“Culture crushes innovation.”  Here, we must not point the finger of blame for the dysfunctional health ecosystem at physicians, nurses and allied health professionals on the hospital floor.  Healers want to heal as much as those who need their help seek answers and solutions. The shared problem is not how to utilize this “hot” evolving technology but are we prepared to make the investment in time and training!  Time to input (usable) data into EMRs and learning technologies that can sort and “scrape” through and highlight information to accelerate clinical decision-making. 

Using AI to Reject Patient Claims and Care

One part of the challenge is understanding how to cognitively maximize and explore vast amounts of information is another. The other is to come to agreement in how AI can and cannot be used ethically and responsibility. As we saw recently, a nascent AI system must not be used by major health insurance companies to deny patients coverage for medicines and procedures.

While the “system” is resistant to significant change and science has become politicized and misunderstood, we must rally to the dual-goal of saving lives and reducing costs.  Can information technologies and “intelligent health systems” do what people in power have not achieved?  Are we able to educate consumers about being partners in data security? Can information bring people – professionals and consumers – together and transform this country’s post-WWII build health system? Yes!

Cardiologist Eric Topol, MD, reflects on the tension between patient care and AI in a Time Magazine interview about his bestselling book Deep Medicine:

“AI will always need human backup. A machine could handle certain things autonomously–diagnosing a skin rash, for example. Doctors shouldn’t be dealing with things that machines will do better than them. But serious conditions, like getting a cancer diagnosis, are what doctors should be working on. I think once patients understand that there are things they don’t need doctors to do, they would love it–once they get used to it.”

Many health professionals (and patients) are understandably wary! In one Medscape interview a physician shared this experience:

“We’ve played around with it. It was very early on in AI and we noticed it gave us incorrect information with regards to clinical guidance,” said Monalisa Tailor, MD, an internal medicine physician at Norton Health Care in Louisville, Kentucky. “We decided not to pursue it further,” she said.

Don’t close the door on an evolving technology! Care professionals work within a system that hinges on economics – how the institution is paid and how it must cover costs.  What is to be done if the system cannot support the health professional’s efforts or make the best use of their training, abilities, energy and dedication?  What will happen as more and more health professionals ghost the provider system that they feel no longer addresses their emotional and economic needs? These are questions that must be addressed sooner than we think! AI is inescapable. It’s an evolutionary process that will improve – improve health professionals and care output – over time.

Perhaps the biggest question is whether we can wait to resolve all these questions while health costs soar and people risk dying from treatable illnesses.  We should already know that answer! If you’re living in the question, that’s great. One way to resolve your angst and uncertainty is to follow people – some pioneers and others pundits – who are also asking those questions, doing the necessary research and exploring sensible possibilities.

20 AI/ChatGPT Champions to Follow

It was a challenge to select only 20 influentials for this listing. There countless people writing, speaking and commenting about AI and ChatGPT. It’s a hot topic and “trendy.” This list is not about “trends” and it isn’t an exclusive roster of people. However, these people are key voices of influence at the frontlines of AI and ChatGPT and are boldly considering how the health sector will need to support and adapt to these technologies ethically. It is important to follow their social posts, speeches and writings. They are theorists, physicians and teachers. What they say and where they say it can inform your opinion and direction. Follow them and get smarter faster!

Acknowledgements

As always, thanks to my friend and Medika Life Founding Editor-in-Chief Dr. Robert Turner, and Cullen Burnell for their encouragement and suggestions, and to Carolyn Neugarten, Medika Life Editorial Assistant for her efforts in making this feature possible, and Tyler Mayers, whose expertise sharing content across social platforms makes important information widely accessible. Special appreciation to colleagues from numerous professional circles who shared their thoughts and contributed recommendations. Special acknowledgement to people who appeared on previous Medika Life Lists and continue on the path to improve the wellbeing of people and planet. These exemplary people are dedicated to improving people’s health and know their efforts will make a difference.

