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AI and Patient Experience: A Balancing Act

AI and Patient Experience: A Balancing Act

SR Health's text-first platform enables nationally top-ranked Boston Children's Hospital to affect more meaningful conversations and interaction with the families it serves.


LEA CHATHAM: Hello, everyone. Thank you so much for joining us today. We're really happy to have you here. I can see that we still have a number of people logging in. So I am going to just give those folks a couple more seconds to kind of get on and we'll kind of move forward with some housekeeping items and talking about a few things. We are doing AI and Patient Experience: A Balancing Act, today. This session was originally intended to be presented at HIMSS ‘20, as we all know, and '20 was canceled. So we opted to work with our partner Kevin on putting this together as a webinar for everyone so that we could still present this content. I'm really excited we were able to pull that together for everyone. 

So our speakers today are, as I mentioned, Kevin Pawl, who's the senior director of patient access at Boston Children's Hospital and Nagi Prabhu, who is the chief product officer for SR Health by Solutionreach. We are going to be talking today about some general information around AI and the patient experience, as well as really some specific recommendations, tools, and experiences that Kevin has had in his role working at Boston Children's. 

I'm really glad everyone is able to join us. Couple of quick housekeeping items. If you would like to ask questions at any point during the webinar today, you can do that in the question bar. So on your toolbar, you'll see there's an option for questions. Just click on the little arrow. You can type your question in. This would be the place to put in, not only questions for our speakers and about our topic, but also if you're having any kinds of issues related to the platform. 

One of the most common questions that we get around webinar platforms or webinar issues has to do with sound. If you're using your computer for audio and you're having any issues with your sound, I would strongly recommend you switch your audio to phone. So again, if you click on the little arrow next to the word audio, you'll see that there are options for computer, phone, or no audio. If you switch from computer to phone, it will give you the dial-in information. That is really the best way to address any audio problems that you're having if you are using your computer for audio.

We also are often asked whether or not this PowerPoint deck is available to attendees. If you click on the little arrow next to the word handouts towards the bottom of your toolbar, you will see that there is a PDF of today's slides. And you can download that from here. I know a lot of people like to download the slides or even download them now and print them out and follow along or make notes. You can absolutely do that.

And finally, there will be a recording of this session that will be sent out. So if you want to share this with other people in your own organization, or you want to watch it again, you're welcome to do that, we're happy to have you watch it as often as you like or share it with anyone you want. So you will get an email with some additional information and a copy or a link to the recording when we're done. We will have plenty of time for asking questions at the end. So please do feel free, as we're going along, to enter any questions that you have in the question bar. And we will do our best to answer them all when we get to the end of today's presentation. 

So, as I said, our speakers today are Kevin Pawl and Nagi Prabhu. And Kevin is the senior director of Patient Access at Boston Children's. And Maggie is the chief product officer here at Solutionreach. Both of them have had quite a bit of experience, really working on issues around patient experience and patient access and how technology can be used to address those issues. 

And I am going to hand it over to them here in one second. I noticed we're getting some questions here about sound. So just reiterate what I said before and send out a quick message, that if you're having any problems with your sound, you probably want to click on audio and change to phone from computer. Okay? So I'm just going to send this message out really quick to make sure everybody knows to do that. And then we will get started.

All right. Great. Okay. So, hopefully, that will help people resolve those issues. I am going to hand this over to Nagi. So Nagi, I'm going to give you the keyboard and the mouse. And you should get a little pop-up here and be able to move these slides forward. Yep. I see you moving your mouse. 

KEVIN PAWL: Okay. Can you hear me okay?

NAGI PRABHU: I can hear you. Okay. Okay. So this is a... All right. First of all, before I start the webinar, I want to thank everybody who has joined the webinar, not just for joining the webinar, but what you guys are doing as part of the healthcare industry. We as an industry have, in the last few weeks, being bombarded by this epidemic and put under pressure to deliver. And I appreciate everything that you guys are doing. Thank you for doing what you're doing.

For us at Solutionreach is it's been a very sobering experience. We have been delivering healthcare messages for last 20 years but last few weeks has been really putting us to test to really ready to step up and deliver messages in a way that have been unprecedented. But I'm glad that we have been able to help our customers and also the patients in this very trying times. So, again, I wanna thank you guys for doing your part in dealing with this epidemic on last few weeks. And I expect that it will last for a few more weeks and your work will continue and our work will continue in doing that. 

