Laboratory automation: Benefits and challenges


Laboratory automation has transformed laboratories over the past 40 years.  From its humble beginnings in the 80s, the technology has made its way clinical laboratories throughout the world.  It has allowed laboratories to perform more tests, a greater variety of tests, with fewer staff and lower cost per test.  It has also has changed how laboratories work, particularly within the clinical space.  That has created conflict in how laboratories look at themselves, what tests are offered, and how staff are deployed, creating challenges even as laboratories have been able to save money and improve service with this technology.  In this article, we discuss the benefits and challenges of laboratory automation, and how they can shape how laboratories operate.

Laboratory automation: The benefits

  1. Reduced test costs

Laboratory automation has scaled from the batch organization of a cluster of tests to the ability to perform a large menu of tests within a small set of platforms. Integrated with sorting and aliquotting systems, a large menu of tests can be performed by a limited number of personnel, eliminating large amounts of manual labor. What is not mentioned is that the flexibility of platforms allow for tests to be performed within a limited amount of space, reducing utilities costs and equipment costs, meaning that capital expenses can be amortized over a higher number of tests.

  1. Faster processing

Eliminating the need for humans to handle specimens means that specimens can be prepared for testing much faster. This means that biochemical tests can be performed faster, and technologies from molecular diagnostics, liquid chromatography and even microbial and tissue culture can be performed without the need for intervention. This means that tests can be performed more quickly that it can be done manually, allowing for faster turnaround times for test results.

  1. Ease of interaction with LIS/HIS systems

Laboratory information systems have been used to track the results and follow trends for patients. What laboratory automation can do with LIS systems is to allow for more sophisticate test ordering to suggest tests that may be appropriate based on the results. Integrated with health information systems, this information can inform treatment decisions and guide towards more effective treatments based on how prior treatments have resulted in lab results with particular prognoses.

  1. Modularity

Laboratory automation systems are customizable to meet a given laboratory’s needs.  The number and the types of modules available mean that different testing technologies can be added and removed as technology comes online.  This gives laboratories the need to evolve with their patient population and with technology, meaning that services offered will be more relevant to patient populations.  This also limits the risk of obsolescence, justifying the overall capital cost.

  1. More time to consult

The reduction of manual labor means that laboratory professionals have more free time to communicate with their healthcare colleague on how laboratory tests work. They can guide them towards tests that will help them answer clinical questions effectively, and avoid tests that may be unnecessary. They can also help explain the science behind the tests as to better assist healthcare professionals as to what is going on with the patient in front of them, allowing them to make adjustments in treatment as appropriate.

Laboratory automation: The challenges

  1. Learning curve

Laboratory automation changes how people interact with testing.  Instead of having to interact with specimens at some point to perform the testing, the automation does all of the work.  However, there are judgment calls to be made with releasing tests results, monitoring equipment, performing quality control testing and deciding whether to perform maintenance.  Understanding the rhythms of how testing may work with this equipment can be a challenge, particularly as workflows may change in a laboratory.

  1. Understanding software

Laboratory automation requires sophisticated software to keep track of the tests orders, route the specimens in the appropriate direction, maintain patient and quality control results and watch for equipment indicators.  Getting in the habit of monitoring the software can be a challenge, as it requires understanding on a systemic level what the automation is doing and why.  For those who have worked with their hands on the bench, understanding how that translates to automation can be a challenge.

  1. Troubleshooting

Understanding what an error means for a complex system can be a problem.  Why there are some obvious issues that can be directly addressed, subtle issues can creep up over time.  This requires tracking and monitoring of systems to stop issues before they start.  It also means bringing a different mindset to system operations, and great communication skills among staff and healthcare professionals, particularly those who may work on different shits, in order to address testing concerns.

  1. Loss of institutional knowledge

When new technology comes in, old technology goes out of the door.  While this does lead to increased productivity, some skills and knowledge of the old system gets lost.  As medical care takes place over a continuum of years, knowing why something was done a certain way in the past is necessary to ensure that any new information on a patient’s tests is understood within a wider context.  Getting rid of older testing techniques makes it challenging to keep that level of knowledge accessible.  Also, older skills may be useful in troubleshooting new equipment, even when those skills weren’t used very often.

  1. Change in test mix

As the benefits of automation become apartment, it may be cost effective to bring some tests in house, while ending or outsourcing other tests.  These new tests require changes in supplies, which has downstream impacts on storage of reagents and staffing needs.  Understanding the new workflows, which may create new demands for labor, may create staffing challenges, as people have to get accustomed to new hours and new responsibilities.  Working through those challenges can create unanticipated burdens which make switching to laboratory automation difficult.

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About Author

Ramya Sriram manages digital content and communications at Kolabtree (, the world's largest freelancing platform for scientists. She has over a decade of experience in publishing, advertising and digital content creation.

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