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Optum analytics and tech innovators

Meet the people behind connecting tech and health.

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The health care experience edge

Our leaders, clinicians, engineers and data scientists at Optum have seen a lot over the years, and they’ve been embedded in all parts of the health system. 

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- I've been in the healthcare industry nearly 30 years.

- About 15 years.

- 22 years.

- Well over about 34 years now.

- About 24 years.

- Over the last 20 years, healthcare has changed in a number of ways.

- I think back to the 1840s, when long before we had germ theory or a real understanding of diseases, put to one in 10 women would die in childbirth. An obstetrician in Vienna by the name of Dr. Ignaz Semmelwise started to figure out that often times it was the physician themselves by not washing their hands in between patient examinations that were actually spreading the disease. By instituting just a simple hand washing procedure, he was able to take those mortality rates down below 1%, a rate that we wouldn't see again until modern times. Now sadly, because this was so heretical to the leading medical authorities understanding of how diseases worked, all of his work ended up mostly being rejected and ridiculed by the leading authorities of the day.

- I grew up in the non-digital world of medicine. I grew up when there was what seemingly was only a few medications, and even remember a professor telling me if you just had one medicine for every disease category you would do fine in your career and it would hold you throughout. Well, that proved to be very wrong.

- Some of the weirdest things that we went through back in those days, we weren't using leeches or anything like that, but we did have people that were way behind on charting and paper charts. I had a physician who stored those charts up in the ceiling because he wasn't finishing the charts.

- One of the strangest things I can't imagine doing today is paying claims by hand with just paper.

- Clinical documentation was hand writing on forms, hand writing on paper.

- When I got into this market faxes were a big thing.

- There was paper everywhere.

- We killed a lot of trees.

- Paper forms, getting faxes. For years when I visited my doctor she had these piles and piles of paper. There was no electronic medical record. There was minimal use of computers.

- Back in the day, in the early days of my career, you used to see pharmacists walking through the hallways with crates of paper information. They would take these things home, these crates of paper home, they would go through them manually just to be able to find a piece of information or a clinical judgment.

- Historically, there used to be a ton of manual paper that you had to do with everything, and today a lot of that has been automated. But I actually reflect and think more about when I was a kid. And so if you had a tummy ache or you had a leg ache, you only had two choices. One was you could go look through your encyclopedias and actually dig into and understand what you could actually go find about yourself, or two you could call a doctor. If you compare that to where we are today in terms of the access to information, whether it's Google or a virtual nurse, or health apps, it's just remarkable in terms of how that's automated and simplified the processes.

- For those of us that live in the analytic space, it's actually been a frustrating career, to be honest. We have to go around and sleuth to find access to data in 27 different places. The data don't always connect, and so spent half of our time just trying to connect different sources. One of our analytics leaders said every single project is like trying to go through the forest with a machete. That you're trying to connect into systems that we haven't had before, and bring data together in new ways.

- In no other industry do you not know what you're gonna pay for a service when you consume it. Back in the old days we had a pay and chase model where a member would see a provider for a given service, the provider would submit a claim for payment from the health plan, the health plan would pay that claim. We would receive claims, and months, if not a year later, we'd evaluate whether that claim was accurate for members and providers and health plans alike.

- I think part of our focus is around how to make healthcare delivery and revenue cycle more efficient. And, you know, with the adoption of new technologies that ability to be able to make some of the things that in the past were totally manual, like medical coding, clinical documentation review, quality review, all those things depended upon review of medical records, that at that time were all on paper.

- The rule of analytics and data in the Medicaid markets, fees for service markets, as well as managed care markets, is really kind of a very interesting juncture point right now. If you think about data and you think about states, most of them are operating for very legacy systems. And the challenges with that is the way states are set up they're set up by departments. And as they're set up by departments you basically get silos of information.

- I've worked in the finance industry, I've worked in the transportation industry, I've worked in the retail industry, and they've got some pretty serious problems, but none of those problems have the weight and magnitude of the healthcare industry.

- I'm involved with the military and veterans. And veterans now have a suicide rate that's 73% higher in the 18 to 34 year old than a none veteran. The ability to take all the information, clinical information, as well as social determinant of health, and be able to do predictive analysis on who is at risk for suicide is gonna be a very huge break through.

