bar code and collecting the data electronically.
#5: Labeling only for your lab
Every lab has its own way of identifying samples. You choose what information needs to appear on the label based on the current needs of your lab. However, it’s easy to forget that these samples could potentially be used for cross studies and research and may have a life well beyond your individual lab. As the industry continues to move toward an environment of sharing and collaboration, it’s important that your labels can be read and understood by those outside of your lab environment as well.
A number of industry-wide best practices have been identified to give you guidance on the minimal labeling requirements for sample identification. These guidelines can be customized for your individual lab but provide a baseline for the type of information that should be included on your labels. By adhering to these best practices, labs can create a common platform for identification and data consistency throughout the scientific community.
Below is a list of biospecimen identification best practices as outlined by The National Cancer Institute.1
- Unique identifier or combination of identifiers
- Firmly affixed to the container
- Number or bar code
- HIPAA regulations for human subjects
- Information system tracks biospecimen from collection through processing, storage and distribution
- Data used for clinical and epidemiological
- Clear and legibly marked; able to endure storage conditions
- Shipping log tracks shipment
- Resources touching specimen
Additionally, it’s important to note that in order to meet these guidelines, a complete informatics system is advisable. This includes software, hardware, written documents, support and training necessary to annotate, track and distribute the biospecimens.
Labels: A powerful tool for laboratory success
In the end, labeling is a bit more complex than it may seem. But those labels can be a powerful, effective tool that impacts the overall success of not only your lab, but labs around the world. Labels can increase efficiency; improve accuracy; reduce errors; and enable a scientific community to share data, resources and learnings.
As technology continues to progress and regulatory requirements continue to expand, there’s no doubt that laboratories are going to see a number of advancements relating to labeling and identification in the future. Now is the time to implement a productive labeling system that accounts for the flow and processes of your lab—both for today and for tomorrow. The integrity of your data and the quality of your services depend on it.
- National Cancer Institute Best Practices for Biospecimen Resources, Prepared by NCI, NIH, US Dept Health and Human Services, June 2007.
Nicole Nelson, Laboratory and Healthcare Market Manager, Brady North America, can be reached at Nicole_nelson@bradycorp.com or by phone at 414-358-6744.
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