rdoe_persona_userprofile
rdoe_persona_select_up
Article

The rise of smart labs: The importance of automation in clinical laboratories

The digital and technological advances of recent years have changed the world of healthcare as we know it.

One of the many results of this transition has been automation, which is now being utilized in numerous traditionally labor-intensive processes to deliver more value and improve efficiencies within clinical environments.1 But is this level of automation within clinical laboratories always seen as a good thing? Or is the rise of smart labs something that healthcare players need to be more wary of? 

Here at LabLeaders, we took a deep dive into the world of automation in the lab in order to answer these questions and more, highlighting the importance of automation in clinical practice, not just in the present healthcare landscape but also in the near future. 

Article highlights:

  • Automation in clinical laboratories helps to enhance accuracy, efficiency, and safety, transforming patient care and the precision of diagnoses.

  • Despite the high initial costs and technical challenges involved in implementing automation, recent advancements in artificial intelligence (AI) and robotics will play a big role in the future of automated lab testing.

  • Embracing automation in clinical labs paves the way for delivering personalized medicine, point of care testing (POCT), and sustainable laboratory practices.

animated speaking bubble

Join our community and stay up to date with the latest laboratory innovations and insights.

Subscribe now

The role of automation in clinical laboratories

Laboratory automation refers to the use of technology and automated systems to perform laboratory tasks and hone related processes with minimal human intervention.2

By automating lab processes and workflows, clinical laboratories have been able to continue delivering a high-quality level of service while balancing factors like cost efficiency, quality goals, patient safety, and increasing industry demands.2,3

Some of the main examples of laboratory automation in action include the use of automated analyzers, robotic sample handlers, DNA sequencers, specimen tracking systems, and laboratory information management systems.  Each of these automated systems enables clinical laboratories to improve the accuracy of their laboratory tests and positively impact patient outcomes.2,3

The benefits of having an automated clinical laboratory

Over the years, the integration of automated systems into clinical practice has brought with it an irrefutable number of benefits.3

For example, research shows that the use of these processes has helped to: 

  • Enhance the accuracy of results — automated systems have helped to minimize human errors by more than 70% while delivering consistently accurate results.4 This is particularly important in clinical environments, where the obtained results can have a direct knock-on effect on patient care.3,5

  • Increase laboratory workflow efficiencies — automation helps accelerate laboratory processes, allowing a larger volume of samples to be analyzed in a shorter amount of time. In fact, automation has been reported to reduce staff time per specimen analyzed by around 10%.4 This efficiency is particularly important within the current landscape, with sample and data backlogs currently being seen in many laboratories around the world.4

  • Improve cost-effectiveness — while the initial outlay required to implement automated systems may be expensive and time-consuming, the long-term savings and return on investment they can provide are substantial.3,5 For example, automated systems not only help free up time for staff to perform other tasks but also lower the risk of human error.2

  • Streamline data management — many of the automated systems currently used in clinical practice include software to help with data management processes such as data entry, storage, and retrieval.2 This helps to reduce the risk of data loss and makes it easier to ensure compliance with regulatory standards.6

  • Increase safety levels — the ability to automate any potentially harmful laboratory process naturally reduces the exposure of laboratory personnel to hazardous materials thereby, improving workplace safety. Automation also reduces congestion in the laboratory, minimizing the distance personnel need to cover to perform multiple analyses.5

The initial challenges in implementing an automated smart lab

While automated systems may offer a number of benefits to clinical environments for today’s modern lab, integrating new systems can be daunting and come with some growing pains. Healthcare players must face a range of issues including: 

  • Initial costs — the implementation of automated systems requires substantial up-front financial investment in terms of equipment, software, and infrastructure.5

  • Adjustments to internal processes — since automation systems help to perform routine tasks, their implementation requires laboratories to adjust their internal processes by allowing staff members to focus their attention on more specialized tests. This transition may feel labor-intensive, to begin with, but should help improve efficiencies moving forward.5

  • Potential exposure to cyberattacks — reliance on automated systems to perform certain clinical processes may leave some laboratories more exposed and vulnerable to software malfunctions, cyber-attacks, or power outages.5

  • Evolving workforce roles — while automation can free up more time and alleviate high workloads, some laboratory personnel may initially worry about the impact it could have on future staffing changes.4 However, this shift offers an opportunity to upskill staff and enable them to focus on more specialized tasks. Automation can also help laboratories to maximize efficiency and tackle the challenge of a shrinking workforce head-on.7

Recent advances in clinical laboratory automation

Despite the various challenges, clinical laboratory automation has seen substantial advances in recent years, which have largely been driven by technological breakthroughs and a growing need to improve efficiencies within the clinical setting.2

For example, artificial intelligence (AI) and machine learning are being increasingly integrated into automated systems to interpret results, enhance data analysis, create predictive analytics tools, recognize patterns, and even recommend certain diagnoses.2

At the same time, they’re also being used to assist with the more administrative side of working in clinical environments, helping to reduce the need for manual record-keeping as well as improving data integrity and accessibility to ensure regulatory compliance.2,3

 

There have also been a number of recent advances in other areas, including: 

  • Robotics and robotic process automation — advances in robotics are helping to automate repetitive and time-consuming tasks in the lab such as handling samples, pipetting, and preparing plates.2 This has helped to streamline the way in which laboratory personnel can work and reduced the likelihood of human error.

