Specific calculation method for return on investment of AI implementation
Posted: Wed Feb 19, 2025 3:20 am
Introducing AI to a medical institution requires two main investments: initial costs and operational costs. Initial costs include the cost of customizing the system to suit the medical field, the cost of preparing data required for training the AI model, and the cost of custom development and customization of existing tools. Operational costs include
continuous tuning costs for the AI system, high-performance infrastructure usage fees, and API usage fees. However, these investments are well worth it from a long-term perspective.
In actual implementation cases, the introduction of image diagnosis support AI has significantly reduced diagnosis time and successfully reduced doctors' working hours. In addition, there are medical institutions lebanon whatsapp number data that have significantly reduced labor costs for responding to inquiries at night by introducing 24-hour AI chatbots. When calculating
ROI, it is important to consider not only the cost reduction effect but also the composite effects such as improved patient satisfaction and an increase in new patients.
3-2. Three steps to introducing medical AI and preparation for success
A step-by-step approach is important for the successful introduction of AI to medical institutions. First, a current situation analysis and requirements definition are performed before introduction, and the existing work flow is visualized. This allows the business process after the introduction of AI to be simulated and potential issues to be identified.
Next, medical data is collected and annotation work is carried out. At this stage, a mutual checking system by multiple staff members, including specialists, is established and regular adjustments of judgment criteria are required.
After that, a PoC is carried out on a limited scope to verify the effectiveness of the system and to quickly identify issues in operation. During this process, the impact on the work flow of medical personnel and operability are also evaluated.
Finally, an appropriate vendor is selected. Effective AI introduction can be achieved by comprehensively evaluating the understanding of medical-specific requirements, the explainability of the AI model, integration track record with existing systems, data management system, etc., and selecting a reliable partner.
continuous tuning costs for the AI system, high-performance infrastructure usage fees, and API usage fees. However, these investments are well worth it from a long-term perspective.
In actual implementation cases, the introduction of image diagnosis support AI has significantly reduced diagnosis time and successfully reduced doctors' working hours. In addition, there are medical institutions lebanon whatsapp number data that have significantly reduced labor costs for responding to inquiries at night by introducing 24-hour AI chatbots. When calculating
ROI, it is important to consider not only the cost reduction effect but also the composite effects such as improved patient satisfaction and an increase in new patients.
3-2. Three steps to introducing medical AI and preparation for success
A step-by-step approach is important for the successful introduction of AI to medical institutions. First, a current situation analysis and requirements definition are performed before introduction, and the existing work flow is visualized. This allows the business process after the introduction of AI to be simulated and potential issues to be identified.
Next, medical data is collected and annotation work is carried out. At this stage, a mutual checking system by multiple staff members, including specialists, is established and regular adjustments of judgment criteria are required.
After that, a PoC is carried out on a limited scope to verify the effectiveness of the system and to quickly identify issues in operation. During this process, the impact on the work flow of medical personnel and operability are also evaluated.
Finally, an appropriate vendor is selected. Effective AI introduction can be achieved by comprehensively evaluating the understanding of medical-specific requirements, the explainability of the AI model, integration track record with existing systems, data management system, etc., and selecting a reliable partner.