So with that, the agenda for today is essentially to talk about the difference between patient versus consumers. And there is a word of consumerism has been going around for a very long time and people are trying to apply that to healthcare. And we want to analyze how that is working. And as the role of AI in patient engagement, what is the right amount of AI? Where is the right places to apply?

And then Kevin is going to jump in and talk about what he has been going through in terms of patient engagement, the role of AI in his organization, what challenges that he saw and how he was able to overcome those. And then, of course, we will stand here for a few minutes to ask any questions. And of course, even after the webinar, both Kevin and I are always available to have offsite conversations regarding, by email or by phone, to have any conversations to dig deeper. 

The learning objectives here is, like I said, is... There's a, unfortunately, delay between my click and the screen. So the learning objective, like I said, is develop the technology strategies and figure out how do you drive patient communication where you automate enough and apply AI in order to create a good balance between patient experience. 

There's a poll that we want to do before we get started. Let's quickly run this poll, if that's okay. Leah or-

LEA CHATHAM: Yep. We'll push this out. You'll see it pop up on your screen. We'll give you guys about 20 or 30 seconds to do the poll and then we can push out the results and you'll be able to see. And this is really just for us to get a sense of how many of you are already kind of at solutions, AI-driven solutions, and maybe have some experience with this already. All right. We do maybe 10 more, five or 10 more seconds. Okay. So I'll go ahead and close the poll and push out the results so everybody can see that.

NAGI PRABHU: It looks like it's at about 50/50 45, 55, 45% have looked at it and the 55% have not looked at it. Hopefully this session we'll try to tailor our conversation with that data in mind. Hopefully, this webinar gives you some idea about where to get started and what to do.

So I want to start with first with definition of consumerism, right? So the consumerization which is a word that has been going around. Yeah.  Consumerization, that's going around. So consumerization, if I have to define it, it is about getting the consumers or the users the things that they need in an immediate fashion, in a automated fashion, and at any point in time, 24/7, and in the way that they need it. So that is kind of what the consumerization can be simply defined as in my mind. 

However, when you look at patients, the patients and consumers are not the same. For example, the consumerization has taken every other industry by storm. And if I look at finance, for example, my bank account actually is in California, but I live in Utah. And last year or so, I've never been required to go to my bank account. I've been able to do everything on my mobile, on my web, using the ATM machine when I needed to do what I needed to do. 

But, however, the patients are not... While consumerism is applicable for healthcare, but the patients are different. So because in the patient scenario, there is a human life involved a wellbeing of a person involved. I think if we roll back 20 years or 30 years behind from now, the banking was like healthcare. Where if I were to trust my money with a financial organization, I needed to meet a banker. And I wouldn't put the money without knowing who I am dealing with. 

But that thing has gone. Like I said, I don't know who my bank person is. I do everything as a consumer. But I think healthcare is not there yet. Healthcare is getting there, but healthcare is not there yet because there is, my wellbeing is involved, my life involved, there is a requirement that there is some amount of personalization or a personal that be there as part of my interaction with the provider.

However, the problem is that there's a big disconnect in terms of what the patients are expecting and how much touch that they're expecting on a day-to-day basis in a personal basis. On the other hand, the providers, how much they are able to provide with the limited resources that they have, this increased demand that is coming. There is a big distance between what the patients are expecting in terms of the interaction that they need in the personal way, and what the providers can provide with the resources that they have and the tools that they have in their disposal. 

However, what we think is that AI is an area where it can actually bridge that balance. So AI can enable the bridging of the gap by taking away some of this overhead from the providers and allowing patients to be getting the similar personalized experience while still having the personal touch. But the need there is you got to make sure that you pick the right challenges to address. 

So some of the challenges that we have in looking at, they need to be something that is not life-dependent, that is not very wellbeing-dependent, but they're more administrative. So the things that we are looking at, the areas and the healthcare that are very right for AI is improving patient communication is one area where the AI could be very useful because that is something that the patients are used to doing in other places. Filling a schedule or making an appointment is another area. Understanding the patient's feedback or the surveys and things like that is another area where patients are used to doing those kinds of things in the other industry that can be applied in the healthcare as well. 

And if you were to look at these areas and see what am I going to use to enable these areas to be AI-enabled, there are several AI tools available such as SMS chatbots, website chatbots, confirmation tools, and things like that. However, not all of them are created equal. The reason is that the primary difference is that if you try to go too far in your AI journey, that actually takes away the experience entirely.