  • The Internet of Things (IoT) — being able to connect IoT devices to lab instruments has provided clinical laboratories with a lot more control, allowing certain pieces of equipment to be operated remotely and, ultimately, helping to increase staff productivity.2

  • Blockchain technology — this advanced database mechanism is increasingly being deployed in clinical laboratories to help with data integrity.8 By storing data in blocks, laboratories become more transparent about the information they hold, helping them comply with strict regulatory requirements.2

  • Advanced analytical instruments — the development of advanced analytical instruments, such as mass spectrometers and molecular diagnostic, immunostainer, and microbiological platforms, has revolutionized the ability of clinical laboratories to perform analyses.3 As a result, clinical tests now offer higher sensitivity, specificity, and speed, making them invaluable in areas like genomics, proteomics, and theranostics.5

The future of automated clinical laboratory testing

The future of clinical laboratory automation looks set to continue being as transformative as it has been over recent years.

One key area in which automation is likely to continue playing a critical role is in the advancement of personalized medicine.5 Due to AI’s ability to analyze high-throughput data and deliver accurate results, automation will allow for tailored treatment plans to be created based on individual patient profiles.9

At the same time, the development of portable and automated point of care testing (POCT) devices will help make these clinical testing improvements more accessible for patients, providing faster sample processing times for those in remote and underserved areas.10 This is also likely a knock-on effect for patient monitoring, with enhancements in remote diagnostics making it easier for healthcare professionals to manage patients with chronic diseases and monitor the efficacy of their recommended treatments. 

Sustainability is likely to play a big role in the future of automation as well. With healthcare providers, medical manufacturers, and health tech companies around the world all dedicated to supporting sustainable healthcare, many future advances are expected to focus on developing eco-friendly technologies that can reduce energy consumption, waste, and the total carbon footprint of clinical laboratories.11,12

The final say

The rise of smart labs is not new and, over the coming years, automation looks set to continue revolutionizing clinical laboratories. Despite some initial challenges, such as staffing concerns, the benefits that automation can offer are undeniable — whether that be through improved levels of accuracy, safety standards, or workplace efficiencies.2,3,5,7

By leveraging the power of automation, clinical laboratories can not only meet the demands of today’s healthcare landscape but also pave the way for a more advanced and efficient future.

Want to be the first to receive the latest insights from industry leaders? Sign up for our newsletter.

  1. Brown AS and Badrick T. (2022). Clin Chem Lab Med 61(1), 37–43. Paper available from https://pubmed.ncbi.nlm.nih.gov/36282956/ [Accessed July 2024]
  2. Doke G. (2023). Article available from https://blog.creliohealth.com/the-power-of-lab-automation-in-clinical-settings/ [Accessed July 2024]
  3. Ebubekir B et al. (2017). Turk J Chem 42(1), 1–13. Paper available from https://www.degruyter.com/document/doi/10.1515/tjb-2016-0234/html [Accessed July 2024]
  4. Robinson AT. (2022). Article available from https://www.clinicallab.com/automation-in-the-clinical-laboratory-26309 [Accessed July 2024]
  5. Lippi G and Da Rin G (2019). Clin Chem Lab Med 57(6), 802–811. Paper available from https://pubmed.ncbi.nlm.nih.gov/30710480/ [Accessed July 2024]
  6. Sciacovelli L et al. (2018). Clin Chem Lab Med 56(10), 1644–1654. Paper available from https://www.degruyter.com/document/doi/10.1515/cclm-2017-1179/html [Accessed July 2024]
  7. Yeo CP and Ng WY. (2018). Singapore Med J 59(11), 597–601. Paper available from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6250760/ [Accessed July 2024]
  8. Haleem A et al. (2021). Int J Intelligent Networks 2, 130–139. Paper available from https://www.sciencedirect.com/science/article/pii/S266660302100021X [Accessed July 2024]
  9. Alowais S et al. (2023). BMC Med Educ 23, 689. Paper available from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10517477/ [Accessed July 2024]
  10. Clearstate. (2023). Article available from https://www.clearstate.com/poct-promises-and-challenges/ [Accessed July 2024]
  11. LabTwin. (2023). Article available from https://www.labtwin.com/blog/lab-trends-2023-sustainability-user-centered-design-interoperability [Accessed July 2024]
  12. Hu H et al. (2022). Annu Rev Environ 47, 173–196. Paper available from https://www.annualreviews.org/content/journals/10.1146/annurev-environ-112320-095157 [Accessed July 2024]