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DISCOVER THE TRANSFORMATIONAL POWER OF HEALTHCARE AI

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All Healthcare AI is Not Created Equal

The adoption of artificial intelligence has more than doubled in the past five years, but one industry continues to lag – healthcare.1

From lingering misconceptions around return on investment to concerns about organizational capacity and readiness, these doubts are paralyzing progress at a time when facilities face ongoing and unprecedented challenges.

But these fallacies stop with us.

Here you’ll find the information and resources needed for developing an AI strategy at your facility. It’s time to change the conversation from what AI could do to what it is doing every day to optimize operational efficiency for for thousands of health systems around the world.

See Why Healthcare Needs AI Now
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How AI is Bringing Value to Healthcare’s Complex Challenges

A common myth regarding healthcare AI technology is that its financial benefits cannot be proven because there is no payor reimbursement. This is false.

Explore how AI is bringing facilities value

We have helped our customers leverage AI to unlock operational value:

  • Enhanced disease detection
  • Increased departmental throughput
  • Improved clinician efficiency through automation
  • Quality assurance that reduces liability
  • Data-driven decision making

Benefitting health systems, clinicians and patients in numerous ways

Effective AI = Connected System of Intelligence

Healthcare AI strategies have primarily focused on a single department or use case, making it difficult to realize enterprise-wide value. A connected system of intelligence touches everything and can help:

  • Manage data overload and healthcare staffing shortages  
  • Address diagnostic errors that lead to suboptimal care
  • Optimize clinical workflows to reduce costs and increase efficiency

The right AI and enterprise system can generate revenue by reducing patient leakage, identifying incidental findings, automating patient management, scheduling follow-up care and managing end-to-end care coordination. All of these lead to higher and appropriate use of DRG procedures.

To be effective, your AI solution should be:

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Single Platform

Integrates applications across specialties versus managing separate solutions that require different platform

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Scalable

Purpose-built to coordinate and deploy algorithms and applications across systems

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Seamless

Integrate within native workflow and IT infrastructure (PACS, EHR, scheduling, etc.)

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Secure

Compliant with data security and healthcare privacy regulations and standards

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Successful

Tailored to provide data-driven ROI

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Explore How AI is

Impacting Healthcare Today

There are over 500 market-cleared medical devices featuring AI or machine learning solutions for healthcare on the FDA website. To help facilities sort through the various definitions and capabilities of AI, the Asher Orion Group prepared this deep-dive into healthcare AI regulatory compliance and what the regulatory categories mean.

Read More

Novant Health, a not-for-profit integrated network of 15 hospitals in the southern United States, has been leveraging various integrated healthcare technologies — including Aidoc’s AI — to help improve access to care and patient outcomes. Read about its tech journey in Healthcare Digital magazine.

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HAVE QUESTIONS? WE’RE HERE TO HELP

1.

https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review 

2.

Khosla A. (2022). Transforming Endovascular Care with AI-Triggered PE Response Teams [Webinar]. Aidoc. Available at aidoc.com.

3.

Wismueller et al. (2020) A Prospective Randomized Clinical Trial for Measuring Radiology Study Reporting Time on Artificial Intelligence-Based Detection of Intracranial Hemorrhage in Emergent Care Head CT. Proceedings Volume 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging; 113170M doi: 10.1117/12.2552400

4.

Petry M, Lansky C, Chodakiewitz Y, Maya M, Pressman B. Decreased Hospital Length of Stay for ICH and PE after Adoption of an Artificial Intelligence-Augmented Radiological Worklist Triage System. Radiol Res Pract. 2022;2022:2141839. Published 2022 Aug 18. doi:10.1155/2022/2141839

5.

Aidoc. (2023). A Medicare Claims-Based Analysis Of The Impact Of AI On Readmission Rates. [White paper]

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