Session Information:

Transforming Healthcare Through Intelligent Automation

Session Transcript:

Donald Cook with us. Global leader, an influencer in healthcare, who's gonna lead us for this amazing journey of transforming health care through intelligent automation. Now, let me tell you, I've had the pleasure of working with Don for many global enterprise transformation in artificial intelligence conferences. And he always brings new and exciting innovations to every event. His legacy of success, transforming, Fortune 50 companies, to industry record setting, margin, and customer satisfaction improvement, has been the subject of many trade journals and radio show interviews.

Today, he'll be introducing new AI developments in both healthcare and health sciences, Dawn. It's always a privilege to be with you and to learn from you. Thank you for sharing your expertise with our global audience today.

Good morning, everyone. I'm honored to be here with you, and Joe say, talking about transforming health care through intelligent automation based enterprise transformation.

This is a topic that's near and dear to my heart, because I began my career at the University of the Air Forces Medical School, studying medicine for the Air Force and managed emergency medicine at Wright patterson Air Force Base Air Force Logistics command headquarters for four years.

And my career went full cycle, from medicine, through banking, computing, global central banking, and all the way back to medicine again.

And I had the opportunity to apply what I learned in automation to this new field, an emerging field of artificial intelligence applied in health care.

I am Donald Cook, I'm the Chief Transformation Officer and President of Enterprise Transformation Excellence.

That's a large consulting firm, global consulting firm, that provides transformation for very large enterprises. I'm currently transforming the one of the largest pharmaceutical companies in the world and one of the largest renewable energy companies in the world.

I've attached my LinkedIn profile. On this page, You'll get a copy of my presentation. So, if there are any questions, or if there's anything that I can do to help you to be successful in your automation journey, please don't hesitate to reach out to me. Just click on the link LinkedIn with me, and we can have an ongoing dialog about how you can become successful with some of these apps.

Applications, I'll share everything. I know my goal and dream is your success.

We have created a whole new world of healthcare through the courtesy of artificial intelligence, and certainly all of you that have been involved in the vaccine creation.

Um, or ..., know that we would never have achieved the success that we did and the turnaround time for development delivery.

If it hadn't been for intelligent automation involved in the vaccine production auction process.

And what we have done recently, in the last couple of years, is apply that same intelligent automation to healthcare, to the practice of medicine, both in our services and healthcare delivery. But, also, to improve operational efficiency. Because, as all of you may know, there's a serious shortage of health care providers on a global scale. And we need to get as much efficiency and productivity out of everyone as possible.

We'll talk today about the fundamentals of Artificial intelligence, development and Deployment.

And our methods. I'm going to talk about these in each in great detail in the slides that are upcoming, but I wanted to point out a couple in particular.

I am known, in my work, is known throughout the industry. You're welcome to Google me. Google me by name, Donald K UK. Cook, you'll see there are a number of articles written about my work and trade journals. I'm known for doing simultaneous process and technology, and can controls change.

Many of you have operational excellence programs that apply Lean six Sigma, and we apply Agile in technology development, but the two wrap around each other like the double helix of DNA, where the acid base pairs really don't ever touch, and one is constantly following the other.

We improve the process, but we break the technology. The technology and IT team comes in and improves the technology, but breaks the process. And so we never get to a highly optimized solution, I do both simultaneously.

I advocate doing both simultaneously, and we get the value delivery and the implementation of the process and technology change out, delivered in roughly 45% less time, and for about 60% less cost and effort.

This is particularly important and robotic process automation plays, where we need to have a highly optimized process before we automate.

Because while the computers are highly repeatable in their behavior, they're really not very smart. They only do what we tell them.

Do they get better with time?

Of course, through machine learning they get their tasks better, but they're really mostly well suited for highly repetitious tasks that are not well served by human beings. So our digital workers are really augmenting our human workforce.

We're using Artificial Intelligence and Intelligent Document Processing. We're going to talk about how we read and manage medical records and histories, And we even have an automated SharePoint site, that makes requests for Ms.

sharing documents in new patient records, so that we can complete the patient history.

And we have a full understanding of the patient condition.

I'm on intake.

