From the November 2019 issue of HealthCare Business News magazine
7. Deployment
Delivering an AI solution to the healthcare provider in a secure, fast, and cost-effective manner is key for its success.
Questions the radiologist should ask:
• Is the AI solution installed locally on-premise, or does it require access to a cloud server?
• If cloud-based, is the protected health information (PHI) removed before the image is analyzed by the AI algorithm?
• Does the AI algorithm require a dedicated virtual machine? Can it be containerized (e.g., Docker)?
8. Support and contracting
As radiologists implement AI solutions from multiple vendors, consideration should be given to the administrative overhead of handling individual contracting and invoicing. The level of technical support provided by algorithm developers is another important consideration, along with accountability, should the algorithm negatively impact the performance of the PACS.
Questions the radiologist should ask:
• Who will provide technical support for the AI algorithms? Will it be the algorithm developers or their distribution partners?
• How will the solution be licensed? Will it be a one-time (perpetual) license fee, or will it be a recurring software-as-a-service (SaaS) license?
• What is the pricing model used by the developer? Do they set a fee on a pay-per-use basis (e.g., dollars per set number of scans), or do they charge one price (regardless of the algorithm usage)?
9. Capital funding
Many of the AI algorithm developers are startup companies that rely on external capital funding. The ability to raise capital through multiple funding rounds is reflective of a vendor’s potential long-term success.
Questions the radiologist should ask:
• How much capital funding has been raised to date, and who are the investors?
• How many funding rounds has the vendor secured?
• How long does its typical funding round last and when was the most recent round completed?