AI and ChatGPT are frightening to some and mysteries to others. Humanity must decide how to best deploy these evolving and “thinking” technologies. What to do next is a mindful choice in the hands of people, and must be for the sake of people.

Gil Bashe, Editor–in-Chief, Medika.Life

AI and ChatGPT Global Voices of Influence

Here is our Medika Life roster of 20 people to follow in alphabetical order; all-important voices – to track and learn from in the coming years We have included wherever available links to the social media platforms and bios.

Follow these Voices and Leaders of Influence – They are writing the future of how AI and ChatGPT will be essential to health care delivery.

Ran D. Balicer, MD

Dr. Ran D. Balicer, a public health physician, executive and researcher, serves as Chief Innovation Officer & Deputy-DG at Clalit – Israel’s largest health insurance organization, and is Founding Director of the Clalit Research Institute.

• LinkedIn
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Regina Barzilay, MD

Dr. Regina Barzilay is a School of Engineering Distinguished Professor for AI and Health in the Department of Electrical Engineering and Computer Science, and a member of the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology (MIT).

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Kirk Borne, PhD

Dr. Kirk Borne is a Data Scientist, providing thought leadership, global speaking, content creation, mentoring, training, and consulting activities in data science, machine learning, and AI across multiple disciplines.

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Atul Butte, MD, PhD

Atul Butte, MD, PhD is the Priscilla Chan and Mark Zuckerberg Distinguished Professor and inaugural Director of the Bakar Computational Health Sciences Institute (bchsi.ucsf.edu) at the University of California, San Francisco (UCSF). 

• LinkedIn
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Lex Fridman, PhD

Lex Fridman, PhD, is a Russian-American computer scientist, podcaster, and artificial intelligence researcher. He is a research scientist at the Massachusetts Institute of Technology (MIT), and hosts the popular Lex Fridman Podcast, a podcast and YouTube series.

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Mo Gawdat, MBA

Mohammad “Mo” Gawdat is an Egyptian entrepreneur and writer. He is the former chief business officer for Google X and author of the bestselling business books Solve for Happy and Scary Smart – The Future of Artificial Intelligence and How You Can Save Our World.

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John Halamka, MD, MS

John D. Halamka, M.D., M.S., president of the Mayo Clinic Platform, was trained in emergency medicine and medical informatics, Dr. Halamka has been developing and implementing healthcare information strategy and policy for more than 25 years.

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Eric Horvitz, MD

Microsoft’s Chief Scientific Officer and an early AI champion for health and medicine going back many years, Dr. Eric Horvitz is among the founders and funders of Stanford’s 100-year longitudinal study of the impact of AI on Society.

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Daniel Kraft, MD

Daniel Kraft, MD, is a Stanford and Harvard-trained physician-scientist, inventor, entrepreneur, and innovator and is serving as the Chair of the XPRIZE Pandemic & Health Alliance. With more than 25 years of experience in clinical practice, biomedical research and health innovation.

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Tom Lawry

A leading AI transformation advisor to health and medical leaders around the world. Lawry is the best-selling author of Hacking Healthcare – How AI and the Intelligent Health Revolution Will Reboot an Ailing System, former Microsoft National Director of AI and now the managing director of Second Century Tech LLC, and partner in Aspire Health Innovations.

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Fei-Fei Li, PhD

Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute. She served as the Director of Stanford’s AI Lab from 2013 to 2018.

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Berci Mesko, MD, PhD

Bertalan Meskó, PhD is known as “The Medical Futurist” and the Director of The Medical Futurist Institute analyzing how science fiction technologies can become a reality in medicine and healthcare. He holds a PhD in genomics and is an Amazon Top 100 author. 

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Mira Murati

Mira Murati is the Chief Technology Officer at OpenAI, and one of the most influential innovators in technology and AI. She oversees efforts to commercialize OpenAI products and improve them through human feedback. She serves on the leadership teams that developed the OpenAI ChatGPT and Dall-E systems.

