Emergent Virtual Face-to-Face Network Platform
Location:
New Jersey, United States
Posted on:
Deadline:
Summary:
RFI for a clinical platform to manage virtual encounters, integrate with existing records systems, and support real-time communication, operational dashboards, and AI capabilities.
Get full access to this RFP
Download the full RFP document and use Settle's AI to analyze requirements, estimate budget, and draft winning responses in minutes.
This RFI seeks vendors to provide an emergent virtual face-to-face network platform designed to facilitate the management of all aspects of virtual clinical encounters. The platform should enable efficient triaging, patient tracking, and seamless communication and coordination among care team members. It must allow staff to find all necessary information and complete their tasks directly within the platform, promoting continuity and offering read/write integration with existing systems such as VistA/Computerized Patient Record System (CPRS) and the Oracle Federal Electronic Health Record (EHR).
The solution should improve provider efficiency and enable effective, coordinated emergent and urgent care, featuring intuitive workflows for clinicians, standard clinical language, and robust tools for care delivery, documentation, order entry, care coordination, and follow-up. Real-time escalation protocols are necessary for critical cases requiring emergent in-person care, and the platform should include an e-prescribing capability for prescriptions to external pharmacies.
Additional requirements include native video, phone, chat, and text messaging functions, meeting or exceeding industry standards for successful video encounters. The platform must also produce real-time operational dashboards with metrics such as patient volume, wait time, and open orders. Options for AI virtual assistants should be available to collate relevant information and resources, and the platform must support multi-language accessibility and integration with vSignals data to display patient satisfaction analytics.
