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5 Reasons Your Clinical AI Platform Needs Intelligent Orchestration

Not all AI platforms are created equal. Many rely on static workflows or incomplete data, leaving gaps in accuracy and efficiency. To truly deliver on AI’s potential, healthcare systems need intelligent orchestration – a capability that dynamically, and at scale, can apply the right algorithms to the right scans and the right anatomy in real time.

Here are five reasons why intelligent orchestration is a key differentiator your enterprise clinical AI platform needs for long-term success.

1. Enhanced Accuracy That Goes Beyond the Protocol

Other AI solutions are tethered to protocol, effectively leaving health systems using technology that wears blinders, only finding what they’re already looking for. They often rely solely on DICOM metadata to guide algorithm selection, but metadata alone can be incomplete or outdated. 

Aidoc’s aiOS™ intelligent orchestration breaks free from protocol and uses much more than DICOM tag analysis to enable the AI to choose the optimal image slice, ensuring the right algorithms are applied to the most relevant anatomy at the right time.

  • Free from Protocol Limitations: Intelligent orchestration breaks free from protocol, using image-based AI to identify all anatomy present on a scan to deploy all relevant algorithms, despite ordered protocol. For example, other vendors run a stroke algorithm on a stroke patient, searching for what’s already there. Aidoc’s aiOS™ performs the most comprehensive AI analysis on the market on all anatomy present in the scan, potentially identifying critical findings, like an incidental pulmonary embolism (iPE) at the top of the lungs on that stroke patient, even if they weren’t part of the original scan protocol. 
  • Precision in Image Selection: By evaluating pixel-level details, the aiOS™ can distinguish between multiple contrast series, choosing the one with the highest quality for analysis.
  • Beyond Metadata Limitations: Intelligent orchestration includes image-based AI, which overcomes the challenges of inaccurate or missing metadata, delivering reliable results across varied imaging protocols.

This multi-validation approach ensures unparalleled accuracy, reducing the risk of missed pathologies caused by incomplete or misinterpreted data.

2. Efficient Data Processing and Optimized Cloud Usage

One of the hidden costs of AI is cloud dependency, which can slow down processing and increase operational expenses. Aidoc mitigates this with on-premises orchestration that minimizes the need for cloud data transmission.

  • On-Premises Computation: Orchestration logic runs locally, selecting only the most relevant series for AI analysis, which reduces bandwidth usage.
  • Faster, Cost-Effective Analysis: By processing data locally and selecting the correct segments of the study appropriate for analysis, Aidoc accelerates response times and reduces cloud storage costs.

This approach not only optimizes resources but also ensures faster results, enabling care teams to make timely and informed decisions.

3. Adaptability to Protocol Changes

Healthcare is a dynamic field, and AI performance changes over time due to data drift. Data drift occurs due to factors like evolving protocols (i.e. different naming conventions for the same types of imaging orders), which can vary up to 20% month-over-month1

Platforms that rely solely on static DICOM metadata and manual tracking of data drift risk serious decreases in AI performance. Aidoc’s automated drift monitoring and remediation  automatically monitors and alerts for changes in AI performance – such as prevalence, specificity, sensitivity, PPV, number of optimal series analyzed and actual amount of AI positives versus expected – to investigate and resolve data drift.  

  • Reduced Maintenance Needs: Automatically detects changes in protocols and dynamically adjusts, minimizing the need for manual updates.
  • Accuracy Over Time: Prevents data drift, ensuring algorithmic performance remains accurate over time.

This is one way the aiOS™ provides a layer of adaptability that future-proofs the AI system in a constantly changing clinical environment.

4. Incidental Findings: Capturing More Helps Save Lives

Aidoc’s intelligent orchestration isn’t limited by what a scan was ordered to find, rather it analyzes all visible anatomy and deploys all relevant algorithms, surfacing incidental findings that might otherwise go unnoticed. This platform-enabled, multi-algorithm deployment approach enhances clinical awareness and helps speed up time-to-intervention.

As Alexander Misono, MD, Chief of Interventional Radiology at Hoag Hospital Irvine, said: “There’s always a patient on the other end. If I get a notification earlier — or potentially far earlier than we would have traditionally — I can start conversations earlier, which may shorten the time to a variety of interventions.” 

In practice this could mean:

  • A PE scan can also detect rib fractures, aortic dissections, coronary calcification and pulmonary nodules.
  • In abdominal CT scans, partial anatomy of the chest included in the field of view are analyzed for pathologies like lung nodules or aortic abnormalities.

This expanded scope helps improve patient care by uncovering additional findings, enabling earlier interventions and better outcomes.