And I think there are some surveys that were conducted by different organizations to understand how much of AI is actually acceptable in an healthcare organization. So if you look at this survey here, 47% of patients will use AI because it's available when need, but 29% said they won't need it but they want to see a doctor. So that's a very low number compared to in other industries or in certain areas. Like 61% would use an artificial intelligent assistant to handle financial transactions, schedule appointments, and explain their insurance coverage and things like that.

So as you can see, the people are comfortable in certain areas of the healthcare to be dealt with artificial intelligence, but then when you ask them about general question about how much AI in healthcare, that number is much lower. And 71% say, then you don't say it as healthcare if you want to use AI. 71% say they want the AI when they are interacting with companies. So that just tells us that the healthcare, there are areas that we can focus that are relevant, and then there are areas that are not relevant and should not be used for automation, will make the patients very uncomfortable about it. 

And now if you look at from the provider perspective, the providers are feeling the need of automation themselves, AI themselves, because they are recognizing the onus on them to provide a great patient experience cannot be satisfied by simply having human conversations and unautomated way or a non-automated way. So there are 68% believe that AI-powered software will allow them to spend more time on other important tasks. 54% executives reported AI technology is already helping them. I think we saw that earlier that there were 45% of the people who're actually looking at or using the AI technology. So surveys says 54% executives reported II technology is already helping them optimize. 

I don't know, Kevin, if you want... As a provider, Kevin, I don't know if you have anything to add in this area. 

KEVIN PAWL: I think it's a wonderful example of where leveraging technology to support the clinical care and clinical operations. I love some of what you said at the beginning, Nagi, in terms of everyone in healthcare right now is facing an unprecedented challenge. And I think about the staff in our call centers and the families that are calling in uncertain. I heard from a cardiology administrator this week that a family without any current clinical concerns was just trying to get through and ask their doctor some questions related to COVID. 

And being able to have the right people, in the right place at the right time, and leveraging AI to support our teams, if there was ever a time we needed it, it's now. So I think it's... If you're not looking at AI in these different spaces, supporting your call center, supporting patient and family communication, I think it's definitely something to investigate. 

The last thing I'll say, Nagi, about this is that I had... One of the chiefs of our neurosurgery department said to me, "What's the biggest problem we have in patient access? And I said, "Well, number one, can they get through to us on the phone? Most people are doing their healthcare business still on the phone. And number two, if they do get through to us on the phone? Do we have that slot, do we have that appointment they need? And how do we leverage the technology to reduce the burden, both on the family and on our staff?

NAGI PRABHU: Awesome. Yeah. Thank you, Kevin. So we have been thinking about this for a while. And I think the technology-wise also, the maturity-wise of automation, the NLP machine learning, are the areas which are significantly progressed over the last five years and are ready for really prime time, even in the healthcare scenario. And one example use case of a patient AI-first patient interaction would be a diagram like this. I wanted to use this diagram to explain how that might work.

So today, I suspect that majority of the conversations that are happening between the patient and the provider is by either when the patient is in the office, which is obviously a natural thing, but when they are not in the office, it is basically happening from the phone. So the patient calls makes a phone call and gets to a person. Or if the patient has had a surgical procedure, at the end of the day somebody from care management team makes a phone call to the patient or the patient's family to find out how that's going and the communication sort of ends there. 

But I think in an AI-first patient interaction, you can imagine a scenario, a patient uses the tool of his choice, which might be phone on a text, and that could be actually fed into an AI situation. And this AI can initially start out with the basic fundamental things that a patient needs such as confirming their appointment, making an appointment, rescheduling an appointment, parking, directions. Those are the kinds of things which really don't have to be dealt with in a personal manner, but are being dealt today in a personal manner, taking the time away from people who are providing care to be doing things that are non interesting. 

So those are the items that can initially be easily fed to an AI and be responded to by an AI. In fact, we have been using to a text conversation for several years. When we ran some analysis of all the conversations that were happening, almost about 56% of the candidates happening were all related to scheduling, and parking, and direction, and those kinds of topics. Less than half word, more about asking care and things like that. 

So the way a system like this would work in healthcare is that AI will try to answer the things that it can, and in the cases where it cannot answer those questions, or it is not confident about answering those questions, which is a distinct thing by itself, it will get escalated to a person who is attending the form or a person who is attending text messages. 

So what that results into is essentially bringing of consumerization into healthcare, which is essentially honoring the patients need to use the communication medium that they want, they don't want to be making phone calls, and also allowing them to be able to get responses to majority of their questions 24/7 and they don't have to wait for the office to open up the next day. 

