Artificial Intelligence (AI) is revolutionizing the way healthcare professionals diagnose and treat certain diseases. Moreover, it's transforming hospital operations by optimizing resource allocation, streamlining workflows, and improving patient care. For instance, AI-powered systems can use computer vision to manage medication stocks, document surgical steps in emergency rooms, and track hand hygiene practices of healthcare staff. With these applications, it's no wonder that AI in healthcare is expected to grow at a breakneck speed (43.2% annually from 2024 to 2032).

Eye-Catching Insights: AI in Healthcare Case Studies

AI has been successfully implemented in various healthcare settings, offering valuable insights into its capabilities. From diagnosing eye diseases to treating cancer, these real-world case studies provide a comprehensive overview of AI's applications in healthcare.

Moorfields Eye Hospital - A Beacon for AI Adoption

Moorfields is the world's oldest eye hospital, where professionals had to analyze over 5,000 optical coherence tomography (OCT) scans per week to spot and diagnose severe eye conditions like diabetic retinopathy or age-related macular degeneration (AMD). However, manual analytics took a long time, affecting early detection and diagnostics.

To overcome this challenge, Moorfields collaborated with DeepMind to develop an AI tool that can identify more than 50 eye diseases as accurately as top eye professionals. The software uses deep learning algorithms to detect anatomical elements of an eye and create a 3D image showing the thickness of retinal tissue through near-infrared light.

The AI-powered software offers clinical advice based on different signs of eye conditions in scans, with recommendations considered 94% accurate by top eye professionals. Moreover, it explains how it arrived at its decisions, ensuring doctors and nurses trust and use its recommendations more carefully.

HCA Healthcare - Unlocking Cancer Detection

HCA Healthcare is one of the US's largest healthcare systems, managing a vast network of hospitals, surgery centers, and other facilities across the United States and the United Kingdom. With numerous points of entry, HCA Healthcare must manually sift through pathology reports, physician schedules, and referrals to detect newly diagnosed cancer patients.

Azra AI, a SaaS clinical intelligence platform, was chosen as a comprehensive solution to this problem. Azra AI uses AI technology to automate oncology workflows, offering several benefits:

  • Early Cancer Detection: Azra AI analyzes pathology reports in real-time to spot possible cancer patients.
  • Surface Incidental Findings: Azra AI detects incidental findings (e.g., undiagnosed cancers) in radiology reports.
  • Cancer Registry Automation: The software extracts key information from medical records and automatically fills in over 50 certain fields, saving time and minimizing errors due to human entry.

As a result, HCA Healthcare reduced its time from diagnosis to the first treatment by 6 days and saved over 11,000 hours for manually reviewing and reading pathology reports. Azra AI also allowed HCA's care team to spend more time navigating and coordinating patient care (65%). For this reason, HCA Healthcare added over 10,000 new oncology patients within 14 months.

Duke Health - Streamlining Hospital Operations

Duke Health is a world-class academic healthcare organization affiliated with Duke University. It includes a large network of hospitals, research centers, and educational institutions like Duke University Hospital or Duke Clinical Research Institute.

Since 2019, the facility has used GE Healthcare's Command Center Software to streamline its operations and improve hospital-wide visibility. This AI platform helps track patient flow, manage capacity (e.g., bed availability or staffing levels), and predict future patient demands. This gives their care teams more time to focus on supporting and caring for patients.

With AI-powered solutions like these, healthcare professionals are empowered to make data-driven decisions, improving patient outcomes and streamlining hospital operations. As the adoption of AI in healthcare continues to grow, we can expect even more innovative applications that will revolutionize the industry.