As test complexity and volume grow, pathology labs face increasing pressure to accelerate case processing without compromising accuracy. Traditional batch-processing workflows, which rely on multiple instruments, can drive up operational costs, limit scalability, and create bottlenecks due to lengthy turnaround times, limited capacity, and the hands-on effort needed by lab personnel. Additionally, managing cases across multiple instruments can introduce batch-to-batch inconsistencies and increase the risk of errors.
To meet growing demands, labs are moving toward automated platforms. This technology allows labs to manage higher case volumes by enabling continuous slide loading and unloading and reducing manual workloads. Labs implementing automated platforms have reported a 74 increase in same-day patient case completion and up to a 37 percent reduction in hands-on time, allowing staff to focus on higher-value tasks. For high-throughput labs, successfully implementing this approach requires high-capacity instruments capable of accommodating multiple antibodies in a single run.
Beyond automation, how cases are managed plays an important role in efficiency. A patient case management approach, where all slides from a patient case are kept together, eliminates the need for pre- and post-run sorting, which further decreases hands-on time and improves overall productivity.
This resource guide explores real-world case studies from clinical pathology labs, providing data-driven insights on how automation and process optimization can streamline operations and better support growing testing demands.
Download this resource guide to discover:
Key workflow challenges impacting pathology labs and their effect on turnaround time, efficiency, and accuracy
Case studies showcasing how pathology labs have improved throughput in immunohistochemistry workflows
How automation and patient case management can increase capacity and reduce hands-on time for same-day patient case completion
Cost-saving strategies, including decreasing instrument redundancy, optimizing reagent use, and minimizing overtime