- A big space that I work in is called medical behavioral integration. This is really kind of the holy grail in behavioral health, just figuring out when a member has both co-morbid medical and behavioral conditions, how do you coordinate and align that care to get the best possible clinical outcomes, and ultimately the lowest possible cost?

- It was very different way back when for providers, physicians, as they were delivering care. They were blind to the information. Their patient could have been seeing multiple different doctors, benign prescribed multiple different types of medications, and yet they didn't have that information to be able to understand is there a contra-indication or is there a, you know, duplication of therapy?

- We all have microwave ovens in our home, and interestingly enough we all expect microwave ovens to work 100% of the time. In other words, you put something in to reheat, it's going to reheat. How many times have you heard somebody say oh my microwave only works 50% of the time, but it's okay? Why can't we apply that to medication? Why is it that when you're given a medication, why shouldn't it work?

- One of the trends, one of the fuels, the engine of change, is the fact that we have three worlds that are emerging, that are coming together, that are being fused. Those three worlds are a world of systems that you and I and others help build, whether those are apps that we have on our mobile devices, whether they're back office systems like claims. We also have a social world where you and I are becoming more connected because of our social networks. And then we have the physical world, which is becoming more instrumented. When you put these three things together the opportunity for healthcare is enormous.

- When I think about healthcare there are a number of areas of business process that used to be very, very manual. And so with new capabilities like OCR, optical character recognition, and NLP, natural language processing, we have new ways of increasing speed and efficiency in healthcare by digitizing those documents and applying analytics to find patterns in medical records and other sort of non-structured data.

- I think if you bring together technology data analytics you're able to provide an ecosystem of how to provide care for a patient that you haven't been able to in the past. And it also brings together providers and payers and life science companies in a way that you haven't been able to in the past.

- It's the combination of data from different sources, leveraging analytics to bring a composite view of an individual that really now allows us to fine tune, if you would, how we deliver the right information in a coordinated fashion about an individual.

- Think of it as an information tapestry. We're continuing to weave in additional types of data into that tapestry so we can get something that's much more robust.

- But we gotta find a way to make that data usable to that community. Usable in a way that they don't have to decipher the noise, and instead understand the real signals that effect patients health. If you think about what you can do with all these different data sets, it's the next level of insight that you can learn about a population or a patient that you haven't been able to with other data sets. So for example if you think about claims data, that gives you a historical perspective on what happened with a specific member. Now if you link that together with social determinate data or other external data, genomic data for example, about a specific patient or member, that gives you a view into that patient that expands from just historical into current state, into what do you actually know about the genome of that individual. And then you can build an algorhithim or a model that helps you predict what could potentially happen with that individual under certain circumstances.

- Today, with artificial intelligence, with this general purpose technology, the sky is almost the limit in what we can do.

- Machine learning and artificial intelligence are forms of analytics that can really help to streamline the overall healthcare system. It's really about the scalability of the information and gathering the insights that we have and embedding it within our operational processes so that we can continue to derive the best clinical outcomes for the people that we are actually focused on.

- The administration of healthcare is really buried inside unstructured data. Clinical notes, medical records, contracts between payers and providers, language that determines what benefits individual members will get are all in forms of unstructured data. So our ability to use advanced data and analytics, things like natural language processing and information extraction allow us to take that previously untapped set of information and make it actual.

- If we can look at the path of these patients with our data and analytics to be able to know where is the best place to intervene before we get a bad outcome, that to me would be a phenomenal advancement.

- We still have this enormous highway ahead of us, this road ahead of us to do automation. We can do that with just a variety of technologies that are available today, whether it's artificial intelligence, whether it's genomics, whether it's block chain, whether it's ambient. There's just a number of technologies that enable us to not only take cost out of the system, but actually technologies that help with aging at home, technologies that help people live healthier lives.

- Artificial intelligence, machine learning, deep learning, all of that's gonna make this move at a much faster rate. As we take care of more people and we have less and less physicians and even extenders, we have to be able to know what to do faster and get it done to keep the patient healthy.