So here, I want to transition it over to Kevin. And, Kevin, maybe you can talk about what your experience has been going through this change process and talk about what you have learned. 

KEVIN PAWL: Thanks so much, Nagi. Change management is such an interesting realm. I'm seeing so many different things in the last few days, given the crisis we're in. And a crisis. I think if you're positioned well and you're calm and collected, a crisis can actually be a wonderful time for changes to occur. We've got people that were not open to virtual visits now open to virtual visits. We've got governments finding ways to break down barriers and allow for reimbursement for virtual care. And we've got people considering different technologies and different ways of doing their work that otherwise wouldn't consider it.

Boston Children's has always been a leader in care. And our goal is to also be a leader in service. And I think that empowering our people to help families and to provide choice to families, whether they want to speak to a person or whether they want to have automated self service solutions. We want to, we want to match that challenge and be the best service provider we can for patients and families. 

I think we're doing a lot of different things with AI in the organization. We've started to look at... Some of you may have seen Dr. John Brownstein's information on mapping the COVID cases. We've also got examples in our revenue cycle in terms of trying to automate some of the processes with authorizations and referrals. And I think looking at the volume of activity in our call centers is another way that we could potentially leverage the technology.

One of the ways that we've used technology is with our self-service kiosks. And I wanted to share a brief video with you all that demonstrates an example of technology working in the family and patient space.

Speaker 4: Hello, welcome to Boston Children's Hospital. (silence). 

KEVIN PAWL: Yeah, this is a good example of a time where we might not have all of our staff physically present in our locations and kiosks are a wonderful way for people to check in without a human interaction. Some of our kiosks, the newer generations, actually have infection control built-in with the UV lights. Having this technology deployed and ready has better prepared us to help people in this sort of crisis situation. I think it's an example of where technology can help. And I think AI is uniquely positioned to where we can do things differently in our call center space. 

Some of the other examples that I mentioned, Amazon, Alexa, so kids being able to speak into a device. I think that's in pilot phase now. Definitely tracking a lot of the different diseases like flu and COVID and other things. And then sending and receiving PHI, this has definitely been a challenge. And I think people thinking creatively around ways that we can safely and securely share PHI with different organizations. It tends to be a major stumbling block for folks transferring care from one facility to another. 

The digital front door is something we often think about. And given that patients and families still do most of their healthcare transactions via phone, the first thing they think of is calling and being able to empower our call center and retrain and enhance our workforce to handle more complicated problems. I think to connect to what Nagi said earlier, when's the last time you called your bank to check on your account balance, or went into a branch? And you could imagine that much of the healthcare can be digitized. 

I was excited to hear about how many virtual visits we're having scheduled and completed each day given that a lot of people that are having less serious issues don't need to go into the hospital right now. And that frees up capacity for the sicker patients. So this is an exciting time to think about that digital door differently. 

Some of the barriers, I mentioned some of this, the fear of change is just so powerful. What's that going to mean? We had people worried that is this going to mean that call center employees are out of work? How is this change going to happen? What if patients and families don't want to use it? And I think some of what Nagi said earlier is so true, this provides choice, and it also has to be used with balance. It's not going to work for everything. Nagi these numbers of 56% of the calls and the interactions being related to appointments.

We've studied this very carefully, listening to thousands of calls. And about half the calls are non-scheduling. And is there an opportunity for AI and automation robotic processing to help with some of those non scheduling needs, like how to message your physician, and can we push families to a patient portal or get them signed up for the portal? There's lots of activities that I think the technology can support. 

When you ask healthcare administrators what are the biggest challenges they face, interoperability is huge. Can we have these different systems talk to our EMR and our practice management system? Is there interoperability? What about, as a pediatric academic medical organization, we rely heavily on the referrals from the community pediatricians? And are we connected to those community pediatricians? And how do we make sure that it's easy for them to send us the patients and families that need help? And all the while, how are we adding value? And are we optimizing to add value?

I think considerations to those barriers definitely err on the side of caution. We rarely would call a patient, a consumer, but it's the world we live in. They have choice. If they're a child has a significant medical concern, we hope they're going to turn to us first. But when they have a lesser concern, some foot pain, or a wisdom tooth extraction that's needed, they have choice. And we want to be that choice. And we want to offer what they have in every other aspect of life. If they can use text and online applications to quickly and easily receive goods and services, why shouldn't they be able to do that in healthcare? 