And, or in the case of human transplant, when we're re-using human tissue, we know exactly the circumstances surrounding the patience, uh, death and recycling of their tissue, and whether or not they're eligible to recycle their tissue. There are a number of reasons for which we cannot re-use human tissue.

We use speech synthesis and speech recognition, particularly in sterile environments when everyone gets scrubbed and gloved. We don't want them pounding keys to do data entry, so we use speech recognition in order to capture all of the conversation and even the tasks in production when we're doing human tissue processing.

We use speech recognition in order to capture the completion of each of the tasks during the process. We use machine vision.

We'll talk about applications of that for spec thing. Tissue for subcutaneous defects, scars, stretch marks, and other things that would render the tissue less valuable for re-use in the case of human skin recycling.

We have a very exotic application of that that we'll talk about.

The use of Radiofrequency, Business Process Management, the linkage of artificial intelligence, along with RFID, to provide real-time tracking for everything that moves in plant and everything that moves in the hospital, including the patients, if we put an RFID wrist band on the patients. We can know exactly where they are located every moment throughout their journey during treatment and diagnosis, so we can direct them. Should they get lost on their way to radiology, should they get lost on their way to the pharmacy? We can direct them and give them guidance through their cell phone.

Intelligent integrated process technology, automation data and regulatory architecture.

This is the use of intelligence in business process management to create a three-dimensional view of the business in real time, and we use that in conjunction with the Radio Frequency Business Process Management in order to track events on a global scale in production and inpatient care, particularly for virtual patient care, we'll talk about that in a moment.

And then finally, we use Advanced Intelligent Automation to do fish, physician, patient, client, and customer behavioral analysis to understand how our patients behave when they're likely to arrive for their visits who's likely to be late or not, or miss them ointment and we can regulate and modify the patient's schedule in order to maximize physician efficiency.

These are the foundational elements that we manipulate, and we used to great success In intelligent automation applications, in healthcare.

They are a combination of traditional RPA, robotic process automation, speech synthesis, and speech recognition.

The use of the Intelligent Business Process management that we described, deep advanced behavioral data management and analysis, machine vision, the ability to see things that the human eye cannot see and be able to work with greater precision.

To do textual analysis, to use the combination of RPA and text analysis to read medical histories, and identify specific diseases, as well as symptoms and combinations of symptoms, was based on words, expressions, and even acronyms.

In order to highlight the medical record for a doctor, imagine receiving a patient that has a one thousand page medical history, and wanting to be both comprehensive and efficient in the review, it would take four days to read in detail of a thousand page history. We now read the computer, reads the document in about three tenths of a second.

and identifies in, read all of the sections of the document, all of the patient history Information.

that is important for consideration as either a symptom for a disease symptomatic of a particular outcome or a known diagnosis from a prior treatment.

We use radiofrequency Business Process Management.

We use a combination of the artificially Intelligent Business Process Management that we described before and radio frequency identification to manage events in real time. These tags are incredibly inexpensive, they're 15 to 18% apiece.

The new RFID tags have enough content information, and they are programmable so that we can update the information on the tag every time something is touched or processed, and every time the patient is seen or or visits a particular clinic, or a diagnosis or treatment. It updates the information, and the tag holds about enough information to put the Constitution of the United States on the tag.

And it survives E beam sterilization. These have an unexpected life span of about 150 years, and tolerate, exposure to E beam sterilizations.

So, these are very rugged devices that provide portable information management for complex tasks.

Then finally, we're going to talk a little bit about how we use artificial intelligence.

And the machine learning function to help the computer gets smarter.

Every time I joke with people that I know in the banking industry that know of my work in the past. That my boss got so smart that two of them asked to go back to the University on Sabbatical. They're not really quite that smart, but they do get really good at what they do.

I thought I would quickly put this together for each of you as a survival guide. You're welcome to use it. These are my best practices for ensuring success with intelligent automation. I do simultaneous process and technology change out. We talked about that. It's a powerful technique. It will streamline and accelerate your success.

We do that by identifying candidate processes for digital worker augmentation. A process that is highly redundant, typically not very popular with our operators, because it's really labor intensive form filling, key punching. These tasks at best for human beings are 85 to 90% efficient and quality. So we're making lots of defects were forcing human beings to do work that we're not very good at.

and where we should not be surprised when they introduced defects into the process that become time and cost penalties for us downstream.

