Development of a Cost Model for Telemedicine Based on Medical Image Processing
DOI:
https://doi.org/10.22034/TJT.2.4.63Keywords:
Telemedicine, Artificial Intelligence, Medical Image Processing, Cost-Benefit AnalysisAbstract
Telemedicine has become an essential platform for delivering remote clinical services, particularly in specialties that are dependent on medical imaging. While AI-driven image-processing technologies can enhance diagnostic accuracy and improve workflow efficiency, most current telemedicine evaluations overlook their economic implications. This paper seeks to fill this gap by developing a dedicated economic framework for the costs and benefits of medical image processing. A three-phase approach was adopted. In the first place, a structured search across the major academic databases evaluated whether already published economic models included image-processing costs. Then, technical and financial parameters were integrated into a quantitative break-even model. Finally, experts in telemedicine, medical imaging, and health technology assessment reviewed the model, and its components were evaluated using Content Validity Index scores. The literature review revealed no previous models focused on image-processing costs, whereas expert assessment confirmed strong clarity and relevance in all components of this model. This validated framework provides a comprehensive basis for detailed estimates of implementation expenses, quantified potential savings, and the required patient volume to achieve financial sustainability. Further research should apply and test this model within a variety of clinical contexts.
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