Category Archives: Healthcare

Why We Need Digital Health Package Inserts

Why We Need Digital Health Package Inserts

GUEST POST from Arlen Meyers, M.D.

The Food and Drug Administration announced new rules for nutrition labels that can go on the front of food packages to indicate that they are “healthy.”

According to one source, a package insert is a document included in the package of a medication that provides information about that drug and its use. For prescription medications, the insert is technical, and provides information for medical professionals about how to prescribe the drug. Package inserts for prescription drugs often include a separate document called a “patient package insert” with information written in plain language intended for the end-user — the person who will take the drug or give the drug to another person, for example a minor. Inserts for over-the-counter medications are also written plainly.

In the US the document is called “prescribing information” or the “package insert” (PI) and layperson’s document is called the patient package insert (PPI). In Europe the technical document is called the “summary of product characteristics” (SmPC) and the document for end-users is called the “patient information leaflet” (PIL) or “package leaflet”.

Given the confusion about 1) which digital health product to prescribe for any given patient, 2) the fact that many products are actually consumer products designated to provide information and education, not diagnosis or treatment, and 3) most are not clinically validated or cost-effective, perhaps it’s time to require package inserts for the prescriber and the patients.

Prescription digital therapeutics is also being added to the therapeutic armementarium and is raising several questions about safety, effectiveness, cost-effectiveness, ROI, reimbursement and regulatory requirements, including whether package inserts should be required, how they should be made available to patients, and what they should include.

What is in a package insert is described and required by the FDA and includes:

  • Clinical pharmacology – tells how the medicine works in the body, how it is absorbed and eliminated, and what its effects are likely to be at various concentrations. May also contain results of various clinical trials (studies) and/or explanations of the medication’s effect on various populations (e.g. children, women, etc.).
  • Indications and usage – uses (indications) for which the drug has been FDA-approved (e.g. migraines, seizures, high blood pressure). Physicians legally can and often do prescribe medicines for purposes not listed in this section (so-called “off-label uses”).
  • Contraindications – lists situations in which the medication should not be used, for example in patients with other medical conditions such as kidney problems or allergies
  • Warnings – covers possible serious side effects that may occur
  • Precautions – explains how to use the medication safely including physical impairments and drug interactions; for example “Do not drink alcohol while taking this medication” or “Do not take this medication if you are currently taking MAOI inhibitors
  • Adverse reactions – lists all side effects observed in all studies of the drug (as opposed to just the dangerous side effects which are separately listed in “Warnings” section)
  • Drug abuse and dependence – provides information regarding whether prolonged use of the medication can cause physical dependence (only included if applicable)
  • Overdosage – gives the results of an overdose and provides recommended action in such cases
  • Dosage and administration – gives recommended dosage(s); may list more than one for different conditions or different patients (e.g., lower dosages for children)
  • How supplied – explains in detail the physical characteristics of the medication including color, shape, markings, etc., and storage information (e.g., “Store between 68 and 78°F “)

Of course, there would need to be some modifications, like:

  1. Safety and efficacy
  2. Cybersecurity risks
  3. Data security
  4. Data , privacy, ownership and transfer rights
  5. Side effects
  6. Designation as a consumer product or a diagnostic or therapeutic device
  7. Generic substitution possibilities
  8. Adverse app reactions
  9. App-app interactions
  10. Compatibility with other drugs or devices

One thing that will not be in the insert will be what all this costs to you or someone else who has to pay for it.

Research shows that “Safety of apps is an emerging public health issue. The available evidence shows that apps pose clinical risks to consumers. Involvement of consumers, regulators, and healthcare professionals in development and testing can improve quality. Additionally, mandatory reporting of safety concerns is needed to improve outcomes.”

It is short-sighted, however, to let DTC medical apps slip under the regulatory radar. As described in a recent article for Nature, they could turn out to have costs which insurers or taxpayers might ultimately be responsible for.

But, the FDA is not the only agency with regulatory power. How about the Federal Trade Commission? Almost every promotion these days claims “AI-powered” What should be the truth in advertising standards to make that claim? Should there be something like a nutrition label ?

Medical student and resident education in clinical informatics, including artificial intelligence, is a good start. Here are some potential curricular and extracurricular learning opportunities for artificial intelligence in medicine.

At this point you are probably thinking, “We have enough regulations and we love our APPs. So what if they don’t make us any better.”

Go shove your insert.

Next, you’ll be telling us it has to have all that cotton in the bottle too.

