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Aidoc’s AI Solution for Pulmonary Embolism Clinically Proven to Reduce Hospital Stay Duration and Improves Patient Access to Treatment

University of Texas Medical Branch, Jamaica Hospital and University of Chicago unveiled new impact data during the Pulmonary Embolism Symposium illustrating the importance of artificial intelligence in PE care

Groundbreaking research in the advancement of AI-driven pulmonary embolism (PE) care was unveiled yesterday evening during the 9th Annual Pulmonary Embolism Symposium. Research from three leading institutions utilizing Aidoc’s PE AI solution demonstrated immense clinical value in reducing mean hospital length of stay, improving patient access, and correctly alerting care teams of suspected PEs with potential for advanced interventions.

The three studies highlighted the care advantages of utilizing Aidoc in the management of acute pulmonary embolisms, including numerous patient outcome benefits. Key findings from the studies presented include:

  • 37% hospital length of stay reduction with AI triggered PERT activation and initiation of advanced therapies
  • 68% increased access of catheter-directed interventional therapy for intermediate-high to high acuity PE patients
  • A highly sensitive (95%) early alerting system that successfully identified critical PE patients

“Proving the robustness of any AI solution hinges on the application of scientific rigor and the scrutiny of peer review. Collaborating with these esteemed institutions to evaluate Aidoc’s PE AI Solutions is critical to increasing awareness of the multi-faceted benefits AI can provide to patients, providers and health systems,” shared Jerome Avondo, VP of Clinical Affairs and Reimbursement, Aidoc. “A difficult to manage, high acuity patient population, such as PE, presents novel opportunities for assessing the impact of artificial intelligence and understanding the overall impact on outcomes.”

These studies illustrate the ongoing evolution of Aidoc’s AI-powered PE solution from an algorithm to enterprise-wide platform used by Pulmonary Embolism Response Teams (PERTs) across entire health systems. Aidoc’s always on AI runs in the background examining both dedicated CT exams and non-dedicated CT exams for both expected and unexpected PE, and brings suspected findings forward to care teams, faster.

For PE management and care, Aidoc’s solution serves as an end-to-end workflow used by multidisciplinary PERTs and diagnostic radiologists to manage acute PE. The solution automates the notification and suggests prioritization of CT imaging to aid radiologists in the triage and coordination of the disease’s treatment.

PE cases are directed to a mobile workflow, where PERTs can view imaging, access the electronic medical record (EMR) data, and communicate to expedite treatment decisions and improve patient care. PERTs can combine their expertise with the operational efficiency of artificial intelligence to address acute PE directly.

University of Texas Medical Branch Reduces Length of Stay

The University of Texas Medical Branch (UTMB), a large academic health system, presented research showing how Aidoc’s proprietary AI platform, the aiOS™, helped operationalize PE workflows and communications. UTMB assessed the clinical and patient outcomes following implementation of Aidoc’s AI-powered PERT solution over a one-year period.

Each AI finding had a chart review either retrospectively for PERT consultation eligibility (pre-AI) or prospectively to determine if a PERT consultation had occurred (post-AI). The mean ICU length of stay decreased by 33.5% (pre-AI:2.30 days, post-AI:1.53 days), while the mean hospital length of stay decreased by 36.7% (pre-AI: 6.70 days, post-AI: 4.24 days). These findings highlight the ability to enhance patient management and outcomes in the PE patient population.

Jamaica Hospital Medical Center Increases PE Interventions with Aidoc

Even in settings where a PERT is available, a substantial percentage of pulmonary embolism patients in the traditional workflow are treated without the involvement of the PERT. Medical researchers at Jamaica Hospital Medical Center examined the change in the volume of PE patients referred by the PERT for catheter-directed therapies, following the implementation of Aidoc in the PERT workflow. After introduction, the annual volume of patients referred for interventional therapies rose by 68% compared to the period before the implementation of Aidoc PE AI.

University of Chicago Medicine Utilizes Aidoc AI to Prioritize and Triage PE Cases

The University of Chicago Department of Medicine published the final abstract involving Aidoc’s PE AI, assessing the retrospective predictive power of the AI to identify patients that will require escalated care. Aidoc PE AI achieved a sensitivity of 95% in identifying patients that ultimately required advanced therapy in the pre-AI standard of care PERT.

Interested in learning about how Aidoc’s AI Solutions have impacted clinical outcomes across other clinical specialties of medicine? Visit Aidoc.com/solutions to see the impact that can be made for patients.\

About Aidoc

Aidoc is a pioneering force in clinical AI. We focus on aiding and empowering healthcare teams to optimize patient treatment, which results in improved economic value and clinical outcomes. Our clinically proven AI solutions eliminate silos, increase efficiencies and improve outcomes by delivering critical information when and where care teams need it leading to immediate collective action. Built on Aidoc’s proprietary aiOS™, we analyze and aggregate medical data to enable care teams to operationalize the unexpected and work seamlessly with a continued focus on the patient. Used in more than 1,200 medical centers worldwide, Aidoc has the most FDA clearances (13) in clinical AI and its AI-based solutions cover 75 percent of patient populations, enabling physicians to make informed decisions based on real-time data. Aidoc AI is always on, running in the background to change the foreground. Visit Aidoc.com to see how we are connecting all points of care with always on AI.

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