Accuracy and efficiency have always been paramount in pathology laboratories and are only becoming more urgent. By 2037, demand for pathology services is projected to increase by 16%, while the number of pathologists is expected to decline by 7%, according to the American Society for Clinical Pathology.
Against this backdrop, immunohistochemistry (IHC) has evolved into a cornerstone of modern pathology, linking diagnostic excellence with the biomarker intelligence that guides precision medicine and empowers more personalized patient care. Yet this critical workflow can either accelerate progress or amplify delays that ripple across the laboratory.
When IHC workflows are well coordinated, cases move predictably from order entry to staining, quality control, pathologist review, and reporting. When they are not, the consequences ripple downstream: repeat work increases, staff spend more time managing exceptions, while researchers or patients wait longer for answers.
For clinical laboratories facing rising testing volumes, increasingly complex biomarker testing, and the continued evolution of digital pathology and AI-enabled tools, optimizing their IHC workflow must be a strategic priority.
The root of the problem
IHC is often where operational strain becomes most visible. Orders may arrive through paper forms, manual entry, or disconnected systems. Slides may wait for the next available run. Technologists must constantly balance urgent cases, instrument capacity, staffing coverage, and competing bench priorities.
Over time, this can create a pattern of workarounds: checking queues, reprioritizing stains, chasing missing information, and keeping cases moving despite friction in the process. The most common pressure points often appear at order intake, instrument loading, and unloading.
Teams often lose valuable time to avoidable handoffs, manual documentation, uneven batching, and idle instrument windows. A delayed start, repeat stain, or missed run may seem isolated, but in a high-volume laboratory it can cascade into quality control, case assembly, pathologist review, and report finalization, which adds pressure to staff and slows the delivery of answers.
Moving toward a solution
Adding staff, shifts, or instrumentation may help, but these investments alone rarely solve the underlying problem. Without a clear, data-driven analysis of the laboratory’s operations, added resources can make an inefficient process more expensive rather than more effective.
End-to-end workflow reviews
A comprehensive, end-to-end workflow review brings stakeholders together, including technologists, supervisors, pathologists, IT, and leadership to examine factors shaping day-to-day performance.
This includes examining each step of the IHC process, comparing order-arrival patterns with staffing and instrument availability, reviewing batching and cutoff times, and identifying where handoffs, workstation layout, or information systems create avoidable waiting, motion, or rework. The objective is workflow orchestration to better align people, processes, technology, and timing so that work moves with fewer interruptions and more predictable outcomes.
Quality management and performance
Quality management is also an important part of that conversation. When actively monitored, it helps laboratories see whether workflow changes are improving performance or shifting pressure elsewhere.
Trends in repeat staining, control performance, reagent issues, deviations, and turnaround-time variation can show where standardization is reducing variability and where further refinement is needed. Quality and speed are not competing priorities: optimization means a smoother upstream flow reduces downstream error pressure, while standardization makes results more consistent and turnaround times more predictable.
A clinical lab’s future state may include revised cutoff times, staggered staffing, extended coverage windows, standardized run-start criteria, improved workstation organization, clearer escalation paths, or tighter connectivity between ordering systems, staining platforms, case assembly, and reporting.
Each change should be tied to a defined constraint, supported by realistic change management, and measured against outcomes the laboratory needs most.
Efficiency today, readiness tomorrow
The field is evolving rapidly. Rising test volumes, larger biomarker panels, digital pathology adoption, and AI-enabled tools all depend on workflows that can support consistent, scalable execution. Before adding new technology, laboratories need to understand whether their surrounding infrastructure, including space, staffing, data capture, validation processes, and quality controls, can support it successfully.
Future-ready laboratories will align histology, IHC, molecular testing, digital pathology, and reporting so that each part of the diagnostic pathway supports the next. The goal is to build systems that can absorb greater volume and complexity without requiring proportional increases in staffing or creating new downstream bottlenecks. An evidence-based approach can help laboratories improve their IHC workflow efficiency.
Workflow assessments, optimization tools, advanced staining platforms, reagents, training, and digital pathology solutions can help laboratories identify constraints, improve flow, and support more predictable performance across the diagnostic pathway.
The laboratory is a connected ecosystem, and when the IHC workflow is optimized, teams can spend less time managing avoidable friction and more time focusing on the work that matters most: producing high-quality slides, supporting confident interpretation, and helping deliver timely answers for the people behind every case.
