Written by William Morice II, M.D., Ph.D., president and CEO of Mayo Clinic Laboratories
The clinical laboratory generates immense amounts of data each day that characterizes both healthy and abnormal, or disease, states. This data is so vast it can be overwhelming for individuals to analyze and comprehend. Yet, when combined with increasing computational power and advanced analytics tools, it has the potential to revolutionize healthcare by enabling earlier and more accurate diagnoses, more personalized treatments, and better access to healthcare.
Three key areas evolving rapidly to achieve this transformation include:
- Artificial Intelligence (AI): AI is increasingly changing our daily lives, and medical laboratories are no exception. The exponential growth of health data, combined with increased computing power and the expansion of skilled bioinformaticians and computer scientists, is leading to unprecedented advancements. We are discovering use cases for clinicians using AI algorithms to process and analyze laboratory and other clinical data to diagnose and treat patients at an increasingly rapid pace.
AI is also improving staff experience within the laboratories. Looking at hundreds of samples to find uncommon or rare abnormalities under a microscope is labor intensive. When we use AI solutions to help identify abnormal results, our highly skilled staff can focus on investigating those results to determine if they are potentially significant. This investigation is one of the most enjoyable parts of the job for pathologists and laboratory professionals, and they can now focus more on that fulfilling aspect of their work. In a recent AI implementation, nearly every staff-related measure improved over time, including less ergonomic strain, lower mental demand, fewer physical demands, less time pressure, and improved job satisfaction.
- Digital Pathology: Digitizing laboratory slides and samples offers innumerable benefits. In addition to increasing the proportion of fulfilling work as noted above, capturing the data from the physical slide and moving it into the digital realm enables its contribution to the pool of electronic health data. This will lead to experts developing and training more and more AI models that can help increase the speed and accuracy of clinicians’ diagnoses. Mayo Clinic has digitized over 12 million laboratory slides to leverage them to transform healthcare.
Although the costs associated with digital pathology have been a barrier to adoption, there are signs that these are decreasing. As costs decline and tools that enable efficient workflows become more available, digital pathology is approaching a tipping point where its use will become common, with widespread adoption by pathologists. Ultimately, adoption and workflow improvements will create new opportunities for innovation and research.
Also, digitization will facilitate collaboration central to educating providers and driving healthcare improvement. Removing the limitations of physical slides will make it routine for physicians hundreds of miles apart to evaluate a complex or difficult case simultaneously.
Lastly, applying AI to digital pathology will unlock a new era for biomarker discovery. In this way, digital pathology promises to accelerate our ability to develop new diagnostics and therapeutic solutions and create more personalized treatment plans.
- Proteomics, Metabolomics, and Mass Spectrometry: Mass spectrometry measures the mass-to-charge ratio of molecules, both large and small. Combined with increased computing power, mass spectrometry will drive clinical proteomics (the large-scale study of proteins) and clinical metabolomics (the simultaneous analysis of numerous metabolites and metabolic pathways).
Traditionally, mass spectrometry has been considered a research tool. It is now becoming more accessible and integrated into clinical diagnostics. Automated platforms for mass spectrometry that are starting to be introduced will make the technology more accessible and interpretable. With this, the technology will extend beyond specialized labs to turn proteomic and metabolomic results into clinical answers. As these methods start being used more often to generate clinically actionable results, they will advance diagnosis and disease management.
These advancements not only enhance how we work in diagnostics but also increase the value pathology and laboratory medicine bring to other domains of medicine and clinical care. The success of these initiatives relies on data, and most quantitative data in electronic health records is generated by clinical laboratories. This gives our profession a crucial role in ensuring data is used correctly, interpreted accurately, and applied appropriately. Laboratory professionals’ understanding of the data provides valuable insights into leveraging new tools to improve patient and provider experiences and identifying potential risks.
Clinical laboratory and pathology diagnostics have been at the center of technological innovation in healthcare since the inception of the light microscope. Today, that continues with AI, digital pathology, and mass spectrometry. These technologies are enhancing the accuracy and speed of diagnoses while also driving innovation and improving workflows for our professional staff serving our patients. As the technologies become more accessible and affordable, their impact on healthcare will continue to grow, ultimately leading to better patient outcomes and more personalized treatment plans.