Patient safety unites all healthcare stakeholders. However, despite this shared goal, safety-oriented innovations are rarely implemented simultaneously throughout the healthcare process. Pathology often stands at the end of the line for new technologies and workflow advancements. As a result, many labs continue to face end-to-end challenges associated with traditional processes that rely on manual completion.
Manual pathology workflows are the greatest risk to patients. Tim Spong, founder and CEO of Vistapath, witnessed firsthand just how dangerous a simple mistake can be during grossing — the pivotal first step characterized by highly manual workflows. During Tim’s tenure as a Lab Director at a top-tier hospital, a sample mix-up resulted in unnecessary surgery for one patient and a false positive for another patient. Unintentional medical errors like this cause significant, lasting harm to patients and families.
Motivated to improve patient safety, Tim began searching for new solutions to close the gaps in quality management. He quickly realized that artificial intelligence (AI) had the power to move the pathology process as a whole into a new era of efficient, error-free diagnostics.
Exploring the Benefits of AI-Driven Pathology
Grossing is often the primary source of errors during the diagnostic process. Up to 68% of lab mistakes occur during the preanalytical phase, initiating a cascade of errors that lead to incorrect conclusions and diagnoses.1 This is largely attributable to human limitations during the grossing process, such as fatigue, oversight, the potential for errors, and often the sheer volume of work.
To help overcome these limitations, AI can be implemented into the grossing process to optimize lab workflows and ensure patient safety from start to finish. In addition to driving efficiency, AI-based pathology lab automation elevates quality management and reduces safety risks in six key ways:
- Improving consistency. AI platforms like Sentinel have the advantage of consistent precision. These systems operate by a predefined set of parameters to uphold the same standard of grossing every time. By eliminating the variations introduced by human factors, AI automation can significantly improve the reliability of gross reports and diagnostic results.
- Detecting errors. In addition to streamlining time-consuming tasks, AI can also flag anomalies or inconsistencies in samples. This serves as a double-check mechanism for pathology technicians, especially during times of high case volumes. Moreover, AI can detect irregularities that might be missed by the human eye, further reducing the likelihood of diagnostic errors.
- Reducing sample contamination. AI augmentation systems can reduce the need for extensive human contact with samples. This, in turn, minimizes the risk of sample contamination — a crucial factor in ensuring safety for patients whose tissues are being handled at the same time in the lab.
- Enhancing safety protocols. With built-in safety measures and protocols, AI systems are well-equipped to recognize and immediately point out any deviations from standard operating parameters. This proactive approach to quality control further improves diagnostic accuracy and downstream patient safety.
- Continuously learning. A substantial short- and long-term benefit of AI augmentation is the ability to adapt over time to meet individual lab needs. These systems are not static; they continually learn from new data. This iterative process further improves detection capabilities and strengthens safety protocols over time.
- Empowering pathologists. Contrary to the misconception that AI aims to replace pathologists, digital grossing systems like Sentinel are designed to augment their capabilities by automating repetitive tasks, allowing pathologists to focus on more complex and intellectually demanding aspects of their work. Pathologists can leverage AI-generated insights to make more informed diagnostic decisions and ultimately improve the quality of patient care.
The AI Revolution: The Next Step in Elevating Patient Safety
The incorporation of automation and AI in pathology lab workflow has far-reaching implications for patient safety and healthcare outcomes. By minimizing errors, labs can provide consistently accurate diagnoses and effective treatment plans. This, in turn, reduces the potential harm to patients and ensures they receive the right care at the right time.
As Vistapath’s flagship technology, Sentinel exemplifies this drive for innovation in pathology to ensure the best possible patient outcomes. Through an AI-equipped workbench, Sentinel helps labs achieve faster end-to-end grossing by automatically photographing and measuring samples in less than one second. This optimized workflow paves the way for greater accuracy, efficiency, quality, and — most importantly — safety.
Sources
- Mrazek, C., Lippi, G., Keppel, M. H., Felder, T. K., Oberkofler, H., Haschke-Becher, E., Cadamuro, J. (2020). Errors within the total laboratory testing process, from test selection to medical decision-making – A review of causes, consequences, surveillance and solutions. Biochemia Medica 30(2), 020502.
