Bringing advanced clinical tools to the bedside to enhance medical decision making
Call9 has created a custom technology platform that includes both web and Android applications for the Call9 clinical team in addition to a data platform that can be accessed directly by skilled nursing facility (SNF) leadership.
for Call9 Providers
All historical and real-time patient data from disparate sources is localized onto a single web platform that serves as the central hub for Call9’s clinical activity. Call9’s remote providers can interact with both the patient and the on-site Clinical Care Specialist (CCS) via multi-camera screens, review real-time medical data streaming in from the on-site diagnostic cart and track and make decisions about patient care, follow-up and documentation without ever leaving the Call9 platform.
for Call9 CCSs
The CCS uses the Android app at the bedside to send medical data and enable real-time communication with the patient. The app sends data from medical equipment, such as the EKG, Ultrasound, i-STAT machine and EKO stethoscope, to our web platform. Within seconds, the remote provider can access critical diagnostics, such as vital signs, lab results and other patient statuses that the CCS has input and/or connected in the app.
for SNF Administrators
SNF Assist, Call9’s proprietary management tool, delivers value through analytics and real-time actionable insights for our partners. SNF Assist helps facility leadership and medical teams predict trends in patient decompensation and transfer rates by providing data that can be used to target performance improvement interventions and drive transfer rates down.
Proprietary dashboard enables the physician, CCS and patient to all see and interact with each other in real-time.
Information & Documentation
EMR integration seamlessly displays the right patient information at the right time, as well as shares Call9’s patient documentation with all other medical stakeholders.
Live Streaming Diagnostics
Enhanced suite of bedside diagnostics deliver clinical tools to nursing homes that are traditionally only available in a hospital setting.
Data analytics and machine learning techniques provide the framework to predict which patients are at the highest risk for hospital transfer.