Welcome to Connecting ALS. This week we discuss how data is helping make ALS a livable disease and pointing the way to treatments and cures.
What is Connecting ALS?
Connecting ALS is a weekly podcast produced by The ALS Association in partnership with CitizenRacecar. We aim to discuss research and technology developments, highlight advocacy efforts, and share the personal stories woven through the community.
This transcript was exported on Oct 12, 2022 - view latest version here.
Pam Knott: Not just using a spreadsheet of data, but using systems and overlays and data visualizations, and all of those tools can help us identify the trends and help us move towards achieving the KPIs and the accountability that we want to achieve.
Jeremy Holden: Hello everyone, and welcome to Connecting ALS. I am your host, Jeremy Holden. In 2012, a New York Times article welcomed us to the age of big data.
"What is big data?" The Times asked. "A meme and a marketing term for sure, but also shorthand for advancing trends in technology that opened the door to a new approach to understanding the world and making decisions. There is a lot more data all the time, growing at 50% a year, or more than doubling every two years, estimates IDC, a technology research firm. It's not just more streams of data, but entirely new ones. For example, there are now countless digital sensors worldwide in industrial equipment, automobiles, electrical meters, and shipping crates. They can measure and communicate location, movement, vibration, temperature, humidity, even chemical changes in the air."
Now that was 10 years ago. Now consider this: An estimated 2.5 million terabytes of information is produced by 7.2 million data centers around the world every day. So it could be said that the age of big data has gotten, well, bigger.
Harnessing that data can enable organizations to make better decisions more quickly, reduce costs and increase efficiency, and respond more quickly to the people they serve. Writing in Harvard Business Review back at the dawn of the age of big data, Andrew McAfee and Erik Brynjolfsson observed, Because of big data, managers can measure, and hence know, radically more about their businesses, and directly translate that knowledge into improved decision making and performance."
So what does all of this mean for us? In a conversation on Connecting ALS earlier this year with Scott Kauffman, chairman of the ALS Association board of trustees, he spoke to the potential for big data to expedite the work to make ALS a livable disease while ultimately finding cures.
Scott Kauffman: There are those among us that believe that the cure is here. It's on this planet with us, but probably an exercise in big data, machine learning, artificial intelligence. And the only way you're going to get there faster is if you pool all of the resources and all of the data, and that you kind of divide and conquer.
Jeremy Holden: So how is the Association harnessing the power and potential of big data to better serve the community, and to speed up the process of empowering people to live better longer lives, to bring new treatments to market, and to reduce the harms associated with ALS? For answers to that, I turned to Pam Knott, Vice President of Data and Technology at the ALS Association. Well, Pam, thank you so much for being with us this week on Connecting ALS.
Pam Knott: Of course. Happy to be here.
Jeremy Holden: You and I had a conversation a couple weeks ago about this very topic, and I mentioned it at the top. But Scott Kaufman, the chairman of the board of trustees for the ALS Association, talked earlier this year about how he was excited about the role that big data could play in moving us closer to making ALS livable, ultimately finding ways to treat and cure the disease. So let's start there. What role do you see big data playing in terms of making ALS a livable disease?
Pam Knott: I think that data in general, and of course big data, plays a very important role. It plays a big role and a broad role. And for that word livable, in my opinion, there are two different sides of that. First, you have the research, so actually prolonging life, finding cures and treatments, finding causes, and hopefully preventions. And with that, an example would be the CDC registry. We collect data from people living with ALS so that we can have more context around their lives to find trends, et cetera, patterns.
But the other side of being livable is the quality of life, enhancing the quality of life, easing the burdens as much as possible. That's really where my team is focused on. Not necessarily the hard research, but the resources and the empowering tools that we can provide the community. So knowledge is power, right? Data gets us to that knowledge. And for the empowering tools especially, that knowledge should be as targeted and specific as possible to the person and their family so that they can make the right decision for them at the right time.
