Digital pathology for efficiency, diagnostic accuracy and improved collaboration at Hallym

The challenge was to update pathology capabilities across four hospitals at once to increase image sharing, consultation, diagnostic confidence and workflow efficiency. The Hallym teams knew that the time had come to move from analog to digital pathology, and they searched for a partner with the experience and capabilities to help make the digital transition a success. The solution? Working with Philips, they were able to centralize management through a single platform for all pathology slides across the four hospitals with improved network consultation, standardized pathology operations, automated workflows and AI-based analysis for rapid diagnostic support.

The institution searched for a digital pathology solution it could use across its four hospitals (Hallym University Sacred Heart Hospital, Kangnam Sacred Heart Hospital, Chuncheon Sacred Heart Hospital and Dongtan Sacred Heart Hospital). Hallym University Medical Center chose Philips, and its digital pathology system has been in full production across all four hospitals since March 2025. After an initial pilot operation, the majority of pathology diagnoses are now performed through the digital platform, leading to improved collaboration, more efficient workflows and increased diagnostic confidence.

Connecting four hospitals through one unified digital pathology network has produced positive results.

Mr. Jung says that the digital pathology solution also helps optimize healthcare resources through a centralized infrastructure that avoids the need for duplicate investments in expensive equipment, reducing operating costs. Standardization increases diagnostic consistency because all four hospitals use the same digital pathology platform and AI tools.

The integrated database facilitates data-driven management for clinical trend analysis and pathology research. The patient experience is improved through the complete tracking of diagnostic history during patient transfers, preventing duplicate diagnoses. The platform’s scalability allows for the rapid application of new technologies such as AI and machine learning across all four sites.

Professor Eun Shin of the Department of Pathology explains how the solution is helping clinicians speed time to diagnosis while enhancing diagnostic confidence.

“Since the introduction of digital pathology, the diagnostic process has been systematically improved, and we are experiencing both workflow improvements and improved diagnostic confidence,” says Prof. Shin. She points out that the transition from paper-based slide management to a digitized system has made slide retrieval and storage much easier, and that high-resolution digital images enable clearer observation of detailed structures than before. There is also no longer the need to search for or carry physical slides, which increases workflow efficiency. The standardization of digital images allows for greater consistency, with the same observed results across repeated reviews. She explains: “The high-magnification zoom functions (zoom-in/out) enable detailed examination of fine structures, and the team finds that it is easier to maintain diagnostic accuracy without the physical fatigue caused by microscope use.”

Integration with the laboratory information system (LIS) has substantially improved collaboration between pathology and clinical departments. Information is now more accessible. In fact, clinicians can now access pathology diagnostic results through the LIS whenever needed. Communication is improved, and consultations that previously required phone calls or direct visits can now proceed more systematically through digital platforms.

Emergency response is also improved, because the system is able to respond quickly when pathology results are needed in urgent clinical situations. Now clinicians at each hospital can easily consult with pathology specialists at other hospitals, which is particularly useful when gathering multiple expert opinions on complex cases. All four hospitals use the same digital platform, improving consistency of diagnostic criteria.

Professor Shin points out that the previous analog system required a visit to the pathology department to view slides, with direct meetings with a pathologist necessary for explanations. Remote physicians lacked access to the system, and information sharing was irregular. Now remote consultation across the four hospitals is routine. Clinicians can view slides anytime from their own offices, with asynchronous consultation possible through memo and annotation features on digital platforms. All of this has led to shortened meeting times and the ability for rapid response to emergency cases. Specialists from all four hospitals can simultaneously participate in reading a case.

Professor Shin says that morphometric AI* is used as an assistive tool to support the pathology team's diagnoses. Nuclear morphometry automatically analyzes the size and shape of nuclei in cancer tissue for reference in malignancy grading. AI adds objective metrics to pathologists' subjective judgments, providing specific evidence for why a particular diagnosis was reached.

Professor Shin notes that AI does not completely replace pathologists' professional judgment, and the final diagnosis remains the responsibility of the pathologist. She says, “AI's assistive function is particularly meaningful in borderline cases where the diagnosis is not clear. In some cases, the pathologist’s experiential judgment may be more accurate than AI results.”

“The Philips team actively listens to our feedback,” she says. “System stability is solid, and the system has not experienced any major failures.” Prof. Shin expects that AI capabilities will be further enhanced through continuous technological innovation. “Our key reasons for choosing Philips are end-to-end integrated solutions and reliable technical support,” she says.

“Philips provides a consistent platform from scanners to software to AI*, minimizing system compatibility issues. The company has the experience and capability to successfully manage the complex project of connecting four hospitals on a single platform, with a commitment to ongoing support that goes beyond the initial implementation to include long-term operation and technological innovation.”

She continues: “We judged that the Philips AI algorithms* and scanner performance could meet our requirements, and we expected that diagnostic standardization would be possible as pathologists from all four hospitals use the same platform.” The stability and reliability that Philips brings as a global medical device company, along with reference implementation cases from major domestic and international medical institutions, boosts confidence.

Professor Shin expects to expand AI utilization for various cancer types (e.g., lung cancer and colon cancer). The institution is further developing its system for clinical collaboration and plans to hold regular consultation meetings (image-based conference) utilizing digital slides and will continue creating an environment where clinical staff can more easily access pathology diagnoses. Prof. Shin expects to be able to initiate more clinical research based on the digital diagnostic data that will be gathered.