I think we have been taking very small steps. So don't go too far, too fast. We use the families' voice very carefully. We partner with our families, patients and families, and our family advisory council. They help advise and they help create many of the different changes we make. And that voice of the patient and family is so powerful. Hearing from them what works well and what doesn't work well. And they're great to work with. They're very open and honest about both the exciting things that we partner with them on and build and the things that that didn't work out exactly as they should. And then we can go back to the drawing board and consider different changes.

The workflow changes and the preferences are key. And listening carefully to the different stakeholders, whether it's the providers, the patients, the families, the employees. Those are all essential conversations to have in the change management process to help remove those barriers. 

NAGI PRABHU: Thank you, Kevin. 

KEVIN PAWL: Thanks, Nagi.

NAGI PRABHU: I think that that kind of brings to the end of the presentation. I want to summarize two things. Number one is that when people talk about AI in healthcare, the first thing that they think about is that, oh, we are going to eliminate the doctors. We're going to take some AI to detect anomalies and identify diseases. Or maybe a robot being a surgery. That's the thinking that comes into mind first. 

But before we go that far, there are a lot of low-hanging fruit out there that that can be solved through AI and automation, particularly in the age where the natural language processing and machine learning has grown so fast in the last 10 years. There are a lot of things related to patient engagement, patient communication, patient interaction, which can be automated using these technologies. 

So I want us to start as an industry, think about the low-hanging fruit first that you can address. And the second thing that I wanted to talk about summarizes that. When you try to do these AI-based automations, think about the tools that allow you to not go from zero to a hundred overnight, but they allow you to go from zero to 50, 50 to 60, 60 to 70, and rightly bring in the person, a human person, being in the conversation seamlessly. But when it is not needed, it is able to answer the question right so.

So that transition needs to be dealt very carefully between the AI-automated conversation to interaction to a human interaction. And if that is not very seamless, then the patients will get disenfranchised by the AI and will not like the experience. So when look for tools that you want to do, look for tools that not just promise you a hundred percent AI automation, but take you through the journey of going from zero to a hundred in an incremental steps without making the experience for the patients suboptimal.

So those are the two things that I would like you to take away, if nothing else, at the end of this conversation. And I think we can open it up for questions. 

LEA CHATHAM: So thank you so much, Nagi and Kevin. We do want to show this last piece, which is actually a video that shares sort of how some of this technology can potentially work. So, Nagi, I'm going to kick this off. I think you said you might need to pause to make a comment.

NAGI PRABHU: Yeah. We can do- 


NAGI PRABHU: Yeah. Oops. 

LEA CHATHAM: And we'll just... You probably still can pause as well. 

NAGI PRABHU: So this is the patient provider communication using texting, which talks about how our text messaging is going between the patient. And in this case, as you can see, the system is responding automatically and it is allowing a person to handle the communication, watch the communication that's happening. But at some point, the patient wants to reschedule. So the AI is actually getting information from the patient to understand when the patient can come in. And the appointment has been rescheduled.

So in this case, as you can see, the whole conversation happened through an automated way, but there is a potential that the patient can ask a question that AI may not understand. So what's the dosage on medication? I think the system needs to be smart enough to move that immediately to the people. 

Another example of this is with the surveys. If you are an organization that receives thousands of surveys, there is no way for it to be able to read each one of them and talk about what the patients are discussing. But I think applying AI can tell you at a very granular level what are the different aspects. It's not about NPS score of one to 10, but you can tell whether the sentiment of the patient around the front desk, or the digital ease of use of the digital tools that they have, or the cafeteria that they are going to.

Each one of the sections of the sentiments, you can actually analyze and see what you are trending better and what you are not trending better. There's another example of um AI that can be applied. That's not really life-threatening or wellness related, but can release lot of unnecessary number of hours your staff might be spending still not getting enough information that you can get out of these patient responses that you get for service. So I want to stop here and open it up for questions. 

LEA CHATHAM: We did have another poll we wanted to push out. This poll is about what are your concerns about AI? So we had about a 50/50 response on whether or not you've already looked at using AI in your organization or not. And now to help us kick off kind of our conversation here in our last 10 or 15 minutes of questions, what are some of the concerns that you have, whether you're currently looking at AI or it's something that hasn't really been on your radar until right now? What are the things that you're most worried about?

