A Conversation with Ed Hammond

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In the past year with COVID we’ve all seen how important it is to have reliable data in order to make informed healthcare decisions. How do you think this experience will change healthcare informatics and analytics in the future?

One of the things that COVID has taught us is how inadequate our systems are to meet the requirements of a pandemic, including just the exchange of information. So what we are learning are the facts that we don’t speak the same language, we don’t collect the same data for the same things, we don’t have connectivity, we don’t understand the governance that’s required for doing that, and we don’t have a clear cut set of privacy rules that permit us to do what we have to do. So I think the significance of COVID is the fact that it really taught us the inadequacy of the present systems.

“I think the significance of COVID is the fact that it really taught us the inadequacy of the present systems.”

What COVID-related research would you like to see done in the future?

I think that we don’t know the long-term impact of COVID. We need to find a way to monitor people that have had COVID for the next 20 or more years, because some of these results are going to be hidden for a long period of time. We need to establish the tests to perform and the data we need to collect to monitor basically each of the organ systems of the body. Creating that long-term database and  tracking people across their movements over the next 20 years is challenging, but a very critical part of what we will be doing.

The other thing is that we have begun to live in a virtual society in many ways. The fact that we’re zooming now, instead of meeting face-to-face, is an example of that. I spend probably 60 to 80% of my work day zooming with somebody. What we’ve learned is that it is more time efficient in some ways, because I don’t have the travel time and I don’t have the cost associated with flying and hotel and everything else. So there’s some positive that’s coming out of that. How we will define the future by doing some things virtually, some things face-to-face, is going to be one of the challenges.

One of the things we need to do is recognize that there are huge demands for tracking more than simple clinical data. Even where we are now with the vaccinations, the distribution and the administering of the vaccine is unbelievably bad. We need to have the standards and the systems and the processes in place for a more simple and efficient operation. So there are lots of impacts with COVID that need to be changed and I think we need research on what those need to be, how we manage to track everything, know where it is, nothing gets lost, and it gets appropriately applied.

The Duke MMCi program celebrated its 10th anniversary in September 2020. Health informatics changed so much in the past ten years. How did the MMCi program evolve over that time period?

First of all, informatics has evolved in that 10-year period. The technology changed tremendously. The biggest value of the MMCi program over those 10 years is really teaching the end-user, the people that are going to use informatics in their work. I think the MMCi program has done an outstanding job of teaching. The challenge, actually, is not so much understanding the technology that you’re using, but to really understand new and effective and really required ways of using that new technology, that new knowledge, that new process and procedures, to make what you do daily much, much better. The MMCi program has evolved over time, as have some of the requirements and systems and everything else. It’s a mixture of people that makes them be better professionals in whatever it is that they’re doing.

For young people just entering college, what undergraduate majors or minors do you recommend as the best foundation for the MMCi degree?

My answer will obviously be biased. I’ve always thought that Engineering is probably the best foundation for almost anything. The way we approach problems, you define a problem and you put forth a solution and you see if it’s worse, so you have feedback on what you’re doing. I think that’s a great way of approaching almost every problem I’ve ever encountered. But in some ways it doesn’t matter because what you learn today is not necessarily what you will use tomorrow. I think the message is learning has to be a continuous process. If I go back and think about what I was taught in my undergraduate degree in Engineering at Duke, and even in my graduate degree in Engineering at Duke, I started out learning about vacuum tubes. These are something the current generations have probably never seen. Everything continues to evolve, and learning has to go with it. Now I’m having to worry about genetics, I’m having to worry about data science, I’m having to worry about analytics, I’m having to worry about policy and regulations. You really have to recognize you need to learn what you need to know for what you’re currently doing. So it’s a continuous process. The biggest thing that you get out of undergraduate work, for example, is the ability of learning how to learn.

“Learning has to be a continuous process.”

Over your career, you’ve seen great growth in the use of information technology and informatics in healthcare. What progress still needs to be made for IT and informatics to reach their full potential to improve healthcare?

