With as few as one to three pathologists per million people in some regions, access to timely surgical pathology remains limited across Kenya. Following her PathVisions 2026 presentation, Maureen Waithaka discusses how a modular digital pathology network is expanding access to surgical pathology across Kenya – and why local training, reliable logistics, and data governance are central to its growth.
What are the main barriers to accessing timely, high-quality pathology services in Kenya and other low- and middle-income countries?
The main barriers are shortages of pathologists, a lack of laboratories equipped for histology, and fragmented diagnostic resources. There are approximately one to three pathologists per million people, many of whom are concentrated in major towns and cities. For some communities, the nearest pathologist or histology laboratory is hundreds of miles away.
Traditional pathology infrastructure remains underdeveloped in many areas. As a result, some hospitals perform surgery without access to an on-site surgical pathology service. Socioeconomic marginalization and limited transportation create further barriers to timely, high-quality diagnosis.
How does your modular digital pathology model differ from systems developed for high-income healthcare settings?
Our modular digital pathology model is designed around local workforce and infrastructure constraints. The workflow accounts for transporting and tracking specimens from surgical hospitals to partner laboratories, as well as moving glass slides from processing laboratories to pathologists across the network for reporting. This allows a relatively small number of laboratories and pathologists to support multiple sites over large geographic areas.
We use comparatively low-cost hardware and match equipment capacity to testing volume. Logistics and quality control are treated as core parts of the service because, in our setting, these are often the points at which diagnoses are delayed or lost.
How does dividing the pathology workflow into interconnected modules help laboratories overcome infrastructure, staffing, and geographical constraints?
Laboratories no longer need to house extensive preparation equipment, physical slide archives, and pathologists in one location. Dividing the workflow into separate modules for slide preparation, courier logistics, and pathologist review can improve operational efficiency.
Centralizing tissue processing within laboratory hubs allows small technical teams to prepare slides in batches during predictable shifts. The workload can then be organized so off-site pathologists receive a steady, manageable flow of cases across large geographic areas rather than irregular backlogs.
The pilot reportedly reduced diagnostic turnaround times by 70 to 90 percent. What changes made this possible, and how has faster reporting affected patient care?
A centralized software platform connecting hospitals, laboratories, and pathologists has turned a fragmented process into a coordinated diagnostic workflow. This has expanded access to reliable surgical pathology services in historically underserved communities where diagnostic infrastructure was previously limited or unavailable.
Streamlined specimen and slide transport, combined with digital data routing, allows reports to reach requesting clinicians much faster than when patients were responsible for coordinating these steps. Timelier diagnoses also support earlier access to subsequent care, including oncology treatment.
How do centralized coordination and remote reporting support diagnostic quality, consistency, and access across the 30 participating hospitals?
Our latest data show that the network has served 79 facilities, up from 30 previously. Centralized coordination and remote reporting support this multi-hospital network through standardized protocols and reporting templates.
Pooling pathologists’ expertise also supports diagnostic quality through peer review and consensus reporting. Centralized governance enables network-wide data tracking and helps ensure that partner facilities follow consistent, benchmarked processing standards.
Through the digital network, patients in areas without local pathology services can access a pathologist without traveling long distances. They can also benefit from the same level of diagnostic expertise available in larger towns and cities.
What role do local pathologists, laboratory professionals, and locally generated data play in making the model sustainable and supporting more representative AI development?
A network like ours depends on its people. Pathologists provide diagnoses that local clinicians can trust, while laboratory professionals produce the high-quality slides on which those diagnoses depend. Training histotechnologists and pathologists locally helps retain expertise and enables services to expand into more communities.
Local expertise is equally important for developing representative AI. An algorithm is only as reliable as the slides and diagnoses used to train it, yet many existing datasets do not adequately represent African populations. Slides from our patients may differ in tissue characteristics, disease patterns, staining, and scanner type. Local pathologists should establish the diagnostic ground truth, while well-trained laboratory teams maintain the consistent slide quality required for reliable data.
African health data should remain under African governance, with local partners sharing in the tools and knowledge developed from it. Systems trained using slides from local patients may be better suited to the populations they are intended to serve.
Looking ahead, what could this model improve in Kenya, and what would be needed to adapt and scale it across other low- and middle-income countries?
In Kenya, this model could reach more facilities and shorten diagnostic turnaround times for additional communities. Expanding immunohistochemistry capacity and digitization could strengthen patient services while generating the local datasets needed to develop more representative AI. A reliable national diagnostic network may also support the case for greater public investment in pathology services.
Other low- and middle-income countries face similar shortages of pathologists and tissue-processing facilities, although their health systems, regulations, and payment structures differ. The broader approach can be adapted by designing services around local workflows, integrating specimen transport and quality control, matching equipment to testing volume, and training the local workforce.
Further expansion will require equitable partnerships that preserve local ownership in Kenya. Funding must support system-wide growth, including standardized training programs, while federated data agreements could allow countries to share knowledge and experience without relinquishing control of their health data.
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