Woven Care Intelligence
Woven care intelligence is a transformative approach to clinical AI that weaves together patient data, clinical care teams and AI tools to dramatically improve patient care and facility outcomes.
© Copyright 2024 Aidoc
A Solution to Fragmentation in Healthcare
With siloed information in a complex system, the threads in your hospital are disconnected. While different AI tools have shown promise, they’ve ultimately offered disjointed experiences to users and patients, feeding further fragmentation — fragmentation that can have deadly consequences.
Woven care intelligence is here to change that. As the architect that weaves disparate threads together, woven care intelligence is an approach that creates a smarter, more connected healthcare system and better outcomes for patients.
AI-Driven Patient Journeys
WCI must deliver AI-generated clinical insights integrating with existing clinical workflows and communication channels by sending prioritized, tailored and accurate notifications to appropriate care teams, enabling AI-driven care coordination for timely and effective care across different care settings from the walls of the hospital to outpatient care.
Precision AI Directed By Orchestration and Monitoring
WCI must deliver clinical-grade accuracy through AI-generated clinical insights in real-world environments. It manages the complex, tangled weave of healthcare data, including predictable, unpredictable, structured, and unstructured inputs, normalizing, monitoring and orchestrating to achieve consistent high performance and mitigate data drift.
Physician-Tailored Engagement Via Multimodal Integration
WCI must integrate multiple data sources (EHR, PACS, scheduling, etc.) to break down data silos, identify clinically important insights and create a comprehensive patient profile. It then filters only the relevant information and delivers these insights in a physician-tailored view, enabling effective and efficient AI utilization.
The Definitive Guide to Woven Care Intelligence
Many AI tools have shown promise, but in fragmented hospital systems, they create more silos. Find out how woven care intelligence weaves these disparate threads together to create a unified approach to AI.
Woven care intelligence is a dramatic shift in the way hospitals leverage the power of clinical AI. Here’s how it compares to the outgoing paradigm.
Outgoing AI Paradigm
Protocol-based algorithms only identify specific pathologies
Single-focused AI solutions operate in silos with fragmented data
Lack of cohesive communication system leading to incomplete workflows
Manual algorithm monitoring
Each solution requires its own strategy, maintenance and deployment plan
Woven Care Intelligence
Always on orchestration automatically deploys all available AI based on anatomy present
Connects disconnected systems and data to create a comprehensive view of patients
Alerts tailored to individual clinical preferences and workflow
Automated algorithm monitoring and management
A platform to deploy any number of AI solutions with future-proof scalability
Health System Impact
Financial Performance:
Improved revenue streams from additional interventions while also enabling cost containment from reductions in readmissions and length of stay
Operational Optimizations:
Improved resource allocation reduces waste and eliminates redundancies in systems and processes
Clinical Outcomes:
Improved workflows and cross-department communication enables more efficient and effective patient care
Pioneering an Approach to Woven Care Intelligence
Aidoc set the standard for how AI should be scaled in healthcare with the aiOS™, the first woven care intelligence platform for enterprise AI adoption. The aiOS™ helps health systems reap full benefits of transformative AI technology.
Woven care intelligence impact
decrease
7 hr.
in time from imaging to thrombectomy with AI at Cedars Sinai Medical Center1
average
33%
readmission reduction rate at 13 sites using Woven Care Intelligence2
day reduction
2.3
inpatient length of stay for intracranial hemorrhage patients at Yale New Haven Health3
ROI
451%
over a five-year period driven by improved patient care, increased appropriate interventions and improved productivity4
Talk with a woven care intelligence expert
- Luh, J. Y., Thompson, R. C., & Lin, S. H. (2019). Clinical Documentation and Patient Care Using Artificial Intelligence in Radiation Oncology. Journal of the American College of Radiology. https://doi.org/10.1016/j.jacr.2019.05.044
- Davis, M. J., Rao, B. M., Cedeño, P. A., Saha, A., & Zohrabian, V. M. (2020). Machine Learning and Improved Quality Metrics in Acute Intracranial Hemorrhage by Noncontrast Computed Tomography. Current Problems in Diagnostic Radiology, 51(4), 556–561. https://doi.org/10.1067/j.cpradiol.2020.10.00
- Aidoc. (2023). A Medicare Claims-Based Analysis Of The Impact Of AI On Readmission Rates. [White paper]
- Bharadwaj P, Nicola L, Breau-Brunel M, Sensini F, Tanova-Yotova N, Atanasov P, Lobig F, Blankenburg M. Unlocking the Value: Quantifying the ROI of Hospital AI. J Am Coll Radiol. 2024 Mar 16:S1546-1440(24)00292-8. doi: 10.1016/j.jacr.2024.02.034. Epub ahead of print. PMID: 38499053
