5 Reasons Why Data Quality Matters in the Lab
Oct 01

5 Reasons Why Data Quality Matters in the Lab

Many laboratories invest in and use state of the art equipment to process and analyse samples. These highly sophisticated pieces of kit can efficiently handle large volumes of samples. They can complete very intricate – as well as repetitive – processes, saving you valuable time. Plus, their accuracy can help improve quality in your lab operations. What’s more, they can carry out tasks that you just couldn’t do manually. Although they’re expensive you can easily see their worth. But, ultimately, the most important thing they deliver is information. So, why would you risk impacting the quality of that information by manually re-entering it into a spreadsheet or legacy database?

When assessing lab data quality it’s not just about its accuracy but also its integrity, completeness, auditability, formatting, consistency and standardisation. Laboratory Information Management Systems (LIMS) or off-the-shelf Sample Management software can help you manage and improve the quality of your data. But investing in these systems is often given a lower priority than other lab equipment. Here’s 5 reasons why data quality matters in the lab and why you may want to consider a system to support your data management activities.

1. Making sure you use those valuable samples

You may be handling tens or even hundreds of thousands of samples across your organisation. If you’re using spreadsheets to record your data it’s highly likely that you’ve got duplicates, inconsistencies, inaccuracies and incomplete information.

As a result, sourcing samples to use can be time-consuming as well as soul-destroying!  You may miss out on finding the ‘perfect’ samples because you didn’t quite enter the right search criteria. Or you may end up buying more samples because it’s quicker and cheaper than trying to find them.

A system such as a LIMS makes sure everyone is recording data consistently. Making it easier and quicker to search for and find the samples you need.

2. Collaborating with others

Collaboration involves working together and sharing resources to achieve a common goal.  One of the most important things you can share is information. You may be reluctant to share your lab data if you don’t have confidence in its quality.

What’s more, biobanks and biorepositories providing samples to researchers need to be able to publish sample holdings data and process requests quickly. If it takes a long time to publish or source your samples, you may lose valuable opportunities. Also, researchers could be missing out on using your quality samples.

3. Assessing sample viability

When working with a sample it’s important you know its provenance. From how it’s been collected and processed to how it’s being stored. Accurately tracking a sample’s every movement and event can be difficult in a spreadsheet that doesn’t have an automatic audit trail. What’s more, this audit data can be vital in understanding a sample’s viability. Especially if a sample’s not been stored correctly or been out of storage for long periods of time.

Also, if you’re not able to view a patient’s informed consent easily against their samples you may be hesitant about using them for certain types of research. This could mean you’re missing out on potential opportunities for use. Some LIMS, such as Achiever Medical, enable you to store consent information including any opt-ins and restrictions. You can see this easily against patients and their samples and you can exclude or include certain samples when sourcing for use based on the finer consent details.

4. Impacting outcomes

You often see the value of data at the end of a process when looking at outcomes and results. But those end results are based on data that you captured right at the beginning of the process – as you took the initial samples. How confident are you in those outcomes and repeatability of results? Especially if you started with incomplete and inconsistent data.

What’s more, you may not capture patient information alongside samples taken. Without this level of data how do you know that the 50 samples you’re working with are actually from 50 different patients? It could be just 5! Working with 50 samples from just 5 people is very different to working with 50 samples from 50 people.

Also, understanding some of a patient’s underlying treatments, diagnosis and lifestyle information can help you really target your sample selection. The more you know about the patients, the more this can help you understand the impact on your research. A LIMS, like Achiever Medical, protects personal identifiable information (PII) only allowing those with the appropriate approvals in place to access it.

5. Influencing decision-making

Every day you may decisions based on information. If you can’t access your data, then you can end up making decisions based on gut feel. But incomplete or inaccurate data can lead you to make to incorrect assumptions. This is where the quality of your lab data can have a significant impact – positive as well as negative.

A LIMS like Achiever Medical provides a library of interactive dashboards as well as data visualisation and query tools. These help you to check the quality and completeness of your data. They also summarise your data, so you can slice-and-dice and further filter it to monitor progress and identify potential issues. You can drill down into the underlying records for more details.

A final thought about why data quality matters in the lab

One of the most valuable assets in the lab is your data. Everything you do relies on data you’ve captured which in turn is used to generate more data for you to evaluate and review. Investing in and using data management systems, like a LIMS, make it easier for you to find, work with, update and analyse your information. They’ll not only save you time but give you more confidence in your results and help you share your information, securely, with collaborators and researchers.

Importantly, they help you find and use samples for their intended purpose and ‘Make Every Sample Matter.’

About The Author

Sharon Williams has over 20 years’ experience of helping businesses successfully implement Sample Management Software and CRM systems. Appreciating that the software will deliver significant business change and improvements, Sharon guides businesses to help optimise these benefits. This includes advice on how to obtain user buy-in, evaluating and redefining existing business processes and how to gain a better understanding of their data to provide invaluable insight and inform business decisions.