Rapid Response Made Easy
Our user-friendly interface guides staff through SBARI (Situation, Background, Assessment, Recommendation, Intervention) makes documentation easy, ensuring consistent communication and timely interventions.
AI Powered Insights for Clinicians
We combine your existing early warning scores with an AI-driven analysis of patient vitals, nurse notes, and EHR data. This hybrid model enriches situational awareness, offering clinicians richer insights while keeping them in charge of final decisions.
Leveraging Predictive AI for Early Intervention
The RRT CoPilot transforms how hospitals manage patient deterioration by replacing traditional methods like phone calls and pagers with AI-powered alerts and real-time communication. This system constantly monitors patient data, using algorithms to detect early signs of clinical decline through changes in vital signs. This allows the Rapid Response Team (RRT) to intervene early, potentially reducing ICU transfers and improving patient outcomes while also lowering hospital costs.[1]
Discover RRT CoPilot's Key Features
Predictive Patient Monitoring
Our advanced algorithms anticipate patient decline, alerting the Rapid Response Team before a crisis occurs.
Instant Access to Patient Data
With RRT CoPilot, the entire Rapid Response Team has instant access to the patient's clinical history, vital signs, and recent lab results on their mobile devices.
Real - Time Alerts and Messaging
RRT CoPilot’s built-in messaging features allow team members to communicate in real-time, ensuring everyone stays updated on the patient’s condition and required interventions.
SBARI
Our systematic SBARI tool features a structured checklist that captures essential patient details, ensuring accurate communication and supporting effective interventions in critical medical situations.
Automated Documentation
RRT CoPilot streamlines post-event documentation by automatically recording details such as response times, interventions, patient vitals, and event durations.
Enhanced Training and Education
RRT CoPilot provides a comprehensive record of every response event, which hospitals can use to train staff, reinforce best practices, and ensure consistency in care delivery.
HIPAA Compliance and Interoperability
RRT CoPilot is fully HIPAA compliant and integrates seamlessly with major Electronic Health Record (EHR) systems, including Cerner, EPIC, and Meditech, ensuring interoperability across healthcare organizations. We offer flexible deployment options, including cloud, on-premises, or private-cloud configurations, all with strict compliance protocols. For Azure users, our AI module integrates seamlessly with HIPAA-eligible environments. We also ensure Business Associate Agreements (BAAs) are in place to meet HIPAA requirements.
Seamless Integration with EHR and Hospital Systems
RRT smoothly with most Electronic Health Record (EHR) systems, ensuring that patient data flows effortlessly between RRT CoPilot and your hospital’s existing infrastructure.[11] Our system automatically pulls critical information like patient history and recent lab results, providing the Rapid Response Team with all necessary data in real-time. This integration minimizes manual data entry, reduces the risk of errors, and allows your team to focus on patient care.[12]
FHIR - Enabled
Real-time retrieval of vitals and lab results for automated scoring.
Data Mapping
Custom mappings to align with your unique EHR fields.
Data Security
On-premises, private cloud, or hybrid setups for diverse IT infrastructures.
Clinical and Financial Benefits You Can Count On
Learn how RRT CoPilot can improve hospital management, reduce LOS, and prevent ICU transfers. Enter your email to download the Financial Impact Report.
Download Financial Impact Report
Reduced Unplanned ICU Transfers
Earlier detection can help lower the need for higher-acuity care.
Shorter Length of Stay
Swift identification of deterioration supports timely intervention and discharge.
Improved Team Coordination
Standardized SBAR/SBARI communication keeps the entire care team aligned.
Streamlined Staff Workflows
Automated communication and reporting free up clinical staff, allowing them to focus on patient care.
Interoperability with Major EHR Systems
Seamless integration with Cerner, EPIC, and Meditech enhances workflow efficiency, enabling better data sharing and coordination.
Bibliography
- Kale, D., & Mulla, J. M. S. (2024). AI In Healthcare: Enhancing patient outcomes through predictive analytics. ResearchGate https://www.researchgate.net/publication/382949199_AI_In_Healthcare_Enhancing_patient_outcomes_through_predictive_analytics
- Data-driven decision-making in healthcare: Improving patient outcomes. International Journal of Scholarly Research in Multidisciplinary Studies. https://srrjournals.com/ijsrms/content/data-driven-decision-making-healthcare-improving-patient-outcomes-through-predictive
- Smartphone alerts may lead to faster response to in-hospital cardiac arrest, 'code blue.' American Heart Association https://newsroom.heart.org/news/smartphone-alerts-may-lead-to-faster-response-to-in-hospital-cardiac-arrest-code-blue
- Giordano, C., Brennan, M., Mohamed, B., Rashidi, P., Modave, F., & Tighe, P. (2021). Accessing artificial intelligence for clinical Decision-Making. Frontiers in Digital Health, 3 https://doi.org/10.3389/fdgth.2021.645232
- Biswas, A., & Talukdar, W. (2024). Intelligent Clinical Documentation: Harnessing generative AI for Patient-Centric Clinical Note Generation. International Journal of Innovative Science and Research Technology (IJISRT), 994–1008 https://doi.org/10.38124/ijisrt/ijisrt24may1483
- Siju, J., Orekoya, G., Vernet, E., & Anagboso, U. (2021). Developing a standardized method for clinical staff training, education, and competency. Journal for Nurses in Professional Development, 39(1), 27–32. https://doi.org/10.1097/nnd.0000000000000821
- Dykes, P. C., Lowenthal, G., Lipsitz, S., Salvucci, S. M., Yoon, C., Bates, D. W., & An, P. G. (2021). Reducing ICU utilization, length of stay, and cost by optimizing the clinical use of continuous monitoring system technology in the hospital. The American Journal of Medicine, 135(3), 337-341.e1. https://doi.org/10.1016/j.amjmed.2021.09.024
- McGaughey, J., Fergusson, D. A., Van Bogaert, P., & Rose, L. (2021). Early warning systems and rapid response systems for the prevention of patient deterioration on acute adult hospital wards. Cochrane Library, 2021(11). https://doi.org/10.1002/14651858.cd005529.pub3
- Stephen, M., & Frank, L. (2024). The role of electronic health records in transforming healthcare delivery and financial gains. ResearchGate. https://www.researchgate.net/publication/377407661_The_Role_of_Electronic_Health_Records_in_Transforming_Healthcare_Delivery_and_Financial_Gains
- Gallagher, D., Zhao, C., Brucker, A., Massengill, J., Kramer, P., Poon, E. G., & Goldstein, B. A. (2020). Implementation and continuous monitoring of an Electronic Health Record embedded Readmissions Clinical Decision Support tool. Journal of Personalized Medicine, 10(3), 103. https://doi.org/10.3390/jpm10030103
- Jacob, P. D. (2019). Management of patient healthcare information. In Elsevier eBooks (pp. 35–57). https://doi.org/10.1016/b978-0-12-814309-4.00003-3
- Pushadapu, N. (2020, May 20). Real-Time integration of data between different systems in healthcare: Implementing advanced interoperability solutions for seamless information flow. https://dlabi.org/index.php/journal/article/view/90