So really, what is big data? What does it mean to the general laboratorian? Who has big data in their lab?

I looked up the definition of big data, and here are some industry descriptions:

Merriam Webster indicates that big data is ‘an accumulation of data that is too large and complex for processing by traditional database management tools (Merriam Webster, 2019)

Forbes adds that a study conducted by McKinsey in 2011, describes big data as, ‘datasets whose size is beyond the ability of a typical database software tools to capture, store, manage and analyze (Forbes, 2014)

So, my idea of big data is in the context of the laboratory environment is:

Data that goes beyond an individual’s ability to understand, compute, or triangulate data points together. Roughly this means that the vastness of laboratory data is beyond our ability to correlate data using simple tools like Excel or simple statistical calculations.

Our laboratory IT systems now are 35+ years old, with patient data dispersed into different middleware and other companion systems. These systems have patient data that is numerical or unstructured with other supporting pieces of data that surround these results. The clinical laboratory data is voluminous and has become so large with the proliferation of molecular and genetic data that it is beyond our comprehension how to make sense of it using the tools we have in the lab. The data expands to many different systems that we can’t even conceive how to normalize and line up the data between the systems to even harness it.

Impact to you.

Do you know your laboratory metrics? You should be familiar with your lab turnaround time, non-conformities and complaints, instrument through puts, volume capacities and important data elements in your working area. You may be asked to participate or collaborate in studies, projects, or technology decisions to optimize your laboratory data that supports important healthcare initiatives. Your data literacy is the power to move labs to the next level of improving patient outcomes and population health.

When does laboratory data become big? Well, I would propose that clinical laboratory data is ‘big’ because of its importance to the monitoring and treatment of patient care. In the simplest terms, laboratory data is, by default, a component of the big data idea. So, for laboratorians – your work every day contributes to the big data reservoir of information that includes the following:

Patient test orders in correlation with patient results

• Specimen integrity data

• Specimen transit and storage data

• Quality Control results linked to patient results

• Patient Moving average data

• Result comments and observations

• Rerun and reflex actions

• Rule trigger events

• Result turnaround time based on specific time points

Now, fast forward to 2020, what do you think big data is in the laboratory? Where is the line between local data that can be managed and data that is jettisoned off to support population-based analytics? Laboratories need to become more familiar with data in general – data that enhances and optimizes workflow, turnaround time, and productivity and data that is useful for complex data analytics. There are valuable technologies inherent in most LIS, middleware systems, and companion applications that can provide data analysis tools today. Labs must take advantage of these tools to advance their laboratories to become champions of local data and data that can be moved beyond the laboratory walls to contribute to new analytics that can improve how we deliver and change healthcare diagnostics.

Inspire you.

Learn about an exciting movement in the Clinical Laboratory industry called Lab 2.0. Click here to read about how our thought leaders are focusing on the value of laboratory data to support the shift in healthcare to value-based models. Many labs are embracing the new paradigm and making real changes in their lab operations to support healthcare in a new way.

Let’s hear from you!

References:

Merriam-Webster (2019). Big data. Merriam-Webster. Retrieved from https://www.merriam-webster.com/dictionary/big%20data.

Press, G. (2014). 12 big data definitions: what’s yours? Forbes. Retrieved on September 2, 2013, from https://www.forbes.com/sites/gilpress/2014/09/03/12-big-data-definitions-whats-yours/#15e1cf6b13ae.