The way we apply the technology is we create a zero defect process design. We map each process that we want to automate to the task level.

We then highly optimize the process to eliminate all known defect contributors.

We use root cause identification and root cause elimination to eliminate the defect creation. Then, we create a defect free process design that is self correcting, so that the bot looks at its own work, and as a final step verifies, completeness, incorrectness to a particular standard.

Then, I apply same day process prototyping to confirm the success of the new process design. I'd like to get a working team together, all in the same room.

And recently, this last year, we've been doing this virtually, we design a new process, and then, we actually run live cycles of the process to confirm and verify the success the same day.

This reduces change, resistance.

We want to reduce the resistance to change. Change is easy, for anyone that doesn't have to do it. But for the rest of us that do, it's often difficult, because people become very comfortable at their tasks roles in their work, including physicians, we want to make it easy.

And this is a mechanism to do that with them launch the prototype and controlled setting.

And we want to be willing to create multiple generations of digital workers to backfill gaps that are identified during the course go live process. And we don't want to wait until we think we have a perfect bot. Because if we wait that long, the process will change. And we'll have to start over.

Now, we broadly celebrate our successes, because we want to inspire culture, change, and transformation throughout the organization.

I'm going to be presenting, again this year, to the World Health Organization in Paris, France. I was I have been a featured presenter for them in the past. And we're going to be talking about using intelligent automation to transform healthcare and health sciences into a global virtual practice of medicine.

A guide to the medical office for the future. This is coming up in July. If any of you want to participate, I'll get everyone invitations, as you wish.

I began my journey in radio In process automation, in central banking, as the chief architect for the world's central bank to the world's central banks, and the challenge was enormous.

We needed to create a process that was content, language, currency, and orientation agnostic in order to be able to manage transactions. Because some languages, as we know, read, right, to left most Read, left to right, right? to left Chinese. Hebrew and Jewish language is reversed.

And, so, in order to be able to take transactions, financial transactions, from China, Japan, top, to bottom, left, to, right, right, to left, we needed to be language and orientation, nasdaq the bank processes more than $2000 billion a day, It's a staggering number. Think about this $2000 billion a day and requires perfect execution because the bank is the bank of record for all international funds transfers. This translates into about 160,000 transactions a day, and if we divide it up by the number of seconds in a day, it's more than $23 million a second, 24 hours a day, every day, all produced by bots.

Between 170 trading nations that all have unique regulatory constraints and have their own languages 135 plus different languages and more than 100 currencies.

We needed also to design a system that was self clocking. That every 10000th of a second would capture a cycle through the entire process front to back. So we could infer exactly when the transaction request was made, particularly in heavy loading periods when the computers are running at full capacity.

And the transaction may take several seconds because of international currency fluctuations.

Several seconds may make the difference in millions of dollars in transaction value.

So we designed a system through self clocking that manages latency and infers the exact instance within a 10000th of a second when the button was pushed. And the request was made to transfer the funds.

We know exactly when that occurred, no matter how loaded the computer is and how slow it may be running because of demand on the system.

The first digital workers that we designed, I think we produced about 200 bots. And they were managing about 93.6% of the process with zero defects.

But about 6.5%, 6.2%, we're running outside of the capability of the first bots.

And we didn't know why. So we designed a second generation bot to do Gap analysis on what wasn't processing well.

And that's second generation bots, then designed the third generation bots to have 100% coverage.

And right now, we have about 300 bots that are running every day, transacting $2000 billion a day, with a zero defect process with insanely accurate timing, clocking, and Bank of Record transaction management.

This is, this is the most perhaps the most highly regulated single process in the world because it's managing global Will every global financial transaction between trading nations and its it underpins as a foundation? The strength of the global, financial, and economic community.

So it needed to be perfect. And we got it perfect. It wasn't a surprise, then that, as a result of the outcome, in the very beginning of the process. I think I mapped 6000 different process maps across the 172 trading nations in order to capture the uniqueness of all of their processes.

The, oh, the success earned many Global Awards for Engineering Achievement and excellence. It was a tremendous process, just to cut my teeth on, because having achieved this success, almost anything after that was going to be easier.