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Innovative Applications of AI in Healthcare

Innovative Applications of AI in Healthcare

GUEST POST from Chateau G Pato

As a human-centered change and innovation thought leader, I’ve always believed that true progress emerges when technology serves humanity’s deepest needs. In no field is this more evident than healthcare, where Artificial Intelligence (AI) is rapidly transforming possibilities. We’re moving beyond incremental improvements to truly innovative applications that are reshaping patient care, operational efficiency, and even the very nature of medical discovery. This isn’t just about automating tasks; it’s about augmenting human intelligence, freeing up clinicians for higher-value activities, and delivering more personalized, proactive, and precise care.

The healthcare industry, traditionally cautious with radical technological shifts due to regulatory complexities and inherent risks, is now at an inflection point. The convergence of vast data availability, exponential computing power, and urgent global health needs has created the perfect storm for AI’s rapid adoption. Its capacity to process immense datasets, identify intricate patterns, and make predictions with astonishing accuracy is making it an indispensable tool. These innovative applications are not only addressing long-standing challenges like diagnostic errors and administrative burdens but also opening entirely new avenues for treatment and prevention, fundamentally improving the human experience of healthcare.

Revolutionizing Diagnostics and Treatment Planning

One of AI’s most profound impacts in healthcare is its ability to dramatically enhance diagnostic accuracy and personalize treatment plans. Machine learning algorithms, meticulously trained on massive repositories of medical images, comprehensive patient records, and intricate genomic data, can detect anomalies and predict disease progression with a precision that often surpasses human capabilities. This leads to earlier detection, more targeted interventions, and ultimately, significantly better patient outcomes.

Consider the realm of medical imaging. While radiologists are highly skilled professionals, the sheer volume of images they must review can lead to fatigue and occasional oversight. AI acts as an intelligent co-pilot, flagging suspicious areas for closer examination, thereby reducing diagnostic errors and speeding up the process. This means faster diagnoses and more timely treatment for patients. Similarly, in pathology, AI can analyze tissue samples, identifying cancerous cells with remarkable accuracy, which is crucial for early and effective treatment, ultimately saving lives and improving quality of life.

Streamlining Operations and Personalizing Care Delivery

Beyond diagnostics, AI is making significant strides in optimizing healthcare operations and enabling more deeply personalized care delivery. From automating tedious administrative tasks to empowering virtual health assistants, AI is constructing a more efficient, responsive, and truly patient-centric healthcare ecosystem.

The administrative burden on healthcare professionals is staggering, often consuming valuable time that could be spent on direct patient interaction. AI-powered tools can automate complex scheduling, streamline billing processes, and efficiently manage electronic health records (EHRs), allowing clinicians to refocus on what matters most: compassionate, high-touch patient care. Furthermore, AI-driven predictive analytics are transforming population health management. They can forecast patient no-shows, optimize resource allocation within hospitals, and even predict potential disease outbreaks, enabling proactive public health interventions that benefit entire communities.

Personalized medicine, once a distant dream, is now becoming a tangible reality thanks to AI. By meticulously analyzing an individual’s unique genetic makeup, lifestyle data, and comprehensive medical history, AI algorithms can identify the most effective treatments and even predict how a patient will respond to specific medications. This fundamentally shifts healthcare from a generalized, one-size-fits-all approach to highly tailored interventions, maximizing efficacy, minimizing adverse effects, and ensuring each patient receives the care best suited to their individual needs.

Case Studies in Action: AI as a Human Enabler

Case Study 1: Accelerating Drug Discovery with AI – BenevolentAI

The traditional process of drug discovery is notoriously time-consuming, immensely expensive, and fraught with high failure rates. Identifying potential drug candidates, thoroughly understanding complex disease pathways, and accurately predicting drug interactions can take years, even decades. BenevolentAI, a pioneering AI company, is revolutionizing this process by leveraging AI to dramatically accelerate drug discovery and development, bringing life-saving treatments to market faster.

Their cutting-edge, AI-driven platform ingests and synthesizes vast amounts of biomedical data, including millions of scientific papers, comprehensive clinical trial results, and intricate genomic information. Through sophisticated machine learning algorithms, the platform identifies novel drug targets, generates groundbreaking new drug hypotheses, and even designs innovative molecular structures. This dramatically reduces the time and cost associated with early-stage drug discovery. A compelling example is BenevolentAI’s success in identifying existing drugs with potential to treat amyotrophic lateral sclerosis (ALS) by analyzing vast datasets of scientific literature, showcasing AI’s ability to uncover hidden connections and accelerate the repurposing of existing medicines for new indications.

By automating parts of the research process and uncovering insights that human researchers might miss, BenevolentAI is directly helping to bring life-saving medications to patients faster, transforming the pharmaceutical pipeline and offering renewed hope for previously untreatable diseases.

