Notice ID: 36C10B21Q0143
This RFI is issued for the purpose of collecting information about a next generation Teleradiology PACS (Picture Archive & Communications System) as described below.
(a) VHA National Teleradiology Program (NTP) is VA s in-house teleradiology service and has been providing 24×7 service to VA facilities for the past decade. NTP is currently supporting over 120 sites across all VISNs and is projected to interpret between 1.0 and 1.5 million studies annually. NTP presently has reading centers located in the following cities: Durham, NC; New York, NY; Dallas, TX; San Bruno, CA; Menlo Park, CA; Sacramento, CA; Los Angeles, CA; Portland OR; and Honolulu, HI and has approximately 100 Radiologists working remotely via home PACS workstations with VA VPN connections.
(b) NTP is currently surveying industry to identify potential vendors who would be capable of providing NTP with a best in breed, next generation modular PACS that incorporates at a minimum the following preliminary features: Cloud-based vendor neutral archive with local image cache at reading centers for optimal display and reading performance. Workflow/assignment engine for subspecialty assignment, image routing and turn-around time optimization Real-time productivity tracking for each Radiologist Master patient index to address VA s conversion from VistA to Cerner EMR and the change in primary identifier from SSN to EDIPI. System must be able to seamlessly function with both VistA and Cerner EMR interfaces and be able to utilize the appropriate primary patient identifier for each respective system to uniquely identify patients and ensure a patient s data appears as a singular instance within the PACS. Zero footprint web viewer for referral viewing and internal NTP Support use Workflow tools such as integrated ad-hoc and assigned peer review, Tech/image quality feedback, critical result notification/callback, NTP PACS Assistant image intake portal for pre-read QC, etc. Multiple voice recognition system options that can be integrated with the VA PACS Artificial Intelligence functionality, with integrated image routing and analysis at a minimum to include intracranial hemorrhage detection and lung nodule detection with measurement and classification HL7 and DICOM integration to all VA PACS, Cerner image archives, and HL7 instances from VistA and Cerner. Must be able to query all connected image archives using the primary patient identifier within each respective PACS instance. The system will be scalable such that VISNs could elect to deploy the system as their in-house PACS and would have their worklist, user database, voice recognition and workflow tools separate and distinct from NTP.