We then took the lessons learned from the banking application and created a national practice of virtual radiology using IBM Watson.

So the practice would send.

Images, and they could be MRIs cat scans, echocardiograms, biometrics studies, ECG's, ultrasound studies for carotid artery interpretation. All of those images were sent to IBM Watson.

IBM Watson does an initial read and screening, doesn't do the final diagnosis, but does an initial read, and looks for all known anomalies in the image.

The image is then encoded encrypted and sent to physicians, James, on a 50 state basis to the very best physician, the best radiologist, with that particular specialty and history, and the best quality of care and diagnostic accuracy.

So we're giving the most complex images to the very best physicians in practice, no matter where they reside, and this is one of the benefits of the virtual practice of medicine. We're able to connect patients with doctors anywhere in the world in real time.

Within about three tenths of a second, from the time that the image was created to the time, IBM Watson reads to the time, it ends up on the desk of the physician and ends up coming back as a diagnosis, it takes about NaN, So before the patient sits up on the table, we already have a diagnosis from the finest physician in the world, in that specialty for that kind of read.

And it's very pro, It's very powerful as a technique because very often, a radiologist would be looking for a single dif back, and in fact, the patient may have multiple anomalies.

I'll give you a quick example, an older man or woman, often, with women, More than men.

Because of degenerative bone fractures presents at a hospital in Miami with an over rotated right? Shoulder complaining of shoulder pain and tenderness after a fall, The initial diagnosis by the Emergency room physician is additional aspect fracture degenerative disk, dessel aspect fracture of the right clavicle.

The X-ray image is sent to the digital images sent to IBM Watson who reads the image and not only notes the degenerative fracture but that this patient has an enlarged thyroid.

The patient was asymptomatic for thyroid issues, but IBM Watson identified it and sends the read to two different physicians, a radiologist with a specialty, The nation's best radiologists with a specialty in degenerative bone fractures in an aging women who lives in Spokane, Washington and the physician that is the finest physician in the car country for thyroid reads, in geriatric women who lives in San Antonio, Texas. And the diagnoses arrive simultaneously both in NaN. So before the patient gets off the table, the emergency Room physician can meet the patient and say, we confirmed the fracture, we're going to treat you for the fracture.

And oh, by the way, we are concerned about your thyroid powerful technology. There's no reason that this technology wouldn't work on the battlefield.

So we could send images of battlefield injured.

Military personnel to physicians, anywhere around the world that we're safely behind, enemy line, are safely behind our protection on a national basis, wonderful technology.

Downside of this is that of course physicians can only practice medicine where they're licensed and credentialed, and typically they're less licensed and credentialed locally and only in one State.

So, if a patient arrives in my office in New York from New Jersey, I would refer them back to a physician, New Jersey.

I can't practice out of state, unless we license and credential doctors in all 50 states. So, the creation of the virtual practice of medicine identified a brand new problem, which was licensing and credentialing, was taking more than 90 days per state per physician.

So we couldn't get physicians licensed and credentialed soon enough to take advantage of the technique and the technology.

So, we aggregated the licensing content demands for all 50 different states, and designed a robotic application to do form filling through a zero defect process design, as we discussed earlier.

And we now have Digital Workers that identify and retrieve all of the missing information for all of the forms and prepare the applications and the cycle time reduction is breathtaking for more than 90 days for a single physician in a single state to less than nine days for a physician in all 50 States because the the packages are perfect.

They arrive proof, correct? And in the last 750 physician licensing and applications, we've had not a single defect, not a single reject.

The benefit is that the company reduced Locum spend by more than $100 million, because we can put doctors on the ground, in practice.

Practicing medicine in remote locations, in the timeframe that, that is faster than what it used to take us, to find a locum physician, a rental physician, if you will, to back fill the gap, powerful technology, happy to share it, anyone that needs it. I'm happy to share it.

We also did a study, using artificial intelligence on physician care delivery.

We baseline, to about 4500 physicians in over 600 locations, and looked at the average number of patients that were being seen and treated by physicians, and the range was kind of staggering, much broader, than I would have expected from 6 to 42 a day.

one might say, Gosh, now those doctors that are working in only seeing six patients a day must be really good at what they do.

