LIMS and Data Integrity in the Age of COVID

C.E. Credits: P.A.C.E. CE Florida CE
Speaker

Abstract

Arguably data integrity is important, very important. It is clear that with bad data, poor decisions are made, in some cases you might as well have not have any data upon which to base your decisions. So, poor testing along with poor quality data can not only cost companies and governments millions, if not billions of dollars, more importantly it can also result in significant loss of life. During the recent COVID pandemic the need for high quality data, management and control has become even more apparent. We will review the events of the initial attempt by the US government to generate and distribute COVID test kits to health departments through all states. We will examine rejected sampling kits by the Canadian government due to mold contamination and vaccine development challenges by pharmaceutical companies all relating to data integrity. Clinical and analytical testing laboratory data along with meta data is being generated at amazing rates, everything from the specimen demographics, supplies, reagents, specimens tracking, temperature readings of refrigerators, freezers and incubators to ensure that reagents, controls, supplies, and samples are stored at the appropriate temperatures, to data electronically imported from instrumentation (which also generate significant volumes of raw data), result data, dilutions, unit conversions as well as quality control data that all needs to be managed, controlled and maintained. There is a shortage of classically trained microbiologists and professionals that have an aptitude for analytical laboratory work, with a pandemic there is a rapid increase in laboratory testing which puts additional strain on health departments and clinical testing laboratories. This presentation will examine the importance of data integrity, along with the role of LIMS and other tools that can be used to help analytical laboratory professionals to produce, analyze, control, communicate and maintain high quality data. We will look at recent events of failures to generate high quality data and the human and financial impacts during the COVID pandemic.

Learning Objectives:

1. Understand the role that a LIMS plays in defining and maintaining data integrity and why it is so critical.

2. Learn how the impacts of poor data integrity can extend beyond the laboratory environment or an audit finding, to grave human and financial loss.

3. Become familiarized with the role that automation plays in LIMS along with data integrity.


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