- We're really blessed today that we've got the ability to manipulate, analyze and assess so much more data. And then to apply tools like artificial intelligence and machine learning so that's not a PhD spending decades trying to study this data set, instead it's a type of thing that you can set a computer that's not gonna sweat on the problem.

- Each of us is really in some sense a big data story. And leveraging technology like AI to fully capture the information and then integrate it into kind of healthcare delivery, and making sure that that care is effective for each individual patient I think is a big part of the future.

- The exciting thing about data and technology is that it's gonna allow us to do things that we've never been able to do before. So predicting claim payment inaccuracies, predicting the change of eligibility with providers to speed up manual processes, to better predict patients who are going to have an adverse event, or who have the onset of a condition.

- That's what's beautiful about healthcare, it's evolving every day, right? And we should never lose sight of the simple fact that healthcare is actually hands on hands. Healthcare is very specific. It's not a population based approach. So I'm excited about the approaches where we haven't lost sight of the fact that these are not populations, but these are individuals.

- One of the things that we're on the verge of doing with data and analytics is value based care. I think there's gonna be a rapid change from fee for service to doing things that are of value, to make quality and outcomes the currency.

- When I think about the opportunity to use technology in a novel way, an opportunity to actually make a societal impact, there's no greater opportunity than the healthcare industry. And I see tremendous upside in just how we can apply technology to make the future simply awesome.

- We have all this technology. We have all these millions and millions of records that we can analyze. We have artificial intelligence. We have predictive modeling. But we still can't forget one thing. We still can't forget the patient.

- The people in healthcare have changed. It used to be, at least from what I saw, people doing data entry. It's then evolved to technologists to be able to build systems to capture data. Now we're at the cusp of the analytic front. How do we have people interpret all of that reams of data? Guide it, find the insights, and then start to deliver it? The thing that excites me the most is the more information and insights that we can pull together. We can help one person live a healthier life, or live the best life that they can. And then repeat it eight billion times.

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A FEW OF OUR ANALYTICS AND TECH INNOVATORS

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Sanji Fernando

Sanji Fernando

SVP AI and Analytics Platforms, Optum Enterprise Analytics

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John Fillman, Innovation Lead

John Fillman

Innovation Lead

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Thomas Gilbertson, Innovation Lead

Thomas Gilbertson

Innovation Lead

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Steve Griffiths, PhD

Steve Griffiths, PhD, MS

SVP and COO, Optum Enterprise Analytics

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Rick Hamilton, Senior Distinguished Engineer

Rick Hamilton

Senior Distinguished Engineer

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Kerrie Holley, SVP and Technology Fellow

Kerrie Holley

SVP and Technology Fellow

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Mike Jacobs,Technology Fellow and SVP of Engineering

Mike Jacobs

Technology Fellow and SVP of Engineering

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John Kontor, MD

John Kontor, MD

SVP Technology, Optum Advisory Services

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Jess Lewis

Jess Lewis

VP of Innovation and R&D 

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Andrea Marks

Andrea Marks

Chief Analytics Officer, OptumRx

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Dan McCreary, Distinguished Engineer

Dan McCreary

Distinguished Engineer

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Tushar Mehrotra

Tushar Mehrotra

SVP Analytics, Optum Advisory Services

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Andy Merrill

Andy Merrill

Vice President, Optum Payment Integrity R&D

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Mark Morsch

Mark Morsch

VP of Technology, Optum360

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Ravi Narasimhan, Innovation Lead

Ravi Narasimhan

Innovation Lead

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Paul Nielsen

Paul Nielsen

VP, Advanced Technology Collaborative

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Eric Rock

Eric Rock

Founder and CEO of Vivify Health

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Brian Solow, MD

Brian Solow, MD

Chief Medical Officer, Optum Analytics

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Tom Sullivan, Innovation Lead

Thomas Sullivan

Innovation Lead

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Mouli Venkatesan

Mouli Venkatesan 

Senior Vice President and Chief Information Officer 

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Matt Versaggi, Distinguished Engineer

Matt Versaggi

Distinguished Engineer

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Julie Zhu, Distinguished Engineer

Julie Zhu

Distinguished Engineer

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