Case Study 2: Enhancing Diabetic Retinopathy Detection – Google DeepMind Health

Diabetic retinopathy is a leading cause of blindness worldwide, yet it is largely preventable if detected and treated early. However, effective screening traditionally requires skilled human graders to meticulously examine retinal scans, a process that can be resource-intensive and prone to inconsistencies, especially in underserved areas with limited specialist access.

Google DeepMind Health developed an AI system capable of detecting diabetic retinopathy from retinal scans with an accuracy comparable to, and in some cases even exceeding, that of human ophthalmologists. The system was trained on an immense dataset of millions of retinal images, meticulously labeled and verified by expert eye specialists. This AI can rapidly analyze scans and pinpoint signs of the disease, even subtle ones that might be overlooked by the human eye. This innovation holds immense potential for scaling up vital screening programs, particularly in regions with limited access to specialized medical professionals. It allows for significantly earlier intervention, preserving vision for countless individuals globally and alleviating the immense burden on healthcare systems.

This case powerfully highlights AI’s ability to augment human expertise, improve accessibility to critical diagnostic tools, and ultimately, prevent debilitating conditions on a global scale, directly impacting the quality of life for millions.

The Human Element: Ethics, Trust, and Shaping Our Future

While the technological advancements are breathtaking, it’s crucial to always remember that AI in healthcare must remain unequivocally human-centered. This means prioritizing ethical considerations above all else, diligently building public and professional trust, and ensuring that AI serves to profoundly empower both patients and providers, rather than replacing the irreplaceable human touch.

Significant challenges such as patient data privacy, the potential for algorithmic bias, and the critical need for explainable AI are paramount. We must rigorously ensure that AI models are trained on diverse, representative datasets to avoid perpetuating or even amplifying existing health disparities. Transparency in how AI systems arrive at their decisions is also absolutely vital for clinicians to trust and effectively integrate these powerful tools into their practice. The “black box” problem of AI must be addressed with robust governance frameworks, continuous oversight, and a commitment to clarity.

The future of AI in healthcare is not one where machines replace doctors, but rather a synergistic partnership where AI acts as an intelligent, tireless assistant. It will free up clinicians to focus on the compassionate, empathetic, nuanced, and inherently human aspects of care that only humans can provide. It’s about empowering healthcare professionals with unparalleled insights, enabling more informed and precise decision-making, and ultimately, creating a healthier, more equitable world for everyone. As we continue to innovate, our unwavering focus must remain on the human at the heart of every interaction, ensuring AI is a powerful force for good, a true partner in advancing health and well-being for all.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Pixabay

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Land Mines of Intrapreneurship

Land Mines of Intrapreneurship

GUEST POST from Arlen Meyers, M.D.

Entrepreneurship is the pursuit of opportunity under VUCA (volatile, uncertain, complex and ambiguous) conditions with the goal of creating user/stakeholder defined value through the deployment of innovation using a VAST business model.

Intrapreneurs are employees trying to act like entrepreneurs within their organizations or non-profits. Here is the textbook of physician intrapreneurship.

Here is how to get your ideas noticed:

If you are trying to develop and deploy an AI solution in your sickcare organization, have you answered these questions?

Here are some reasons why your initiative will fail.

Do you have a VAST edupreneur business model?

Studies show that around 60 to 80% of new products fail. The same is probably true for programs and new educational offerings. It is difficult to determine the exact number of unreported cases, because who would like to talk about his innovation flops? The odds are against you.

So, what are the landmines to detect and avoid?

  1. You did not do your homework because you where unwilling, unable to do so ,or ,you do not have an entrepreneurial mindset and think because you already have 2 people who said they were interested that you could forge ahead.
  2. You did not have an exit strategy.
  3. You did not read the field manual.
  4. You don’t have the right sponsor with staying power.
  5. You tried to bite off more than your stakeholders are willing or able to chew.
  6. You are a bad rebel and chalk it up to “being authentic.”
  7. You do not have the right clinical champions on board.
  8. You have empty seats on the bus or the wrong people sitting in them.
  9. You are making these rookie intrapreneur mindset mistakes.
  10. You are not addressing the dysfunction of teams.
  11. You are not aligned with your organization’s strategy or vision.
  12. You are working in the wrong place with a toxic or fixed culture or for the wrong person.
  13. You don’t have an innovation strategy
  14. You don’t get sales and marketing
  15. You didn’t ask and answer these four questions before you started
  16.  If you’ve got a major change on the horizon, here’s how to avoid three of the most common saboteurs of company transformation. First, understand that significant change will be harder than you think it will be to achieve. Next, be realistic about your organization’s capacity to implement changes. Finally, make sure your organization understands how and why the transformation is important to you.
  17. You have not learned how to win at Survivor  1) Don’t expect friendship. Invest in relationships outside your company to meet your emotional needs; 2) Manage sideways. Your reputation with your peers becomes an important factor as you’re being considered for senior ranks; and 3) Hone your political skills.