Not so much, The best quality of care and the best outcomes were in the physician group that we're seeing between 36 and 42 patients a day.

In other words, in order to get their practice, to be more efficient in order for them to be able to see patients with less time. They became very good at every procedure, so we characterized how they did what they did, videotape them and transferred them nationally across all the physicians, and increased the physician productivity nationally by 17%. As it is said, a rising tide lifts all ships. We were able to do that.

We also did advanced behavioral analysis studying patient behaviors based on location and demographics, and it's not a coincidence.

that in those demographics where there is consistently low income, patients are often travel challenge.

So we identified arrival times and miss visits by doing a time of day, day of week, day of the month, study, to determine how to best adjust the recommended arrival time, So patients always arrive before their visit.

So, we were able to maintain a full schedule, and take advantage of that, the new physician, efficiency, and operating capability.

And we overbooked the schedule, based upon the dropped patient rates, so that, in each different location, in each different demographic, we overlook the schedule by the day in the very window of time. So if the patient was expected to drop into 230 appointment, that's the one we overbooked. We didn't overbook the whole schedule all day, and if people sitting in the waiting room all day, that's not only badly inefficient, exposes all the patients to coven.

So, we wanted patients to arrive at the perfect moment, And we did it by adjusting the arrival times in overbooking based on behavioral analysis. We increased physician productivity and quality of care by 23% staggering improve.

Then in a global pharmaceutical company, we automated the human tissue donation processing so that the digital workers read the incoming medical histories of all the donors. We identified the acronyms and expressions of symptoms, diseases, and treatment outcomes that would keep us would create a denial environment.

The digital workers then request additional supporting documents and medical history information from the from the the donor processing site, and we maintain statistics on how efficient and the turnaround time was.

These digital workers have human characteristics and send e-mails that are very humanlike in order to inspire the operators, to believe that they're working with people and ensure that they turned around their information in a timely basis. Downside of that is if we've gotten so good at it, that one of my doctors asked one of my bots out on a date. It was a very awkward moment to have to explain that the bot was not going to like their favorite food or be able to enjoy their favorite movie.

The medical histories, then are with all the supporting documents are annotated for final review by a physician, and even the structure of the content of the document. Imagine a medical history that arrives with a thousand pages, the computer re stacks the document for ease of reading and for ease of use.

Then, finally, we installed Machine Vision to characterize human skin.

And the machine vision looks for subcutaneous effects, things like skier's, stretch marks, plum, meshes tattoos, even things that are not visible to the naked eye.

And uses a highly optimized area utilization software package that was developed by Amazon for Carbon Packing and provides cut cutting pattern optimization. So we optimize the best use of the human tissue, and we resulted and delivered a 23% improvement in production yield loss reduction.

The site was awarded the Chief Executive Officers Award for engineering achievement among the 30 sites globally in this large pharmaceutical company, top five pharmaceutical company.

This operation that we re-engineered received the Global CEO Award for Engineering Cheap.

So what are the secrets?

How do we ensure your success?

How can we make sure that if these technologies have relevance in your medical practice and for your business, for your bank, for your insurance company, for your automated revenue cycle?

They called management. We're also using bots to do RCM in 10 operating centers around the country. How do we use bots in a successful way, and how can I ensure your success?

First, seek someone that's done it before. Seek someone with a track record. That is well documented, well known, and with suppliers that have a legacy of success in that particular industry, in your industry and even in your specialty.

Just because someone is a world-class bhat provider in the financial community doesn't mean we want them to touch and read medical histories. It's a completely different application, requires different technology, and it's not a crossover, It's not an easy part, or a short distance from RPA, managing and executing financial transactions to getting the system to operate efficiently managing medical histories. They're completely different outcomes.

Second, believe in yourself and in your team.

Think about what your team and your patients and your practice needs, and what they would best benefit from.

And believe in yourself, believe that you can make the change, believe that you are in this journey to success, and that your team is going to deliver it.

They know if you believe in them, they know when you trust them, they know when you are behind them, Also know if you're not.

So you need to be very collaborative and collegial in your approach and inspire and encourage people to participate openly because the defects that we find early and prompt in the process are less expensive by a factor of 100 to 1.

