This is digital health today, in a nutshell.
Tuesday, November 5, 2024
15 Health AI Liars Exposed—Including One That Just Raised $70M at a $0.5B Valuation (Part 2 of 2)
The Death of Teladoc and the rise of Doximity, Privia, Curai, and - the drum roll - your neighborhood EHR
Teladoc
As I predicted in my recent "Telehealth Masquerade" review, the telehealth industry, as we know it, is collapsing. It's a natural selection process, where companies with zero innovation and poor management, such as Teladoc and Amwell, are yielding way to those who already have telehealth as part of their integrated solution: Doximity, Privia, Curai, and - the drum roll - your neighborhood EHR.
Teladoc has just reported earnings. It's bad. The CEO blamed "the macro-economic environment". Really? At a rare time when we have the coveted three "3s": 3.3% real GDP growth, 3.1% inflation rate, 3.7% unemployment rate. Teladoc's management has no one to blame but themselves.
In the latest edition of "AI Health Uncut", I'm taking a deep dive into the disappearance of the telehealth industry as we know it, as well as Teladoc disastrous decision to acquire Livongo via the leveraged buyout (LBO), a move spurred by the venture capital industry with 7wireVentures at the helm.
It is no surprise this has occured. The decreased necessity for social distancing with the conclusion of the covid19 pandemic as well as reduced and unlimited funding for conferencing has inevitably created this situation.Saturday, October 26, 2024
Exploring the New LinkedIn Group: AI in Medicine Innovators
# Exploring the New LinkedIn Group: AI in Medicine Innovators
In the ever-evolving landscape of digital health, artificial intelligence (AI) is reshaping the way we approach patient care, diagnostics, and medical research. Recently, a new LinkedIn group titled **AI in Medicine Innovators** has launched, providing a platform for professionals in the healthcare and technology sectors to connect, collaborate, and share insights on the transformative potential of AI in medicine.
What to Expect from the Group
The **AI in Medicine Innovators** group is designed for a diverse range of members, including healthcare professionals, data scientists, researchers, and entrepreneurs. Here’s what you can look forward to:
### 1. **Networking Opportunities**
One of the primary benefits of joining this group is the opportunity to network with like-minded individuals. Whether you're a seasoned professional or a newcomer to the field, connecting with peers can lead to potential collaborations, mentorship opportunities, and even job prospects.
### 2. **Knowledge Sharing**
Members are encouraged to share articles, research findings, and case studies related to AI applications in healthcare. This knowledge-sharing environment can help members stay updated on the latest trends, breakthroughs, and best practices in the field.
### 3. **Discussions on Ethical Considerations**
As AI continues to integrate into healthcare, ethical considerations are paramount. The group provides a space for robust discussions on topics such as data privacy, algorithmic bias, and the implications of AI in clinical decision-making. Engaging with others on these issues can help shape responsible AI development.
### 4. **Showcasing Innovations**
Innovators and startups are invited to showcase their AI-driven solutions and projects. This not only helps in gaining visibility but also fosters a culture of innovation and collaboration. Members can provide feedback, share experiences, and even explore partnership opportunities.
### 5. **Webinars and Events**
The group plans to host webinars featuring industry leaders and experts discussing various aspects of AI in medicine. These events will provide valuable insights and foster a deeper understanding of the challenges and opportunities in the field.
## Why Join the Group?
Joining the **AI in Medicine Innovators** group is an excellent opportunity for anyone interested in the intersection of technology and healthcare. Here are a few reasons to consider:
- **Stay Informed**: The digital health space is rapidly evolving, and being part of this group ensures you’re always up-to-date with the latest developments.
- **Collaborate**: Find potential collaborators for research projects, startups, or initiatives that leverage AI in healthcare.
- **Engage in Meaningful Conversations**: Participate in discussions that matter, from technical challenges to ethical dilemmas.
The **AI in Medicine Innovators** LinkedIn group is more than just a networking platform; it's a community dedicated to pushing the boundaries of what's possible in healthcare through AI. By joining, you'll not only enhance your professional network but also contribute to the ongoing dialogue about the future of medicine.
