Adoption of a platform approach can significantly reduce the time and costs associated with the deployment of new medical imaging applications and AI algorithms. In this blog, we address some of the questions about deploying a platform.
- What kind of marketplace does it provide?
Platforms that offer a curated marketplace ensure all applications on the platform are vetted and tested to meet strict criteria such as FDA clearance, or clinical and interoperability testing.
- Does it offer secure processing?
The ability to supplement local processing capability with cloud-based processing should be considered as a strategy to minimize hardware costs while supporting future software applications growth and spikes in processing demand. Secure de-identification and re-identification of data must be performed to ensure that personal health information is fully protected and HIPAA-compliant regardless of whether a platform is deployed locally or in the cloud.
- Does it automate workflow?
The platform should be able to automatically extract relevant information and produce results prior to image reading. This can be achieved via the relevancy engine that automates the process of matching incoming study information with the appropriate application, processes the data, and ensures results are quickly sent back to the right system.
- What is the provider’s customer service reputation?
The platform provider should have a reputation for providing excellent customer service and training, not only for the platform but also for the applications available on it. The platform vendor should provide a single point of contact for the purchasing, contracting, and financing of the platform and the applications available in the marketplace.
- How strong is the provider’s technical expertise?
The platform should have excellent documentation and controls around security and HIPAA compliance and provide the appropriate legal privacy protections. It should be fully integrated with existing systems, able to prove its ability to manage proprietary and OEM-specific implementations of the DICOM standard, and disparate backend and user interface configuration challenges. A high-quality platform will also provide data analytics that spans all applications on the platform, as well as allowing the adoption of varying deployment approaches.
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