Then, after they're hard coded into a robotic process or an automated process, I believe, with great compassion, that there is one race.

The human Race.

And if coven has taught us anything about the world, it's that we are all vulnerable. We are all susceptible. None is perfect. There's not a perfect person among us.

And we all worry about our children and our future.

And if we can share the joys of our lives, share what empowers us.

We have nothing but success to look forward to, because really life is a team sport.

And we're all on the same team.

If I am remembered for anything I want to be remembered, as someone that was a collaborator, someone that joyfully gave away everything he learned new in order to inspire and help others on their life's journey, because God knows.

I can't share, and I can't tell you.

And I can't count the number of times that the people that have been my mentors lead, and pick me up.

So with that, I hope that the discussion has been interesting today has been collaborative, collegial and I'm, I'm open to any questions.

Can see. Do we have any questions from the audience?

Yes, we do. So I want to remind the audience that we will, Don is not a video right now because we want to preserve the audio broadcast quality. And as such, I'm not going to bring up my video either at this time done well. Maybe I should let me, let me just be here on video and so that people can see me.

And, uh, so a number of questions that have come up as I scan through here. And the, one of, the, the, the themes that have emerged has to do with your work, with RPA.

Really, even before RPA was understood by most any industry, the, the RPA, you know, in, you know, applications, have not been around for too long, and. And you have been the very beginning of that journey. So, by the way. Lots of thank you, Dawn, for sharing expertise and wisdom with us, I mean, deep knowledge, and experience on, on bringing technology to this fields.

So going back to the RPA Coleman, How, how was it, Dawn, to go from, you know, really kind of being a test pilots for RPA technology and implementing the swing? And the hollow will go to just start, and how much has it improved since you first started working with RPA.

Gosh, that's a great question.

I was the Enterprise Transformation Officer at General Electric.

Worked for Jack Welch, going all the way that far back. And we did a lot of very complex, multiple variable design of experiments using an exotic statistical technique called response surface analysis, because we optimize the thrust of an aircraft engine in real time, based upon fuel consumption, Altitude, pressure density, humidity, RPN engine RPM, angle of attack.

Literally, 75 variables, and we need to manipulate them all in real time.

So, we design the computing solution to encompass the broadest possible variables, and then through multiple variable design of experiments, determine the ones that are most critical that we need to manage.

So we started sort of using industrial characterization and very exotic analytics in industrial characterization.

I own the copyrights for the image generation for GE MRI Machine and their cat scanners. I worked on the patient coil for the MRI machine.

So I've done some pretty exotic product design.

But then went over to banking. Went literally from General Electric to being the first transformation officer, ever hired by JP morgan Chase Bank and worked for Jamie Diamond. And in every step, what was interesting to me, it shows a and I thank you for asking the question, is that, in every step, the lessons learned were highly applicable.

So the lessons that we learned in complex, multiple variable design of experiments and response surface analysis generated a technique called fractal basin boundary analysis that we applied in every ATM transaction.

So when you stuff your credit card into an ATM machine, it does a deep analysis looking for one anomaly in a billion transactions. It's a subatomic particle, analytical technique, so that we can scrub out terrorism. So with it, we're not funding terrorists, it's scrubs out.

Your card against everyone on the non .... So, it's these are very, very exotic techniques. And the beauty of it is that once we developed and learned how to apply them, then getting to the next level, to design the global banking system was relatively fundamental.

And to get back to health care, because I started there, I managed emergency medicine for four years. We're seeing 200 patients a day, right?

Um, it was a wonderful and miraculous journey For me, it gave me a tremendous opportunity to build and re-use the tools and methods. And it turns out that they are highly re-usable.

I think what is different is that the application is unique.

But we built the tools and technology over time and kept expanding their capability.

Great question, by the way, Very well.

And, and on, on the, on the, you know, you have clearly, experimented and worked with so many different technologies in your, in your career in across multiple industries.