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Andrew Ng, PhD

Dr. Andrew Ng is a globally recognized leader in AI. He is Founder of DeepLearning.AI, Founder & CEO of Landing AI, General Partner at AI Fund, Chairman and Co-Founder of Coursera and an Adjunct Professor at Stanford University’s Computer Science Department.

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John Nosta

John Nosta is a cutting-edge thinker in the world of technology, science, medicine and innovation. He is a globally recognized among the foremost voices constantly pushing the envelope on how AI and ChatGPT will transform health settings and work flow. Nosta is non-stop power thinker (and contrarian) and has more than 500 articles published on innovation topics.

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Tam C. Nguyen

Associate Professor Tam Nguyen has more than 20 years of working in clinical trials, health and medical research and research management sector including tertiary teaching hospitals, medical research institutes and universities across Australia. He is the co-editor of the recent book: AI in Medicine (Springer).

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Ziad Obermeyer, MD

Ziad Obermeyer, MD, is the Blue Cross of California Distinguished Associate Professor of Health Policy and Management. He is a physician and researcher who works at the intersection of machine learning and health.

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Brian Roemmele

Brian Roemmele is a scientist, researcher, analyst, connector, thinker and doer. Brian became an early adopter of AI and neural networks and pioneered Prompt Engineering technologies and techniques to understand and extract information from AI platforms.

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Mihaela van der Schaar, MD

Mihaela van der Schaar, MD, is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge and a Fellow at The Alan Turing Institute in London. In addition to leading the van der Schaar Lab, Mihaela is founder and director of the Cambridge Centre for AI in Medicine (CCAIM).

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 Eric Topol, MD

Eric Topol, MD, is the founder and director of the Scripps Research Translational Institute; Executive Vice President, Scripps Research; Professor, Molecular Medicine, Scripps Research; and the Gary and Mary West Endowed Chair of Innovative Medicine, Scripps Research. In many ways, Dr. Topol was he kindled that started the AI transformation with his more than 1,300 publications and bestselling books.

Dr, Topol appears last – alphabetically – on this Top 20 Voices in AI and ChatGPT to follow. His ideas and prodding the system, perhaps place him first!

• LinkedIn
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Spot a broken link, typo, forgotten degree or name misspelled?

Oops! Apologies! While care has been taken in compiling this list and adding social media links, things go wrong or a name is misspelled or a link broken. Please do get in touch to address typos, amendments, or omissions by reaching gil.bashe@medika.life.

Thanks in advance and be healthy!

The post Medika’s Top 20 AI Voices to Watch. Follow These Experts as They Demystify AI and Its Future appeared first on Medika Life.

 How so?

The COVID pandemic has changed the way we evaluate health technologies in four important and distinct ways.

1. Practicality replaces glitz.  The “Wow factor” is what mattered in the past.  “Look how cool this laser is that can identify your heart rhythm from 300 feet away!” “This headset lets me see how food travels through my body in real time!”   Technology can still be cool, but now the question is how will I use it?  Wearables that measure important variables like blood pressure will get more attention than new imaging tools that simply provide a clearer picture.
2. Prevention takes precedence over therapeutics.  COVID has demonstrated to us the importance of our personal health.  For too long, we made our jobs and other commitments our top priority.  Going forward, one’s personal health will become a major focus, especially as it relates to prevention.  How will a particular technology let me take control of my own health?  Nowadays, I am now more interested in a toilet that can monitor my urine for signs of diabetes or my stool for colorectal cancer than a device that creates holograms.  Once one gets pass the “icky” factor of some tools,  we will evolve to truly personalized preventive medicine.
3. Rigorous outcomes rule the day.  Everything now will be measured by how did it change patient outcomes.  Sure, it a device might show a new way to measure blood glucose – but what impact does it have on quality of life, co-morbidities, and life expectancy?
4. Consumer centricity rather than physician centricity.  In the past, technology has been focused on the health system and doctors.  It’s been a B-B approach.  That won’t go away, but more and more tech innovations will put the health consumer in charge.  For instance, I won’t be wearing a device that sends all the information to my doctor, but rather there will be more interpretation of all the data from wearables with direct communication to the patient.  This may require changes in regulation by the US Food and Drug Administration with a more practical definition of what constitutes a “medical device.” 