If you get too far ahead of your troops, it is hard to tell the difference between you and the enemy. De-risk yourself. Be careful out there.

Image credit: Pixabay

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Should you be a physician entrepreneur?

Should you be a physician entrepreneur?

GUEST POST from Arlen Meyers, M.D.

Not every doctor is cut out to be a physician entrepreneur. Are you?

It seems to me there is confusion about physician entrepreneurship, its definition and whether it represents a threat to professionalism. I’m not alone. Is a physician entrepreneur someone who starts and runs a business, or is it something more?

Entrepreneurship is the pursuit of opportunity under variable, uncertain, complex and ambiguous conditions. The goal of all entrepreneurs, including physician entrepreneurs, is to create user defined value through the deployment of innovation using a VAST business model to accomplish, in the case of medical professionals, the quintuple aim or, if applicable, shareholder value.

Here are three things to know about physician entrepreneurship.

Because of the many changes in the art and practice of medicine, many doctors have decided to get involved in non-clinical side gigs or, in some instances, leave medicine entirely. Here is a guide to non-clinical careers.

Doctors are practicing the art of entrepreneurship for many reasons:

  1. It helps patients
  2. It’s fun and challenging
  3. It gives them the ability to exercise creativity
  4. It creates alignment and engagement with organization
  5. The profit motive
  6. It creates meaning
  7. It satisfies psychic needs
  8. It provides another sources of external vaidation
  9. It’s a way to get outside of your comfort zone
  10. It allows you to take more risk
  11. The sick care business model is broken and they want to be part of the big fix after feeling ignored and disempowered
  12. They have to to surthrive

Whether you are a pre-med, a medical student, a resident, a fellow or a practicing clinician thinking about beginning the entrepreneurial journey, you should take some time to identify your persona.

You career strategy starts with answering:

  1. Where are you now?
  2. Where do you want to go?
  3. How do you want to get there?

Begin by matching yourself with one of the four core entrepreneurial personas as defined by their willingness and ability to practice entrepreneurship successfully.

The Convinced and Confident know entrepreneurship should be part of their career pathway. In fact, many of them have had entrepreneurial life experiences prior to medical school.

The Curious but Clueless don’t know what they don’t know but are willing to learn more. Many have never held a job in their life. Some might be willing, but unable to develop an entrepreneurial mindset. . Others discover their innerpreneur, and move on.

The I Couldn’t Care Less are unwilling and unable to give it a try. Their attitude is , “I went to medical school to take care of patients, not take care of business”. What they don’t realize is that if you don’t take care of business, you have no business taking care of patients.

The Conflicted have yet to discover their “innerpreneur”, but are conflicted about whether to step outside of their comfort zones and cut the chord.

Your persona will help lead you to the next steps:

  1. The Convinced and Confident: Continue to improve your knowledge, skills, abilities and competencies and learn from your experience.
  2. The Curious but Clueless: Start with education, building your networks and finding mentors
  3. The I Couldn’t Care Less: Pass on entrepreneurship until or unless you change your mind. Here are the many reasons why you should not be a physician entrepreneur.
  4. The Conflicted: Start with the 6Rs of physician career transitioning, beginning with reflection.

Where you are in the thought process will depend on who you are.

Moving from unawareness to awareness to intention to decision to action might show you someone in the mirror you would have never recognized in the past. Or, you might be looking at the same old person.

Image credit: Pixabay

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Challenges of Artificial Intelligence Adoption, Dissemination and Implementation

Challenges of Artificial Intelligence Adoption, Dissemination and Implementation

GUEST POST from Arlen Meyers, M.D.

Dissemination and Implementation Science (DIS) is a growing research field that seeks to inform how evidence-based interventions can be successfully adopted, implemented, and maintained in health care delivery and community settings.

Here is what you should know about dissemination and implementation.

Sickcare artificial intelligence products and services have a unique set of barriers to dissemination and implementation.

Every sickcare AI entrepreneur will eventually be faced with the task of finding customers willing and able to buy and integrate the product into their facility. But, every potential customer or segment is not the same.