What is the process that you go through to separate the technologists? There are ready for prime time anchor value creation versus the one. There are just overhyped and the sound good but really when you when you try to make them work for to create value. There are too many barriers and they're not ready yet. How do you go for that process to separate because you have worked with a lot of leading edge technologies. And honestly, that, that's, there's a lot of risk with that, because a lot of the things that people talk about are just not ready. And the, and I'm curious about the, if the process that you follow to be able to separate, you know, the hype from reality.

Absolutely. Great question.

Couple of things. one, I stay very active as you may know, and I've been a constant supporter of vetoes.

I love these events.

I participate actively because no matter what I give away, probably if I give away everything I ever learned in this conference, I will leave knowing more about different things than what I brought to the event.

So one of the beauties of participating in these events is that I get real-time access to the leading edge of the technology and who's actually using it and successful with it. It's a powerful tool and technique.

Second, I do look at commercialization, impacts. And when the sales team comes and brings their, their exciting demonstration, I ask to see it. I say is there, and do what? Can I sign an NDA, a non disclosure agreement? I want to go touch it. I want to go see it. I want to see where it's actually installed and delivered.

And, that way, I get a much better, real-time understanding. Then, finally, I am a multiple patent holder for all kinds of things. The compact fluorescent lamp that looks like a helix is one of my pets. I have three patents and everyone every compact fluorescent light. So I understand the patent process, and the conversion from ideation.

To value delivery And the journey is long. You said it. Well.

Technologies that are not yet ready for prime time may be in the development phase, Um, awaiting commercialization and not yet ready for prime time. And the investment to make that one work is 100 times more expensive than to be a fast follower and take advantage of it when it does really go live.

And one of the things that I do to do that I am the Chief Transformation Officer for the world's largest academic research organization called the Academic Technology Partners headquartered out of Toronto, Canada. And we actively monitor the research on the top one thousand universities around the world. And correlate all of the byproducts of their research to see if there are common themes and threads that are emerging, which direction they're taking, and whether or not we want to jump aboard and provide some funding to take them over the finish line and commercialize them. So I, I have a privileged perspective as a hands-on user.

And someone that shares everything that I know through beto's and other organizations.

But, at the same time, I'm also a developer, and very active in that community as the Chief Transformation Officer for the largest academic research organization in the world.

I'm sorry, I'd just say I can't hear you. Or You unmute.

Yeah. I was on mute. My microphone was muted. So, yeah, I said, thank you, Dawn, for for that perspective.

And then I follow up by saying that you have been involved with artificial intelligence, intelligence development through the maturity of the technology, which continues to evolve as we know. And all the way back to when IBM has started playing with Watson and all the different Watson applications that took place to where we are today with deep learning and further neural network. The deployments and more sophisticated algorithms that we continue to developed. And I know that you have done some work with the with the ... 90 and with the coronavirus pandemic, by using Artificial intelligence in the analysis, the analysis of the coronavirus. I was here, I was I was curious if you could share some of what maybe what you have learned and found on doing the research and doing that work with AI on the coronavirus pandemic.

Absolutely.

one of the things that is fascinating to me is that if we look at the CDC produced numbers on morbidity and we look at the expression that within the country, 400,000 people died of .... It's it's possible that 400,000 people died, that had corvid, but they may not have died of ....

Because if we look year over year, on average, about 20,000 Americans have died over the previous year, right? So we take last year's mortality, and 20,000 that is the expected mortality for the following year, if there are no other perturbations in the system.

This year, only 50,000 people died more than what we would have expected without coronavirus.

So that means that either 350,000 patients were expected to live forever, which is not likely.

Or we have rolled over 350,000 patients with comorbidities that were likely to pass.

And because in their final moments, quad core ovid, we assigned colvin as a final outcome.

So one of the things that we're learning is that for sadly, those people that are exposed to ... that are vulnerable to ..., it is a life-threatening disease, make no doubt about it. I lost two family members.

Both were highly decorated Marines, one of whom was interred at Arlington Cemetery for his military contribution.

So it comes with great pain that I did, that it's very intimate, the experience is intimate to me, But I, but I think what we have learned is that the morbidity of the disease is both less invasive than what we thought.

It's running about a 10th, two tenths of a percent morbidity and and it probably isn't, 400,000 Americans have died of unique ... disease.

They may have comorbidities and there might have been other issues, and we did use artificial intelligence during the screening process says, using RNA blocking and using CRISPR, gene editing technology.