The real future of  digital health is when tech tools  continuously collect health data points and help interpret the information and provide preliminary diagnoses to patients.   The doctor isn’t going to be left out of this equation, but the difference will be that the patient will no longer be left out.  It’s the patient who will be at the center of how these technologies function from start to finish.

I’m sure I still going to be wow-ed this year and be entertained by the advancements we have made, especially during the last two years. But I’m also going to ask tougher questions on innovation, especially as relates to the purpose and impact.

The post Four Ways COVID has Changed Health Tech appeared first on Medika Life.

From evolution to the industrial revolution, this is a recurrent theme for humanity and all life on earth. We receive a kick in the ass and move (sometimes crying and screaming) into the future. Sometimes, it’s a singular event that drives a profound transformation—remember those dinosaurs and that asteroid?  And if you use your imagination, you might even see that horrific sphere in the sky and conger some images of the COVID-19 virus. Sometimes it’s a cluster catastrophic events or a confluence of magical things. 

Change is disruptive.  But adoption is gradual.  And that where people get confused.

The year 2021 was certainly disruptive.  And it was defined by COVID-19 and void of innovation that perfectly reflected the difference between disruption and adoption. Certainly, there were important breakthroughs including therapeutics and vaccinations.  But failure was also a defining aspect of a tumultuous year. Adoption can drag its feet…

Clinical uncertainty was met with the demands of rapid action and resulted in the complexities of innovation, confusion, and adoption. COVID-19 compressed years of science, pharmaceutical development, technological advances and clinical practice into just months—sometimes even days. And then, layered moral imperative of action into this equation. The lessons learned from 2021 are vast. But, in many instances, these lessons were driven by events, or, if I may, singularities that helped shape and drive action.

It seemed that almost every day in the past year provided new data, insights, and guidelines that helped informed clinical practice. Yet, this pushed clinicians away from the “clinical comfort zone” into more a “risk/reward” posture where conformation was either antidotal, pre-published, or driven by societal and political pressures. Consensus—from patient to clinician—was sometimes difficult to find. But bravery, from thought to deed, was frequently at hand.

Today, we are around the corner from another asteroid or spike protein.  But we are also at the center of another confluence that offers the potential to transform and protect humanity from those fireballs in the sky.

Social need, technology, genomics, artificial intelligence and a host of factors are aligned for more than a change, but a tectonic shift of unimaginable proportions. These are coming at us with the jolt of disruptive transformative that can make us cling to a safer and more predictable past. But that’s the nature of transformation.  It’s sudden and shocking.  But the human side of that journey may not always align. 

The traditional vision of our future and of transformation is our desire for  “the same but better.”  From the emergence of the electric car (a transition) to the introduction of a new beta-lactam antibiotic with better tolerability and spectrum of coverage (another transition), we adopt in baby steps.  But technology can often loom larger and step more broadly. 

That’s where we are today.  Look up and you’ll see it.  We are just heartbeats from our next inflection point. The question isn’t only about the wonder of technology to help solve these conflicts, but the bravery of humanity to move forward.

The post Perhaps, A Braver New World appeared first on Medika Life.

1. Poor Design

Without a doubt, the most commonly raised issue for existing solutions and new-to-market products that rely on user input, whether patient or provider input. The refrain “the system doesn’t allow me to do x, y, or z” can be heard across every field of healthcare in America. This speaks to one single cause. Poor design based on a limited understanding of the ecosystem you are engaging with and as it’s a frequent refrain, many companies, in fact, the large majority, are at fault here.

You are producing AI and data-driven software that, while efficient at performing its assigned tasks, lack the ability to perform accurately or meaningfully as your data capture is incomplete. You’re not asking the right questions and offering your user the breadth of input they require for their responses. The result is an incomplete picture and as you’re probably all too well aware, in healthcare that can prove fatal at worst, and at best, result in, you guessed it, terrible adoption.