There are a number of problems that have existed for many years. I mean, if I look at my career, I go back in the late eighties, early nineties, and things I was trying to solve that still are unsolved. We find it easier to do work arounds a problem rather than facing the problem. The reason we do that is it’s easier to do a work around than it is to confront the problem itself because when you confront the problem, there are more factors involved than just the problem itself. It’s the bureaucracy, it’s the architecture, it’s change. All of those things are factors. So that’s really the biggest issue that needs to be addressed,  learning how to solve a problem that you know exists and you know the solution, but don’t have the energy to confront the system. It has to change. We assume the world as it is, is the world that it has to be. We need to change that philosophy. 

Is interoperability one of the problems you were dealing with in the nineties?

Interoperability is something that I wrote about even in the seventies. It used to be that when I talked about interoperability, it was being able to plug something into the wall. My joke was when I travel around the world, I have to have 10 or 12 different plugins to accommodate all the different plugs. And for me, interoperability was one plug that would fit everywhere. But then I began to understand that it was more than just the functional, technical aspect of this, but it was also the semantic aspect. When you say something I may misunderstand, I may hear the word, but I may not understand what word you’re meaning. So those are fundamental problems that we really haven’t been able to solve. What we really need to do is understand that we need to bring more and more people into the solution.

In healthcare, for example, we talk about clinical data. I spent most of my life trying to collect clinical data, but now we’re reading reports that suggest clinical data is only about 10% of what’s important for the quality and length of life of a person. It has to do with behavior. It has to do with the social aspect. It has to do with where you live, your environment, how much money you make.

One of the things that’s important, and the MMCi program attempts to address this in some ways, is the impact. I mean, how do you accommodate the diversity that exists, the disparities? One of the things that the COVID pandemic has driven us to is digital health. Yet digital health requires access to the internet and access to devices that we use on the internet and access to some degree of health literacy so we can understand what we’re seeing. Those are all factors that need to be considered in the future. And what is the proper balance? Do we have total equality? I think that’s totally impossible, but what do we set as the bar for the bottom? How do we accommodate the transition through the different stages? Those are issues that are extremely important now that we’ve become very sensitive to race and economics.

One of the things we haven’t talked about is the role of robots and computers. I don’t know if you’ve seen the Boston Dynamics’ latest dancing robots. It’s the latest thing going around now and it’s fantastic. Yet what you need to recognize is there are huge other applications of that. I was amazed purely by the balance. So if I can learn how those algorithms create the balance in the robots doing the dancing, how do I apply that to humans? I have an increasing number of friends that are getting older as I am, and are finding balance is a huge problem. I’ve had several friends who’ve had major falls, some of them resulting in death over the last three or four years. We need to begin to understand by using what is happening in the analogy of the robots and the balance that they’ve got, how do we apply that to humans? Is it educational? Is it vision? Is it hearing? We need to understand that better and there’s lots of research we had done about that, but I think technology is going to really help us move ahead with this problem.

Besides AI and robotics, what other technologies do you see that will really transform healthcare in the next 20 years?

It’s fun to consider that, and I’ve always been a person that really looks ahead at the future. Clearly digital health is here to stay, and we need to recognize that we have a global world. My comment is if you look at the earth from outer space, you don’t see the boundaries between countries. I think that’s the vision that we have to have for the future of healthcare, where we understand the mobility of people and clearly the COVID pandemic was a consequence of travel between countries. So we need some way of knowing that. We’re finding, for example, the airline industries are suggesting that you will need to have proof of vaccination before you get on an airplane. We’re going to see that kind of thing, which makes these become global problems. It’s not a single country, but every country that an airline flies to, which is most countries, they’re going to have to be able to accommodate it. So there needs to be global standards for doing that.

Digital health really implies computers and analytics, and we’re just now beginning to appreciate the value of data. If we knew everything about everybody in the world in a single database, we could extract so much knowledge to significantly improve the quality of life for everybody. We would at least know what to do. If we were smart enough to do what we know how to do. So I think that’s going to be the future. We’re going to see registries.