Also, for resources and improving quality of life, we have our advocacy and public policy efforts. Those efforts require evidence to bring to the table on why a certain bill related to Medicare should be passed, or why the FDA should approve a treatment quicker. Things like that. So yeah, data has a really big role, but we sometimes go right to the hard research. I think that there's a broad spectrum there and each side of that spectrum is just as important.
Jeremy Holden: Yeah, I think it's a good point to think about. Yeah, we do often think about data, particularly in this world about driving research and having more data points to try and understand disease mechanisms and a way to maybe slow progression and that sort of thing. But I think you're talking about ways that data can really touch on the delivery of care, and some of that work being done to, as you said, improve and enhance quality of life.
So let's dig in. What does that look like? What are some kind of programs that are being driven by data? What are some day to day ways or things on the horizon that are really bringing data to life?
Pam Knott: The first thing that popped into my head, I just got off a call actually, for the patient journey map tool. And like you said, this isn't launched yet. It's somewhere on the horizon. But we are working collectively with our care services team, with our communications team, to build a tool, again, that translates data into knowledge and action items for a person living with ALS and their family wherever they are along their journey, and in different ways and different levels. When you're first diagnosed, it's probably a lot to take in, and maybe you don't want to read a 10 page article at that moment. Maybe you just want to really quick video. Or maybe you just want to know, "Where can I find a group of people that I can talk to that's already gone through this that can support me?" So that's one of the tools we're working on that patient journey map too.
Again, technology, I sort of lump data and technology together, because you have that information, but you also need a system or a process to help make it actionable.
Jeremy Holden: Sure.
Pam Knott: So this tool will be available in different formats. Folks can access it when they want to. If it's midnight and they can't sleep, they can access it then. Those sorts of things. Also, making the information as accessible and inclusive as possible. Just thinking about learning styles. So perhaps I'm a visual learner, but maybe somebody else is an auditory learner. So using tools to help expand the accessibility and inclusion as well is really important. So that was just one tool, the patient journey map tool.
Circling back a little bit to the research side of things, we are developing a clinical trial MATCH initiative.
Jeremy Holden: Oh wow.
Pam Knott: Yeah. We have an initiative that we are building out right now in our database. We use Salesforce. This is for clinical trial MATCH. So right now it's a pretty big burden for people living with ALS to identify and understand what clinical trials are out there in the first place, and which ones they might be eligible for. Because there's a certain set of criteria for particular trials. That could be age, gender, location, how far along the disease has progressed, things like that. The tools available right now, at least the feedback that I've gotten, are kind of daunting. There's a lot of filters to apply. Maybe you don't know the timing of a certain trial, if it's closed already or not, all that stuff.
We are partnering with companies who have trials, who are releasing trials. They have a certain trial recruitment window. Once we get the criteria, the eligible criteria from those partners, and we understand the window of time for which they want to recruit, we can use the data already in our database to target folks that have the right eligibility requirements.
Let's say trial A, the company is recruiting the month of July. So in the month of July, we can build an automated email journey that grabs those folks with those particular data points and automatically send them an email so they don't have to do anything. We are trying to take that burden off of them. They'll receive an email saying, ".Hey, you might be eligible for this certain trial if you're interested, click on this link to learn more and register." So that's one of the things that I'm really excited about, taking the burden away from the person and the family dealing with ALS.
And also what that will do is get recruitment for trials completed quicker, because that's really a bottleneck for trial recruitment is that the people living with ALS can't find the right trials and the trials can't find the right people. So hopefully we will be able to aid in that matchmaking process there.
Jeremy Holden: That's really exciting. I know we're going to be talking to Dr. Merit Cudkowicz in the coming weeks about other efforts that are underway to expand access to clinical trials. And now knowing that reducing that burden, so someone's not just sitting there at their computer hitting refresh waiting for that trial to open up. Going to them-
Pam Knott: Exactly, yep.
Jeremy Holden: ... and saying, "Hey, there's a trial that you might match with." That's exciting. I don't want to step all over the great things that you have to bring here, so what are some other exciting things that are happening in the world of data?