5. Streamlined Reading Times and Improved Patient Outcomes

Aidoc’s intelligent orchestration capabilities are designed to enhance the speed and impact of care delivery, helping to ensure better outcomes for patients and providers:

  • Improved Workflow Efficiency: By optimizing AI integration through Aidoc’s PACS-agnostic Desktop Application, radiologists can more quickly triage critical findings, leading to faster care activation and streamlined clinical workflows. In a multi-site prospective study, overall workflow efficiency improvements of 8% to 15% were observed across more than 405,000 reports from eight Aidoc sites and four AI algorithms.2 
  • Accelerated Time-to-Intervention: With AI-driven prioritization that sorts cases based on urgency rather than first in, first out, clinicians can act faster on urgent cases, improving overall treatment outcomes. Cedars-Sinai found a 40% mean decrease in time from CT angiography to mechanical thrombectomy (17.1 vs. 10.1 hours) after Aidoc implementation.3 
  • Maximized AI Utilization: Aidoc’s aiOS™ ensures the highest possible yield by running a wide range of relevant algorithms on all applicable scans. This enables more patients to benefit from AI insights while connecting radiologists with other physicians. Jamaica Hospital Medical Center utilized Aidoc and based on the findings and risk stratification, routed 60% more patients for appropriate advanced interventions4,5

This approach ensures that more patients receive timely interventions, and clinicians can work more effectively, focusing their expertise where it matters most.

Real-World Examples of Intelligent Orchestration

Trauma Case Analysis:
In a full-body trauma case, Aidoc simultaneously applies multiple algorithms across different body regions, detecting fractures, hemorrhages and other critical findings. This centralized orchestration results in faster triage while ensuring all relevant conditions are addressed promptly.

Why Aidoc Leads in Orchestration

Aidoc’s intelligent orchestration engine is a proven solution with 170+ studies and abstracts demonstrating clinical, operational and financial benefits. Here’s what sets it apart:

  1. The Most Comprehensive AI Analysis: Breaking free from protocol, Aidoc’s aiOS™ doesn’t just look for what it expects – it intelligently analyzes all anatomy present, running relevant algorithms to flag unexpected pathologies and prioritize the most urgent cases.
  2. Image-Based Validation: Goes beyond DICOM metadata to directly analyze pixel data, ensuring optimal image selection for more accurate results, and detecting even partial anatomy present on a scan.
  3. Drift Mitigation: Continuously and automatically monitors and adapts to evolving protocols, maintaining high accuracy over time.
  4. The Most Widely Adopted AI Platform: Implemented at more than 1,500 health systems, analyzing 3,00,000 a month around the world.

Orchestrating a Better Future for Healthcare

By combining innovative technology with real-world adaptability, Aidoc’s aiOS™ platform ensures that more patients, radiologists and healthcare systems reap the benefits of AI-enabled workflows.

In a world where every second counts, Aidoc’s orchestration ensures AI delivers on its promise: improved outcomes for patients and clinicians alike. Interested in learning more? 

Interested in learning more?

Request a personalized demo with an Aidoc AI expert. 

References

  1. Internal Aidoc Analysis.
  2. Aidoc. (2023). A multi-site prospective study; the impact of AI on read time efficiency. [Whitepaper].
  3. Gupta, K. (2022) Mechanical Thrombectomy, Artificial Intelligence and the Activation of a Pulmonary Embolism Response Team. Presented at PERT Consortium. https://pertconsortium.org/wp-content/uploads/2022/09/Use-of-Artificial-Intelligence-in-the-Activationof-a-Pulmonary-Embolism-Response-Team.pdf
  4. B. Rivera-Lebron, M. McDaniel, K. Ahrar et al. PERT Consortium. Diagnosis, Treatment and Follow Up of Acute Pulmonary Embolism: Consensus Practice from the PERT Consortium. Clin Appl Thromb Hemost. 2019 Jan-Dec;25:1076029619853037. doi:10.1177/1076029619853037. PMID: 31185730
  5. E. Langius-Wiffen, P.A. de Jong, F. Hoesein et. Al. Retrospective batch analysis to evaluate the diagnostic accuracy of a clinically deployed AI algorithm for the detection of acute pulmonary embolism on CTPA. Insights Imaging. 2023 Jun 6;14(1):102. doi: 10.1186/s13244-023-01454-1.

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Alex Kane

Alex Kane is a business development and product marketing leader with expertise in cloud computing and enterprise SaaS for healthcare. As the head of product marketing for Aidoc’s clinical AI platform, she drives go-to-market strategies and messaging. Previously, Kane led healthcare business development at Amazon Web Services, helping health systems adopt cloud solutions. Her background includes senior marketing roles at AVIA, Apervita and Uptake, where she specialized in product marketing, strategic messaging and content development. She hold a master’s degree in healthcare communication and a bachelor’s degree in journalism from Northwestern University. Kane is also AWS Cloud Practitioner Certified.

Alex Kane
Director, Platform Marketing