There are differences in:

  1. The governance structure
  2. The process for vetting and choosing a particular vendor or solution
  3. The makeup of the buying group and decision makers
  4. The process customers use to disseminate and implement the solution
  5. Whether or not they are willing to work with vendors on pilots
  6. The terms and conditions of contracts
  7. The business model of the organization when it comes to working with early-stage companies
  8. How stakeholders are educated and trained
  9. When and how which end users and stakeholders have input in the decision
  10. The length of the sales cycle
  11. The complexity of the decision-making process
  12. Whether the product is a point solution or platform
  13. Whether the product can be used throughout all parts of just a few of the sickcare delivery network
  14. A transactional approach v a partnership and future development one
  15. The service after the sale arrangement

Here is what Sales Navigator won’t tell you.

Here is why ColdLinking does not work.

When it comes to AI product marketing and sales, when you have seen one successful integration, you have seen one process to make it happen and the success of the dissemination and implentation that creates the promised results will vary from one place to the next.

Do your homework. One size does not fit all.

Image credit: Pixabay

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Real-World Applications of Design Thinking

Real-World Applications of Design Thinking

GUEST POST from Chateau G Pato

As a human-centered change and innovation thought leader, I’ve witnessed firsthand how design thinking can revolutionize the way organizations approach complex problems. Design thinking is not just a process but a mindset that prioritizes empathy, experimentation, and iteration. In this article, I’ll explore some real-world applications of design thinking, showcasing its transformative potential through two compelling case studies.

The Essence of Design Thinking

Design thinking emphasizes an iterative process and involves stages like empathy, definition, ideation, prototyping, and testing. Its power lies in its ability to break down silos, foster collaboration, and create solutions that are deeply aligned with user needs.

Case Study 1: Improving Public Transportation in Singapore

Singapore’s Land Transport Authority (LTA) faced challenges in optimizing the city’s public transportation system. With overcrowding and inefficiencies impeding commuter satisfaction, the LTA needed innovative solutions. They turned to design thinking for help.

The LTA began with the empathy phase, conducting in-depth interviews and surveys with commuters, bus drivers, and staff. This approach helped them to uncover pain points such as long waiting times, insufficient information about bus schedules, and crowded carriages.

In the ideation phase, multiple brainstorming sessions were held, bringing together diverse perspectives from designers, engineers, and everyday commuters. Ideas like real-time tracking apps, the redesign of bus stops, and enhanced user information systems were prototyped and tested with actual users.

Through iterative prototyping, the LTA successfully implemented real-time digital screens at bus stops, providing exact arrival times and occupancy levels. This innovation not only improved commuter satisfaction but also led to a 15% increase in public transport usage.

Case Study 2: Revolutionizing Healthcare through Human-Centered Design

Healthcare can often be a challenging field for both patients and providers. The Mayo Clinic, recognized globally for its patient-centered care, saw an opportunity to enhance patient experience further using design thinking.

The clinic embarked on an empathy-driven exploration by gathering insights from patients, families, and medical staff. They discovered that while the clinical care was excellent, the waiting experience and navigation through the facility were areas needing improvement.

With these insights, multidisciplinary teams engaged in ideation sessions, which led to the design of a patient-centric app. This app provided real-time updates on appointment timings, directional aid within the hospital, and educational content about their medical procedures.

Prototypes of the app were developed and tested with patients and staff, leading to refinements based on feedback. The final product was launched, significantly improving patient satisfaction scores and reducing perceived waiting times by 30%.

Conclusion

Design thinking is a powerful tool for organizations seeking to innovate and address complex challenges. By putting the user at the center of the process, organizations can create solutions that truly resonate with people’s needs. Whether it’s revolutionizing public transport in Singapore or enhancing patient care at the Mayo Clinic, the examples above illustrate the tangible impacts of this approach. As we move forward, the continued application of design thinking promises to unlock even greater potential in various sectors worldwide.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Unsplash

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What will it take to create a national medical records system?

What will it take to create a national medical records system?

GUEST POST from Arlen Meyers, M.D.

Almost every person that has experienced the US sickcare system has been frustrated by the lack of data interoperability. We are all paying the costs, now pegged at $4.1T. About $1T of the tab is waste.

Here is the case for data interoperability.

Larry Ellison, the CEO of Oracle, is the latest person who says he wants his company to fix that.

