The use of Vsee videoconferencing for live telepathology in Rwanda, a potential solution for resource-limited area

Author:

Manirakiza Felix123ORCID,Niyoyita Jean Paul2,Habanabakize Thomas1,Ndagijimana Emmanuel45,Surwumwe Jean Bosco3,Rugwizangoga Belson13

Affiliation:

1. Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda

2. Department of Health Informatics, School of Public Health, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda

3. Department of Pathology, University Teaching Hospital of Kigali, Kigali, Rwanda

4. Department of Biostatistics, School of Public Health, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda

5. The African Center of Excellence in Data Science, College of Business and Economics, University of Rwanda, Kigali, Rwanda

Abstract

Objective The shortage of pathologists is a worldwide problem that is more severe in Africa. One of the solutions is the use of telepathology (TP); however, most of the TP systems are expensive and unaffordable in many developing countries. At the University Teaching Hospital of Kigali, Rwanda, we assessed the possibility of combining commonly available laboratory tools into a system that can be used for diagnostic TP using Vsee videoconferencing. Methodology Using an Olympus microscope (with a camera) operated by a laboratory technologist, histologic images were transmitted to a computer whose screen was shared, using Vsee, with a remotely located pathologist who made the diagnoses. Sixty consecutive small biopsies (≤6 glass slides) from different tissues were examined to make a diagnosis using live Vsee-based videoconferencing TP. Vsee-based diagnoses were compared to pre-existing light microscopy-based diagnoses. Percent agreement and unweighted Cohen’s kappa coefficient of the agreement were calculated. Results For agreement between conventional microscopy-based and Vsee-based diagnoses, we found an unweighted Cohen’s kappa of 0.77 ± 0.07SE with a 95% CI of 0.62–0.91. The perfect percent agreement was 76.6% (46 of 60). Agreement with minor discrepancy was 15% (9 of 60). There were 2 cases of major discrepancy (3.30%). We were unable to make a diagnosis in 3 cases (5%) because of poor image quality related to the instantaneous internet connectivity problems. Conclusion This system provided promising results. However, additional studies to assess other parameters which can affect its performance are needed before this system can be considered an alternative method of providing TP services in resource-limited settings.

Publisher

SAGE Publications

Subject

Health Information Management,Computer Science Applications,Health Informatics,Health Policy

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