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Liz Kah, MD

Aidoc and Mount Sinai: Revolutionizing IVC Filter Management with AI

Care Coordination, Inferior Vena Cava Filter, Patient Management, Venous Thrombeoembolism, Workflow
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Mount Sinai Health System is at the forefront of transforming inferior vena cava (IVC) filter management. Through the strategic implementation of Aidoc’s AI-driven solutions, Mount Sinai has developed innovative workflows that address critical care gaps, enhance patient safety and demonstrate significant financial advantages in IVC filter retrieval programs. 

Automated IVC Filter Detection: Addressing a Critical Care Gap

Approximately 65,000 IVC filters are placed annually in the United States, yet only about 35% are retrieved1. The main reason? Many patients who receive IVC filters are lost to clinical follow-up leaving them exposed to potential life-altering complications, such as caval thrombosis. 

Mount Sinai’s collaboration with Aidoc directly tackles this challenge through the implementation of an AI-enhanced workflow for IVC filter management. Aidoc’s Patient Management dashboard, based on natural language processing (NLP), analyzes all inpatient, Emergency Department (ED) and outpatient radiology reports from a single tertiary care center. This AI system scans confirmed radiology reports to identify mentions of IVC filters — whether existing or newly placed — and adds the patients to a workflow to ensure they receive proper long-term monitoring and management, including filter removal. This tool has demonstrated extremely high sensitivity2 for flagging incidental IVC filters and ensures patients aren’t lost to clinical follow-up.

How the Streamlined Workflow for Patient Care Works

Once patients with IVC filters are routed to the Patient Management dashboard, the interventional radiology office can contact them. Sometimes, the patients aren’t even aware they had an IVC filter placed during a prior surgery, so this notification creates an opportunity for them to schedule follow-up appointments and discuss potential retrieval. 

During these follow-up appointments, the interventional radiology physician investigates the initial indication for placement, appropriately manages anticoagulation therapy and obtains any relevant imaging (e.g., lower extremity duplex ultrasound, CT venography). Following appropriate clinical workup, long-term management is discussed and, if indicated, retrieval is scheduled on an outpatient basis. 

Financial Benefits for Health Systems

Aidoc’s ability to automatically flag IVC filters and route relevant patients into a patient engagement workflow not only promotes patient safety by minimizing risks associated with long-term filter placement but also offers substantial financial gains for the healthcare system. 

A sensitivity analysis performed by Mount Sinai revealed a growing systemic value as more comprehensive care stages are implemented per patient. With reimbursement incentives highlighting both the specific costs of each retrieval step and the aggregated financial benefits of a typical IVC filter retrieval journey ($2,597.41 per patient), this model presents a significant cost-effectiveness argument for other healthcare providers.

For example, the potential total healthcare system value can be estimated as follows:

  • For 50 patients: $20,006 (initial evaluation) to $268,729 (office visit + radiologic studies + retrieval + follow-up).

Promoting a Proactive Role for Interventional Radiology

Mount Sinai’s preliminary experience with this workflow suggests that enhanced filter awareness allows for efficient engagement with patients. Given interventional radiologist’s crucial position at the intersection of imaging and venous thromboembolism (VTE), the implementation of Aidoc’s Patient Management dashboard empowers the interventional radiology specialty to take a more proactive and centralized role in the long-term management of patients with indwelling IVC filters.

The collaboration between Aidoc and Mount Sinai exemplifies how advanced AI technologies can be seamlessly integrated into clinical practice to enhance patient safety, facilitate care coordination and improve clinical outcomes while achieving financial benefits in complex areas of patient management.

Citations

  1. Quencer KB, Smith TA, Deipolyi A, Mojibian H, Ayyagari R, Latich I, Ali R. Procedural complications of inferior vena cava filter retrieval, an illustrated review. CVIR Endovascular. 2020;3(1):23.
  2. Aidoc data on file.

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Liz Kah, MD
Liz Kah, MD, is the Associate Vice President of Innovation and Strategic Partnerships at Aidoc. She's a physician by training, who has 20+ years of experience in healthcare strategy and innovation, including clinical AI. Dr. Kah’s diverse background spans management consulting at Boston Consulting Group, strategic and operational leadership at Kaiser Permanente and roles in both startups and nationally recognized healthcare and pharma organizations. Her experience includes product development, concept creation, marketing and the delivery of innovative solutions and services. Starting in medical school, she knew that computer-generated algorithms, clinical decision support, automation and AI could have an enormous impact on improving treatment quality, improving provider efficiency and addressing issues of health equity. Now, Dr. Kah works at the leading edge of clinical AI, optimizing patient outcomes and eliminating health inequity – which results in improved economic value and clinical outcomes – and breaking down silos, enabling enhanced communication and improved provider efficiencies.
Liz Kah, MD
Associate Vice President, Innovation and Strategic Partnerships

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