Like those that preceded him, he will face:

  1. Stakeholders that don’t play nice with each other
  2. An enormous cost
  3. Trying to create a VAST business model
  4. Inconsistent technical standards
  5. Competition
  6. The lack of a national patient unique identifier system
  7. Privacy and confidentiality issues
  8. A highly regulated system for patients sharing their data
  9. End user resistance to dissemination and implementation
  10. Cybersecurity
  11. Connecting the kaleidoscope of the disparate elements of the US sickcare system of systems, like the VA, safety net hospitals, rural hospitals, academic centers and DOD facilities
  12. Combining financial data with clinical data
  13. Combining research data with clinical care data
  14. Varying levels of data maturity in the system
  15. Accessing data that is created outside of traditional medical service facilities
  16. The growth of retail sickcare and sicktech companies
  17. Harnessing data from the internet of medical things
  18. Integrating artificial intelligence to not only achieve the quintuple aim, but also create shareholder value that will conflict with one another
  19. Winning the “cloud wars”
  20. The lack of trust and growing sickcare technoskepticism
  21. The Cerner VA implentation FUBAR halo effects.
  22. Changing the EMR “SHIT” -single most hated information technology- to a whole product solution
  23. Accessing unstructured data on social media sites
  24. Governance of the enterprise
  25. Regulatory oversight of software as a medical device and digital therapeutics
  26. Low levels of sickcare professional and patient data literacy
  27. Barriers to international data sharing in a era of pandemics and required rapid response
  28. Fax facts
  29. Push back from patients who want to be paid for their data
  30. Decentralized clinical trial data issues
  31. DEI
  32. Leaderpreneurship skills
  33. UI/UX Will he eliminate passwords?

Wouldn’t it be nice if Sickcare USA, Inc. could provide you with the same experience as your bank ATM system?

Is Larry really the smartest person or just in the wrong room?

Image Credit: Pixabay

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The Ethics of AI in Innovation

The Ethics of AI in Innovation

GUEST POST from Chateau G Pato

In today’s rapidly evolving technological landscape, artificial intelligence (AI) plays a pivotal role in driving innovation. From healthcare and transportation to education and finance, AI’s potential to transform industries is unparalleled. However, with great power comes great responsibility. As we harness the capabilities of AI, we must also grapple with the ethical implications that accompany its use. This article delves into the ethical considerations of AI in innovation and presents two case studies that highlight the challenges and solutions within this dynamic field.

Understanding AI Ethics

AI ethics refers to the moral principles and guidelines that govern the development, deployment, and use of AI technologies. These principles aim to ensure that AI systems are designed and used in ways that are fair, transparent, and accountable. AI ethics also demand that we consider the potential biases in AI algorithms, the impact on employment, privacy concerns, and the long-term societal implications of AI-driven innovations.

Case Study 1: Healthcare AI – The IBM Watson Experience

IBM Watson, a powerful AI platform, made headlines with its potential to revolutionize healthcare. With the ability to analyze vast amounts of medical data and provide treatment recommendations, Watson promised to assist doctors in diagnosing and treating diseases more effectively.

However, the rollout of Watson in healthcare settings raised significant ethical questions. Firstly, there were concerns about the accuracy of the recommendations. Critics pointed out that Watson’s training data could be biased, potentially leading to flawed medical advice. Additionally, the opaque nature of AI decision-making posed challenges in accountability, especially in life-or-death scenarios.

IBM addressed these ethical issues by emphasizing transparency and collaboration with healthcare professionals. They implemented rigorous validation procedures and incorporated feedback from medical practitioners to refine Watson’s algorithms. This approach highlighted the importance of involving domain experts in the development process, ensuring that AI systems align with ethical standards and practical realities.

Case Study 2: Autonomous Vehicles – Google’s Waymo Journey

Waymo, Google’s self-driving car project, embodies the promise of AI in redefining urban transportation. Autonomous vehicles have the potential to enhance road safety and reduce traffic congestion. Nevertheless, they also bring forth ethical dilemmas that warrant careful consideration.

A key ethical challenge is the moral decision-making inherent in self-driving technology. In complex traffic situations, these AI-driven vehicles must make split-second decisions that could result in harm. The “trolley problem”—a classic ethical thought experiment—illustrates the dilemma of choosing between two harmful outcomes. For instance, should a self-driving car prioritize the safety of its passengers over pedestrians?

Waymo addresses these ethical concerns by implementing a robust ethical framework and engaging with stakeholders, including ethicists, regulators, and the general public. By fostering open dialogue, Waymo seeks to balance technical innovation with societal values, ensuring that their AI systems operate ethically and safely.

