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SearchLinda Li, CFA, Partner, Cleveland Clinic Ventures, discusses how Artificial Intelligence (AI), electroencephalography (EEG), and Virtual Reality (VR)/ Augmented Reality (AR) technologies are reshaping healthcare. Discover how AI optimizes clinical trials and workflows, the potential of EEG in Alzheimer's diagnosis, and the innovative applications of VR/AR in patient care.
Explore the intersection of technology and patient care with Linda Li, who highlights how AI, EEG, and VR/AR are not just trends but essential tools revolutionizing the way we approach healthcare. From improving clinical trial recruitment to enhancing patient experiences, discover how these advancements are paving the way for a more efficient and accessible healthcare system.
One of the most significant applications of AI is in clinical trial recruitment. The complexity of trials, with numerous diseases and specific inclusion/exclusion criteria, makes finding suitable candidates challenging. AI algorithms can rapidly analyze vast datasets to identify eligible patients, accelerating the recruitment process and enhancing the development of new therapies.
AI also optimizes hospital workflows, particularly in billing. By streamlining the process, AI ensures patients receive timely and clear information about payments, significantly reducing the delays often associated with billing inquiries. Additionally, AI improves patient eligibility assessments, enabling healthcare providers to process claims more efficiently.
Integrating AI in healthcare not only enhances patient care but also leads to significant cost reductions. By reducing the workload on staff and minimizing manual processing, AI saves hospitals time and money, allowing them to focus on improving care rather than administrative tasks.
Implementing AI in healthcare presents significant challenges and promising opportunities. While regulatory compliance and data security are concerns, the main hurdle is integrating AI into existing workflows. Many startups focus on point solutions for specific issues, but healthcare encompasses a more complex patient journey. At Cleveland Clinic, the goal is to help these startups develop technologies that fit seamlessly into patient care.
Implementation risks and feasibility are key considerations. Contrary to the belief that clinicians may resist AI, many at Cleveland Clinic are eager to adopt new technologies. The challenge lies in streamlining workflows to effectively incorporate AI. For example, if a physician must switch systems to use a point solution and then manually update electronic medical records (EMR), it creates inefficiencies. Automating this integration is essential for enhancing clinical care without increasing the burden on healthcare providers.
Navigating the clinical care landscape is a challenge for many patients, who often see their doctors only once or twice a year due to scheduling issues and the complexity of accessing care. While Cleveland Clinic employees may have better access, patients in remote areas face significant hurdles, often needing to travel 30 to 40 miles to see specialists. This situation is exacerbated by a nationwide shortage of doctors and nurses, making it hard for health systems to meet patient demand.
In underserved regions, many patients struggle to access timely care due to geographical and logistical barriers. Complicating matters, demanding work schedules often prevent patients from attending appointments during standard hours. This overflow of patients underscores the need for more care providers to serve both urban and rural populations effectively.
To optimize resources, healthcare providers must differentiate between high-acuity and low-acuity patients. By prioritizing those who need immediate attention, the system can ensure timely care for high-acuity patients. Integrating innovative solutions from startups into the healthcare ecosystem is essential for enhancing access and efficiency, ultimately leading to better patient outcomes.
EEG data is vital for precision treatment, especially when combined with AI. Unlike simpler ECG data, EEG captures complex brain activity through multiple channels, making it challenging to analyze without technology. AI enhances the interpretation of EEG signals, helping to identify abnormalities and improve diagnostics. For example, it has been used in epilepsy management to predict seizures, allowing patients to avoid dangerous situations.
At Cleveland Clinic, neurologists emphasize the importance of understanding EEG signals in context. Timely information is crucial, delaying diagnosis can lead to risks, while premature alerts may impose unnecessary restrictions on patients. With AI's advancements, EEG data could serve as a new biomarker for various diseases, aiding in early diagnosis and monitoring while improving patient outcomes.
EEG data offers a promising, non-invasive alternative for diagnosing Alzheimer's disease, of which a definitive diagnosis can only be obtained upon autopsy of the brain at death. Traditional methods, like analyzing cerebrospinal fluid, are invasive and impractical for screening.
In contrast, EEG allows patients to wear a helmet or some innovative EEG monitoring device for about ten minutes, enabling regular monitoring without discomfort. This approach could potentially facilitate earlier diagnosis and treatment, similar to how continuous glucose monitors work for diabetes.
By leveraging EEG's rich data, we can enhance our understanding of Alzheimer's and improve patient care and outcomes.
Virtual reality (VR) and augmented reality (AR) enhance healthcare through improved workflows and innovative therapies. For instance, MediView, a Cleveland Clinic portfolio company, uses AR for surgical navigation, enabling surgeons to visualize procedures more effectively than with traditional images. This technology can enhance surgical skills across various settings.
In therapy, VR helps individuals on the autism spectrum by gradually exposing them to social situations, such as family gatherings, to reduce anxiety and improve coping skills. Additionally, VR aids rehabilitation for patients with conditions like Parkinson's disease by gamifying exercises in a safe virtual environment, encouraging movement without real-world fears.
VR and AR technology can significantly enhance patient care, but a supportive policy environment is essential. It’s crucial for startups to validate their solutions within regulatory frameworks while integrating effectively with health systems.
Cleveland Clinic exemplifies this by fostering collaborations with external partners to drive innovation in VR and AR. While implementation challenges exist, ongoing improvements and a commitment to embrace new technologies suggest a promising future for these advancements in healthcare.
I believe that the future of healthcare technology will evolve in two stages.
The initial focus will be on integrating AI, VR, and AR solutions within existing hospital settings. This phase aims to validate these technologies as effective components of patient care.
Once validated, care will become more decentralized, empowering patients to choose how they receive treatment—whether online, at home, or in-person. With intelligent technology, patients can customize their care according to their needs.
Emerging trends show patients increasingly opting for telehealth services instead of traditional hospital visits, though periodic check-ups may still be necessary. In this future landscape, clinicians will serve as knowledgeable navigators, guiding patients through complex care options while prioritizing high-acuity needs over low-acuity cases.