Whether you’re a healthcare provider, a tech enthusiast, or an AI researcher, this group offers a valuable space to learn, share, and innovate. Don’t miss out on the chance to be part of this exciting journey in the digital health space!
**Join today and start connecting with the future of medicine!**
Friday, September 13, 2024
OpenAI and ChatGPT,DougallMD, Doximity and most Medical applications will use AI Breaking the rules of medical technology: A conversation with Dr. Eric Topol | LinkedIn
History has proven that society moves forward when innovators question and defy the accepted financial, cultural, or technological norms. This is especially true in medicine.
1. Personalized Preventive Care
The traditional approach to preventive care uses broad, universal categories like age and sex to determine what medical screenings and preventive measures people should receive. While this approach works on a large—and mostly probabilistic—scale, it overlooks individual risk factors, such as genetic profiles and specific biomarkers. Humans can’t possibly retain and recall all the data that affects each individual patient, but they will be able to apply the totality of information using GenAI. These tools can almost instantaneously analyze vast amounts of data to identify those individuals at highest risk for serious conditions like cancer and heart disease and recommend targeted approaches to improve patient outcomes.
2. Reducing Diagnostic Errors
Traditionally, doctors rely on memory and experience to diagnose new symptoms, drawing from their medical training and past cases. However, this approach risks overlooking rare or complex conditions, and it is vulnerable to cognitive errors like confirmation and proximity bias. GenAI offers a powerful solution by integrating vast amounts of medical data—combining patient history, symptoms and real-time imaging—and correlating it with comprehensive medical literature, including obscure case reports. In the future, combining a dedicated clinician with a generative AI application will produce more accurate diagnoses than either alone.
3. Enhancing Doctor-Patient Interactions
In today’s healthcare, doctors often spend more time inputting data into electronic health records (EHRs) than engaging with patients, leading to impersonal and transactional experiences. GenAI is changing this dynamic by automatically transcribing and organizing doctor-patient conversations into accurate, high-quality EHR entries. This technology not only frees up to two hours a day for clinicians, but also improves the quality of care and helps reduce burnout.
A Fourth Opportunity: Accelerating Medical Research
In addition to Dr. Topol’s three points, I’d add a fourth: the ability of GenAI to accelerate research. In medical science today, it can take years to gather enough data to drive meaningful advances. GenAI can dramatically shorten this timeline by analyzing vast amounts of patient data quickly, leading to faster breakthroughs and more timely application of new treatments.
Clinical research conventionally starts with a question, followed by lengthy data collection and analysis. This approach is time-consuming and limited by the volume of data that researchers can analyze and manage. GenAI alters the calculus by enabling doctors to sift through enormous datasets. Today, U.S. hospitals produce up to 50 petabytes of data each year, 97% of which currently goes unused. By mining this data, GenAI will be able to uncover patterns and insights that would take years to find with traditional methods. One of the first practical applications will be identifying hospitalized patients who are likely to deteriorate over the next 24 hours, allowing clinicians to intervene earlier and potentially save lives.
Challenges and Risks
Of course, breaking the rules of medicine comes with challenges. Security is a major concern, especially when clinicians use generative AI for EHR data entry. However, the reality is that this danger already exists in the current EHRs, which can easily be hacked, but fail (alone) to offer the advantages that GenAI solutions will provide.
The evolution of medical technology always includes trade-offs. The advent of CT scans, MRIs, and laparoscopic tools, for example, led doctors to lose their skill in physical exams, but the lives saved by these innovations are undeniable. No clinician would go back to the past.
Within the next five years, Dr. Topol predicts that GenAI will become a standard tool for creating electronic health records (EHRs). Other applications will follow soon after. I’m confident that the old rule “the doctor knows best” will be replaced by a new reality—one in which the best outcomes come from a collaboration between a dedicated clinician, an empowered patient, and GenAI. Together, they will achieve more than any of the three could accomplish alone.
The Future of Medicine is boundless.
You will be there.
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