You’ve chosen one of the most complex ecosystems to distribute a product into. Not only is the healthcare sector incredibly diverse with wide-ranging needs to address the most complex piece of machinery on the plant (the patient), this ecosystem is already filled with a multitude of products that you need to be able to communicate with seamlessly. There is no standardized Windows, Apple, or Android platform to base development on. Healthcare is the programmer’s version of data hell and you need to be ready to toss out all your preconceived ideas out the window.

To develop an effective AI or digitally driven software solution for healthcare(we’re not referring to cutting edge medical devices and tools here, but rather the software that drives much of the industry) it’s time to go back to med school 101 and that involves being able to draw on a full picture. One that includes both patient and provider views. Fail either and you’re doomed. This might sound patently obvious, it clearly isn’t and it this lack of a proper appreciation for the issues faced in the day-to-day practices of patients and providers that undoes most new solutions.

Startups need to spend time in their doctor’s and patients’ shoes. Live with them, shadow them and develop systems that solve their problems without creating new ones. Only once you can relate to their experiences can you arguably develop suited tools and solutions. You can’t provide the answers when you’re not even sure which questions to ask. Embed yourself and learn first. Then do what you do best. Build solutions.

2. Inbuilt Bias

I’ve broached this topic before and it’s a critical one that speaks directly to patient safety. Depending on which areas of the United States you’re pushing your services into, you’re addressing a multilingual, multiracial patient and provider landscape. The time for developing solutions for a white middle-class patient has died a well-deserved death and is now ascribed to history. The fact that so few platforms address equitable access to healthcare successfully is almost criminal, not only from an ethical perspective but when viewed from monetizing any solution.

Dude, you just missed half your customers. Seriously. Do you know how many Asians, Hispanics, and other nationalities intentionally avoid using your solution because you’ve built bias into the system? What about the elderly? You’ve forgotten about half your market and that has two major consequences. Let’s examine both.

• You‘ve just cut your income stream in half and potentially rendered your product obsolete by not making it inclusive. It will suffer from poor adoption rates and as users discover its limitations you will hemorrhage clients. Trust me, go ahead and design for privilege, intentionally or otherwise, and let me know how that turns out.
• You‘ve developed a product that is in direct contradiction to healthcare’s much-vaunted goals of equitable and accessible care for all. We’re not there yet, but if your solution is part of the problem rather than seeking to address it, you can see where this is going right? EVERYONE, irrespective of race, color or creed should benefit or be able to benefit from your solution. If not, then it clearly isn’t fit for purpose.

Create products that are inclusive and allow for varying levels of access and when all else fails, still allow for human interaction. Do this well, and in the current market, you are ensured of spectacular success.

3. Flexibility

The ability to change and adapt to a fluid working dynamic like the one posed by healthcare is key to your product’s success. No matter how much homework you’ve done, how inclusive your system is, and how much money you’ve spent on testing, you’re dealing with human beings and ever-changing dynamics in terms of protocols and treatments. Build a rigid system that cannot be easily and rapidly fine-tuned and you will quickly find yourself in customer service hell.

IT companies often adopt an attitude of “fault tolerance levels”, waiting for the reports of glitches and flaws to mount up before they effect system-wide repairs. Healthcare is no different and if you want to really get a leg up on the competition, your ability to respond quickly and meaningfully is key. Not only will you reduce customer service loads, but your solution will also ingratiate itself with providers, who in turn, will ensure widescale adoption and brand loyalty. Win, Win.

Ignore issues, calls for updates, changes, and additions to a system and you’re committing brand suicide. At best, you’re alienating your customer and at worst, your inability to respond to requests for change can cost patients their lives. Neither outcome is desirable Build it so you can change it. Easily and quickly. This one aspect alone, coupled with simple and accessible customer service, will set your product light-years apart from competitors.