Principles for Ethical AI Innovation

As we navigate the ethical landscape of AI, several guiding principles can help steer innovation in a responsible direction:

  • Transparency: AI systems should be designed with transparency at their core, enabling users to understand the decision-making processes and underlying data.
  • Fairness: Developers must proactively address biases in AI algorithms to prevent discriminatory outcomes.
  • Accountability: Clear accountability mechanisms should be established to ensure that stakeholders can address any misuse or failure of AI technologies.
  • Collaboration: Cross-disciplinary collaboration involving technologists, ethicists, industry leaders, and policymakers is essential to fostering ethical AI innovation.

Conclusion

The integration of AI into our daily lives and industries presents both immense opportunities and complex ethical challenges. By thoughtfully addressing these ethical concerns, we can unleash the full potential of AI while safeguarding human values and societal well-being. As leaders in AI innovation, we must dedicate ourselves to building systems that are not only groundbreaking but also ethically sound, paving the way for a future where technology serves all of humanity.

In a world driven by AI, ethical innovation is not just an option—it’s a necessity. Through continuous dialogue, collaboration, and adherence to ethical principles, we can ensure that AI becomes a force for positive change, empowering people and societies worldwide.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Microsoft CoPilot

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17 Reasons Not to Be a Physician Entrepreneur

17 Reasons Not to Be a Physician Entrepreneur

GUEST POST from Arlen Meyers, M.D.

Judging by the headlines on their LinkedIn profile and their presence on social media, more and more MD/DOs are innovators, coaches, entrepreneurs and non-clinical consultants. Many are starting or working with biomedical and clinical startups, including a group of medical school graduates, who don’t do a residency or starting their own company.. But:

  • They are not trained to do so
  • Entrepreneurship in the US has been in a downward spiral in the US for the past 40 years.
  • Most startups will fail
  • Most startups don’t have money to pay people
  • There is an innovation bubble.
  • Job security is low
  • You have to deal with people who have entrepreneurial psychopathologies are simply untrustworthy.
  • Students loan burdens are rising
  • Many are not in it for the long run
  • There are unrealistic expectations on both the consultant/employee and employer side.
  • Most MD/MBA programs should be terminated
  • Innovation theater is pervasive.

What is physician entrepreneurship? Entrepreneurship is the pursuit of opportunity under volatile, uncertain, complex and ambibuous conditions (VUCA).. The goal of physician entrepreneurs, is to create user defined value through the deployment of innovation using a VAST business model to accomplish the quintuple aim. There are many ways to do that other than creating a company.

Here are some reasons why you should think twice about being a physician entrepreneur:

  1. You are not ready to innovate
  2. You do not have the courage to innovate
  3. You do not have the mindset to innovate
  4. You think that your clinical mindset and your medical degree and training is enough to succeed
  5. You are not in a financial position to take the risk
  6. You are doing it to get away from someone of some job instead of towards something that is a better fit
  7. You do not have a career transition strategy
  8. You or your family are not willing to pay the price of successive failure
  9. You are unwilling to come down off the mountain
  10. It’s not personal
  11. You are not ready to quit your day job
  12. If you decide to create a company, or work for one, making money for the company is not that important to you.
  13. You don’t have the knowledge, skills, abilities and competencies to add value to a business
  14. You don’t have entrepreneurial DNA
  15. You don’t have a big enough network or know how to manage it as part of building your personal brand
  16. You don’t know how to sell things
  17. You are a problem solver, not a problem seeker.

Think twice about telling someone to take your white coat and shove it. You will save yourself and lots of other people heartburn and other people’s time, effort and money.

Image Credit: Pixabay

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Future of Global Physician Entrepreneurship

Future of Global Physician Entrepreneurship

GUEST POST from Arlen Meyers, M.D.

What’s your definition of entrepreneurship? Here’s the conventional one.

Mine is that physician entrepreneurship is the physician pursuit of opportunity under volatile, uncertain ,complex and ambiguous (VUCA) conditions with the goal of creating user defined value through the deployment of innovation using a VAST business model.

There are many myths about entrepreneurs. Here are some about physician entrepreneurs.

The life science innovation roadmap is risky, expensive and time consuming. To be successful, bioentrepreneurs whether healthcare professionals, scientists, engineers, investors or service providers, need to work as a team with their organizations to overcome the multiple hurdles taking their ideas to the market and patients. The process is neither linear nor predictable and outcomes are never guaranteed. In addition, because of global macroeconomic conditions, investors are unwilling to gamble on unproven technologies in a more hostile regulatory and legal environment. Consequently, commercializing bioscience discoveries is becoming more and more difficult. However, innovators still thrive. Where are some of these exciting business opportunities for bioentrepreneurs?