Pam Knott: Yeah. One really tangible area is geospatial data. This might be the best example of really making insights snap into focus. You actually see a picture. We've been putting a lot of resources towards mapping different layers of data, first and foremost to be a tool, again, an empowering tool for people living with ALS and their families to understand where the closest clinic is to them. On the surface, that might not be a big deal. We have lists online already of the clinics in Alabama, the clinics in Arizona. But adding this additional visual of an actual map, again, going back to being as inclusive and accessible as possible, but it makes the insight easier and quicker to grasp of, "Oh, I know exactly which one is closest to me, because there it is. I can see it on my computer screen." Or the patient could be traveling, so maybe they're familiar with the clinic that's closest to their home, but they need to become familiar with those that are going to be the easiest to get to when they're on vacation or whatnot. So that's a really exciting tool that we just launched, the clinic locator.
Geospatial data also helps us at the Association understand where our gaps are, where we can do better. So maybe we map people living with ALS that we are serving at the moment, and we also map our clinics and other resources we have available in those areas. We can see that there's a really big gap where a lot of patients are, so perhaps that leads us to investigate working and establishing another clinic, or maybe hiring additional care services resources, particularly in that area. So it's not only an empowering tool for our constituents, but an analysis tool for us to take action in that way.
And also, with the recent hurricane, geospatial tools can also be really impactful for when we have to have a disaster response. Again, understanding the most affected areas and getting to the people living in those areas as quickly as possible.
Jeremy Holden: You were talking earlier about maybe underserved areas, geographically speaking. So much conversation in recent years, and I know again, you and I talked about this relatively recently around diversity, equity, and inclusion. How can data help us maybe reduce some of the healthcare inequities that we know we've talked about on this show in the past?
Pam Knott: Yeah. First you have to capture the data. You have to know who you're serving in order to maybe realize who you're not serving. And so it's really tricky to understand who you're not serving, and how you take steps to get to them. But that's the first step of just understanding the broad landscape. That's also why it's really important that we break down our barriers and our data silos to have that full picture.
Right now we are working on a project to consolidate our data into one data ecosystem. This is one of the really great reasons why it's so important to do that, so that we understand that we are looking at all of our data to identify those trends that you just spoke about, of are there clusters of overlaying geographic and demographic layers of, well, we know that the population that we're serving in this area is underrepresenting the overall population in that area. So tools, again, of not just using a spreadsheet of data, but using systems and overlays and data visualizations and all of those tools can help us identify the trends and help us move towards achieving the KPIs and the accountability that we want to achieve.
Jeremy Holden: Yeah, KPIs are so important to be able to measure results and measure performance and make sure that we're gathering useful data, we're putting it to use in meaningful ways. Very exciting stuff. Pam, before I let you get back to it, to those visualizations, to those overlays, and to the data analysis, any closing thoughts for listeners as we think about the role that data plays in the fight against ALS?
Pam Knott: Yeah. I will say that data is important because data leads to knowledge. But it's not just data; there are people behind that data.
Jeremy Holden: Yes.
Pam Knott: There are people creating the systems. There are people cleaning the data. There are people taking those insights and taking action with them. I think that that's also a really important piece to understand of, yes, data is extremely important and we couldn't do it without data, but additionally we couldn't do it without the people and the relationships and the integration and the collaboration that is needed for understanding the comprehensive picture and getting the work done. Prioritizing the work and making sure that we are all headed in the right direction towards our mission.
Jeremy Holden: Really fascinating stuff, and I'm looking forward to some of those tools that you talked about coming online. I will dive deeper into those when they are ready and start talking about them with listeners. But Pam, thanks so much for your time this week. Hopefully we can have you back on down the road.
Pam Knott: Sure, absolutely.
Jeremy Holden: If you enjoyed this week's episode, share it with a friend. And while you're at it, please find time to rate and review Connecting ALS wherever you listen to podcasts. It's a great way for us to connect with more listeners.
Our production partner for this series is CitizenRacecar. Post production by Alex Brower, production management by Gabriella [inaudible 00:16:47], supervised by David Hoffman. That's going to do it for this week. Thanks for tuning in. We'll connect with you again soon.
Transcript by Rev.com