Are you aware that your selected research samples are from only 3 donors?
This example of data insight was gained following an import of a customer’s data into our Achiever Medical sample management system. The information had been taken from multiple spreadsheets and until the data had been consolidated into one system, it had been impossible to see the bigger picture.
When viewing the data within each individual spreadsheet, it was not immediately apparent that the original sample had been split into many aliquots and a large proportion of the data were ‘child’ samples. At first glance, with their individual sample status, storage information and allocated internal IDs, there appeared to be an abundant pool of samples from which to choose for use in research. Carefully scrolling across the columns and grouping the data showed a slightly different story which was compounded across other spreadsheets.
The potential impact on the validity of any research results based on such a restricted pool of donors could be significant.
Consolidating your data into a single system or view will provide greater insight into the quality and extent of the information available. In turn, this will improve your ability to determine whether your sample selection is as diverse as you wish.
Holding basic donor data can improve your research quality
Why are 90% of the samples used in this experiment taken from female donors?
Even if you only have visibility of basic clinical data against a sample, such as gender and age, this will help you to assess whether your sample selection really is as extensive as you think. Naturally, if your research should only include females within a defined age range then having this data is essential. However, if your research should include samples from both female and male donors, being able to quickly and easily assess sample variety will help you consciously remove any obvious bias.
Enhancing this data further, by capturing disease, diagnosis and treatment information, not only allows you to focus your selection but also allows you to check for diversity.
It’s not just about selecting samples for research
When you are choosing teams, labs, samples or storage facilities to include in an audit, are you selecting those you think might be slightly better organised than others? No-one enjoys an audit but Sample Management software, such as Achiever Medical, can help you proactively manage your audits. Achiever’s auditing module allows you to randomly select samples and storage that has not been audited before or has not been audited for a defined period. This helps to improve the quality of all your samples across your organisation – not just one section.
Introducing processes to assist
Sample Management systems and Laboratory Information Management software (LIMS), can also assist further, for example with dashboards, automated alerts and notifications. These can be available to the users throughout sample processing to highlight potential issues.
Naturally, software systems can only do so much and internal training and Standard Operating Procedures (SOPs) are required to help address these challenges. However, where software can help is by providing guidance to users when carrying out processes and displaying any non-compliance issues to lab managers that will inform training and assistance needs.
In summary, Sample Management systems can provide tools to maximise your sample diversity and appropriateness to improve and support the validity of research findings. They can also help to proactively manage SOPs and audits to evidence best practice, further supporting those findings.