We’re going to see rare disease become less rare because everybody in the world with that particular disease is going to be part of a database and we’re going to learn from it. We still need to learn more about COVID. We still don’t understand COVID. We’ve got the variants that are happening now. We need to do research on that. So if I had a connected network of everybody in the world, then those questions are going to be quickly and easily answered of knowing what’s happening and being able to track those changes over time, both in terms of the migration of the disease, the evolution of the disease, the treatments, and the impact of that.

So computers are much better than humans. We make decisions on very few data points. We now have hundreds of thousands of data points, and how do we use them? Humans cannot, computers can. I think that’s what the future is going to be, computers doing the analytics, but we aren’t getting rid of humans. The truth is that computers find it very difficult to deal with unexpected events and humans do an amazing job of dealing with unexpected events. Whether that’s experience, whether that’s history, whether that’s genetics, whatever that turns out to be, we haven’t really learned how to put that into a computer. So for me, the future partnership is going to be computers and humans, but the roles of both are going to change significantly.

You’ve had a long and successful career, and you really are very inspiring to so many people. What advice do you have for the rest of us to be more like you?

Well, my advice is get to be as old as me. Being old is not a bad thing, it’s a great thing! I don’t have to hide my age simply because I think I’m still functional, I still have new ideas, I still have great visions, and I don’t want to give up on those. I want to encourage other people to do that. So the big thing is to stay active, take care of yourself, lots of exercise, enjoy life, don’t panic, and do what you really want to do.

“Being old is not a bad thing, it’s a great thing! I don’t have to hide my age simply because I think I’m still functional, I still have new ideas, I still have great visions, and I don’t want to give up on those. I want to encourage other people to do that. So the big thing is to stay active, take care of yourself, lots of exercise, enjoy life, don’t panic, and do what you really want to do.”

It seems like you’re always learning, you’re always aware of the latest things. You have a really active mind and curiosity, and that probably keeps you young too?

Yeah. And you know, I’ve never seen anything I didn’t like, and I never see anything that doesn’t have some relation to something else. For example, watching the robots dance, everybody was talking about the dancing. For me, what it inspired is saying, “Geez, if they can balance those robots on one leg hopping around, they ought to be able to figure out how to do something good for humans.” So I really believe everything is connected to everything. I’ve been lucky enough to have the vision of looking at something and seeing how to apply that. In my early career, Don Lindbergh visited Duke and looked at what we were doing. He said, “What I like best about what Ed Hammond is doing is he hasn’t come up with as many new things as anybody else. What he’s done is put together things that other people have done to make it more effective as a system.” That’s what I’ve really done with much of my career. I see things that people are doing and try to put them together. I still do that. I try to put groups together. I try to put countries together. I try to keep technology together. All of those sorts of things are a contribution that I hope I’m making to the field. And I encourage people to look for that approach.

“I see things that people are doing and try to put them together…. I try to put groups together. I try to put countries together. I try to keep technology together. All of those sorts of things are a contribution that I hope I’m making to the field. And I encourage people to look for that approach.”

That’s great advice and I’m sure the students in the MMCi program are inspired by you.

Well, the truth is, and I really mean this, I continually learn from my own students. I have very many examples of people that are teaching me things because they approach things differently than I do. What they grew up with was different than what I grew up with. So their philosophy is a little bit different. Their approach is a little bit different, and I think that’s extremely important for me to listen. So I love arguments. I think debate is the best form of moving ahead with new ideas, because I want different thoughts. I want people pushing back on some things, expanding on some things. So I continually learn, and I’m delighted to be in an atmosphere, a university, where the opportunity of continual learning is available to me. And I love students. I love to have conversations with students. My door is always open. The MMCi people that are interested in applying, people that are in MMCi, and people that have graduated from MMCi will always find my door open.

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