4. Understand the problem you’re addressing

This isn’t about poor design, although the two concepts overlap. it is about not correctly understanding the parameters of the problem you are seeking to address and this can have major ramifications when it comes to product adoption. One GP or a hospital that faces an issue is not reflective of the entire industry and problems can often be localized to an area or state. Do your homework. Understand the extent of the problem before you set about creating solutions.

Keep in mind that solutions don’t make users’ lives more complex. This is at odds with the whole idea of a solution and yet, the market is flooded with clever ideas that practitioners don’t need, much less have time for. Does your product address a widespread issue faced by healthcare workers, does the solution simplify their lives, and finally, is it simple to use. Tick all three or head back to the drawing board. Again, these are basics, but basics that are often lost sight of in our eagerness to bring our version of a solution to the marketplace. Any addition to a doctor’s workload that doesn’t translate into time saved and better patient outcomes is doomed to failure. Understand the problem you’re addressing and ensure the solution is appropriate.

Develop working models and consult with your users along every step of development. Changing tack is easily done when you’re in the development phase, less so when your distributing.

5. Accessibility

Possibly the most obvious of all, and yet, applications are still designed that will only function in the chrome browser, require the latest computers to run, and offer users complex and logic-defying UI’s. Dependence on a stable internet connection is another issue faced by many applications. kill the internet and you kill the application. While many solutions require an internet connection for functionality, many don’t, and making a system available offline increases reliability and access. 

Offering your solution across all platforms and browsers also greatly increases adoption and again, for a world that loves digital but doesn’t enjoy total coverage, don’t ignore your users that don’t as yet have access to smart devices. Integrate voice for people who don’t own a smartphone, who may not have internet, or who may simply not be familiar with our technical world. They also require access to medical help and the solutions you are creating. Be innovative and include them.

Ensure application UI’s are user-friendly, that visually impaired users can access the system and that font sizes can be adjusted. Inclusivity is your guiding principle for any healthcare application, particularly patient-facing solutions.

Going Commercial

There are fortunes to be made and lost in healthcare, especially in the trending arena of digital health. That hunger for profit and the need to generate turnover is often achieved at the expense of the patient and the provider. If your sole purpose is revenue, your experience with healthcare will most probably be singular and short-lived. The industry is unlike any other and while commercial interests do currently skew the medical landscape there are moves afoot to set the world to rights,

Idealists, purists, and ethical professionals want to ensure a return to patient-focused medicine, where the patient serves as both the motivation for and the final purpose behind the industry. Again, companies who are perceived as furthering the commercial exploitation of healthcare and patients will be spurned for their more ethical competitors. This patient-focused movement is alive, well, and growing within healthcare. Developers would be well placed to ensure their primary focus is improving the lot of the patient, even if that means occasionally forsaking profits and shareholders.

The post 5 Key Pitfalls That Compromise or Sink Digital Health Startups appeared first on Medika Life.

Join Bianca Phillips, John Nosta and Gil Bashe in a thought provoking discussion on the Digital Health Revolution.

About Bianca

Bianca Rose Phillips wants to help build a world where telemedicine enables access to healthcare no matter where you live, where the mainstream use of wearables allows for disease prediction before anything happens, and where clinical outcomes are improved because of uses of precision and personalised medicine. 

She is considered a leading thinker on the future of digital health and the law, recognised globally for her thought leadership in the field. Her ideas attract the biggest minds and companies in digital health.

Bianca takes you on a journey to imagine a future immersed in digital health. Her works include: The Digital Health Revolution: Structural Elements & Logical Methods, and ‘The Digital Health School of Thought.’

​These works explore the processes, pillars and methods upon which digital health laws and societies are built, constrained, transformed and revolutionized.  

She holds a Bachelor of Laws, Bachelor of Commerce, Graduate Diploma of Professional Legal Practice, Master of Laws (Medical Law). Admitted as a Lawyer & Officer of the Supreme Court. Juris Doctor Lecturer. 

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