My daughter is graduating on May the second from Brown University with highest honors. And her thesis was on CRISPR gene editing to solve for Alzheimer's disease.

So we're learning so much using the computer, using AI as a screening tool for these CRISPR experiments.

We can do multiple variable design of experiments and you do multiple knockouts at the same time and look at the end effects. It's very powerful technology and I expect we're going to know so much more. Well, we will learn more about the human being and its behavior in the next three years than we have since the beginning of time.

It's that powerful.

That's, that's, that's a great insight, and that's a great message, and something to look forward to, than the pin, as the technology, and our understanding.

Based on this technologists, continue to increase. Don, Thank you so much for taking the time to share your expertise of our global audience today. It's always a pleasure to have you with us. You have cross industry, domain and expertise, and we appreciate your leadership and we appreciate you sharing that with all of us.

It's my pleasure.

It's a great honor to be here today, thank you, because it shows A and I appreciate so much your wonderful leadership and Your guidance as well. You've been a really bright shining light in the community and in the industry. Thank you for your great leadership.

Thank you, I'm humbled and honored by that, especially coming from you. So thank you very much.

Ladies and gentlemen, this concludes Day two of the Beatles Healthcare Live. So let me give you a preview of what's come. Tomorrow, our last day together on Beatles healthcare life. We're gonna kick off the day with ..., who is the lead Performance Improvement Advisor at the University of Pennsylvania Hospital. So, she's going to talk about process improvement and change on the end, the University of Pennsylvania Hospital, and how they have continue their transformation in the way that they they design and really operate the hospital.

We're going to follow that up with a session on a high power, digital transformation in healthcare, directly from Toronto Canada. one del leader, who is an AI expert and data analytics leader that is focused on the health care industry, belong, is going to share with us tremendous market data and research related to AI in the **** in healthcare. And, and very practical applications of, of the of the technology that are taking place today, not some vision of the future. It's happening today. And how health care is really leveraging these AI tools and technology to create the most value to have the greatest patient benefit possible. After that, we will welcome Matt Thibadeau maximal, though, is the Director of Business Efficiency for Big Blue Cross Blue Shield Michigan.

And Matt's going to talk about value malnourishment.

Lots of people talk about transformation, Very few people can actually show the value that's being created by their transformation. So, he's going to have a focus on how do you identify, create, and report on the value of your transformations?

So, he's gonna go deep into the, into the, into value creation as a result of business transformation and the, and the, and what the results look like for, for an organization like Blue Cross Blue Shield of Michigan in their own transformation journey.

And then we're gonna wrap up the day, and we're gonna wrap up the conference with our wonderful presentation from Marcus Paganini, who is the Vice President of Global Manufacturing Strategy and Deployment at Johnson and Johnson. So Johnson and Johnson has been incredibly busy with the production of the culvert vaccine. And the certainly the last 18 months or so have been have been very critical for the organization as it ramped up many of its capabilities to develop a vaccine to develop the manufacturing to deploy the vaccine, But also all the other operations that J&J has in place that we still go on no independently of vaccine product design and production. So, Marcus is going to tell us about this path towards smart operations that they're using at Johnson and Johnson. It's really a combination of operational excellence with Industry four.

What does it look like for a leading organization like Johnson and Johnson, when they are building this connection between operational excellence and industry four point at all.

So, great presentations tomorrow, I hope that you enjoy the presentations today. Please, comment, share, like ask questions to our speakers. Use the LinkedIn, the connection that we have, post conference. You can look, my name is Joseph ..., I have the post in there, you see lots of comments. I'm providing updates on that page as well. So, if feel free to continue the conversation, ask questions, interact. Comet. Support our sponsors by saying, like, and support because none of this would happen without our sponsors.

And, of course, our speakers who who are so generous in sharing their expertise and time from all over the world we had we had speakers from Chicago all the way to Kuala Lumpur, Malaysia today. And tomorrow, we expect another global, not only audience, but a global list of speakers who are going to be with us. So support them. And thank you again for taking the time to be with us, and we look forward to seeing you today, tomorrow. Have a great rest of your day, wherever you are in the world. Thank you.