An initial understanding of the changes happening in international systems is the first step in identifying potential market opportunities. Here are but a few:

  1. Major and continual healthcare policy reforms
  2. Migration away from fee for service payment
  3. Consumerization, commoditization, internationalization, customization and digitization of care.
  4. Changing from a sick care system to a preventive and wellness system
  5. Defined benefit to defined contribution health insurance coverage
  6. Rightsizing the healthcare workforce
  7. Do it yourself medicine (DIY)
  8. Mobile and digical (physical and digital) care delivery models
  9. The growth of employed physicians
  10. Innovation management systems and increasing attention to health entrepreneurship.
  11. Increasing demand for high touch care
  12. Increasing discontinuity of cares changing quickly. All of these changes present biomedical and healthcare entrepreneurs opportunities to create new products, services, models and platforms. Patients are taking more control of funding and contributing to basic and clinical research using the internet and social media continues to play a bigger and bigger role in healthcare marketing and delivery.
  13. Demographic and economic changes and social mobility
  14. Closing the digital divide
  15. The impact of the 4th industrial revolution

Take opportunities in AIntrepreneurship, for example, in India, China, MENA and Africa

The drivers of physician international entrepreneurship include:

  1. Fear: Doctors are afraid they will suffer the professional, personal and economic consequences if they don’t adapt to change
  2. Greed: Physician incomes are threatened by innovation and new business models
  3. Necessity: Most doctors in industrialized countries have a relatively high standard of living. They did not bother themselves with innovation or entrepreneurship because they didn’t have to.
  4. The innovation imperative: The pace of change has accelerated and markets and employers are demanding more with less
  5. Generational demands: Medical students and residents are questioning their career decisions and demanding that schools provide them with the innovation and entrepreneurship education and training knowledge, skills and attitudes they need to thrive after graduation and throughout their careers
  6. The shifting doctor-patient relationship: Technology and DIY medicine is disintermediating doctors and fundamentally altering the doctor-patient relationship
  7. Resources: The internet, local ecosystems, acclerators and access to early stage capital has made it easier to start a business or develop an idea. People are connecting to the global economy.
  8. Portfolio careers: The sick care gig economy is growing and the future of work is changing. Fewer are committing to one lifetime career or job, including clinical medicine
  9. Opportunities: With change, comes opportunities and those few doctors with an entrepreneurial mindset are actively pursuing them. The opportunities in health entrepreneurship are sizable and physician entrepreneurs are increasing well positioned to capitalize on them.
  10. Culture: The culture of medicine is changing and encouraging creativity and innovation
  11. Politics: Access to quality care at an affordable price is in high demand as middle classes grow in developing countries. Not providing it leads to social upheaval and political instability.
  12. Budget deficits: The demand for care is almost infinite. However, the supply is limited. Consequently, policy makers and markets are looking for ways to improve outcomes at a lower cost through the deployment of innovation.
  13. Youth unemployment: Restless unemployed, educated citizens are demanding jobs and ways to use their talents.
  14. Economic development: Innovation and entrepreneurship is fuel that that feeds the engines of economic development in emerging economies. like Africa.
  15. Globalization: People, money and technology go where they are treated best, regardless of location.

The future of physician entrepreneurship is measured by progress in four domains: educationpracticeresearch and impact. Unfortunately, each part of the physician innovation value chain is highly resistant to change and subject to multiple barriers to dissemination and implementation. We have made progress in all, but, the results are unevenly distributed.

The future of international physician entrepreneurship will be punctuated by:

  • The coherence of disparate technologies from diverse industries other than sickcare
  • Increasing transdisciplinary and international dependencies and collaboration
  • Educational reform in health professional, public health, bioengineering and computer science programs
  • Significant regulatory, legal, economic, ethical and societal issues
  • Generational, social and demographic variations in dissemination and implementation
  • An evolving global IT cybernervous system and interoperability
  • More difficult trust, privacy and security barriers
  • A high touch backlash against high tech
  • The rise of patient sickcare entrepreneurship
  • A slow migration to healthcare from sickcare

That said, this is the golden age of physician entrepreneurship, as reflected by the record number of applicants to US medical schools, the number of doctors pursuing non-clinical careers or side gigs, the ever increasing number of biomedical and clinical ecosystems, inclusion of digital health, business of medicine and entrepreneurship education and training in medical and graduate schools and the results and impact of entrepreneurs during the COVID pandemic.

Physician medical practice entrepreneurs, technopreneurs, intrapreneurs, social entrepreneurs, philanthropreneurs, edupreneurs and others are changing the world and the movement is spreading rapidly. Fortunately, despite efforts to the contrary, there is no vaccine to stop it.

Image credit: Unsplash

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