And that should help us actually a little bit talk about some of those things and kick off our Q&A and discussion period. We'll give everybody just about another five seconds or so, and then we'll close that up. I think what you'll see is that it seems like the biggest concerns are around sort of IT infrastructure, reliability, which I know we've heard a lot, too, people kind of concerned about how you roll this out and make sure that it does what it's supposed to do. Because obviously, as Nagi mentioned, we're concerned about just as people's wellness, this is their lives. You obviously don't want to roll out solutions that aren't going to work the way they're supposed to. 

So given that, I think, Nagi, a great kickoff question for us would be, how do you make sure if you're implementing something like this that you can ensure that it's rolled out and that it works the way that it's supposed to? 

NAGI PRABHU: Yeah. I think I mentioned that in my second takeaway point, is that you got to be able to dial in and out of how much automation and how the transition happens. You got to experience that. At the beginning, you might want to dial it down where you want to be a hundred percent certain that the AI is confident in a hundred percent. And then you can dial it down to get more automation. So I think the most important thing that you can do is find a way to be able to adjust the amount of automation, patient satisfaction, and play with those. And then make sure that you are achieving the right results. 

The second thing is that you also may want to make sure that you pick the right type of things that you want to automate. Like I was saying earlier, you probably don't want to automate somebody who is having a heart attack or a heart pain, but you certainly want to make sure that there are intents that are safe that are non life-threatening that you can automate. And over time you can actually bring more medically-oriented intents into the automation. 

Like for example, you could ask a person who has had a surgery, you can ask a question automatically to say, do you have fever? And based on the person saying yes or no, you can take an appropriate action to have a person call that person or not. So the finding the right use cases that are non life-threatening, easier, the people feel comfortable, people have used them in other industries, is the key in making sure that your deployment of AI is successful. 

LEA CHATHAM: Great. Thank you. So we, and this maybe more of a question for Kevin and I apologize we're continuing to... I think we finally got this thing working here. So, Kevin, how do you guys sort of figure out the ROI around making a purchase like this, implementing a new system like this? What are sort of some of the guidelines you have in place around how you figure that piece out? 

KEVIN PAWL: I think it's not always the return on investment that is the primary driver. I think patient experience has a value. So I think hearing from the patients and families what they want and need. At the same time, taking our highly valuable resources... The people that answer the phones are called patient experience representatives. So having those resources free to help patients and families with the more complicated tasks, scheduling multiple visits for a complex care child versus providing directions to the parking lot or information that can easily be handled via self service. 

I think it's a disruption in many ways, an innovative disruption. And I think similar to change, the feelings that people have with change management, going slowly is really important. So I think we definitely look at the return on investment and could we redeploy staff to more value-add tasks. But I think people do get very worried about it. So going slow is part of it for us. 

LEA CHATHAM: That's great. Thank you. Okay. So, Nagi, this may be more of a question for you. But someone is wondering, can AI be used to move people to directing the conversation to the right technologies? Right? Can it be used moving people between text and phone and over to a portal or video chats to kind of have a seamless transition from one thing to the next thing? 

NAGI PRABHU: Yes. The answer is yes, it starts with an automation with the text and then it raises us to another person for texting. And that person can actually then pick up the phone and call. Or we could actually create a scenario where we can direct them to their portal if they are asking questions about their health situation. And if we know that that patient has a portal sign in, you could actually have the AI automatically direct them to the portal. So all those possibilities of moving between multiple mediums needs to be part of the automation process and the workflow process. And a lot of it is currently possible. 

LEA CHATHAM: That's great. Thank you. So we had said that this webinar was going to be about 45 minutes. So we have gone over by a couple of minutes and I apologize that we have had some slight technical stuff. I'm sure most of you understand that some of us are working from home. And that is something that happened with not a lot of preparation. So we are not necessarily on the best connections or on our ideal technology. And I just do want to apologize for a few of those issues with sound and with the presentation and having to reload that. We really are very grateful for your patience in that. 

Also, I did very quickly just want to remind everyone, we've had several people asking questions about being able to get the slide deck or being able to get a recording later. As a reminder, you can download the slide deck in the handout section. You'll see an option there for handouts. If you click on the little arrow, that will open that up. You can download a PDF of the slides. We will be sending out an email later, which will also have a link back to the recording. And you are welcome to watch this again at any time or share it with other people in your organization or other colleagues. We're happy to have you do that. 

I am going to just very quickly share some information about SR Health by Solutionreach. We are sponsoring this webinar since we were not able to do this at HIMSS. We managed to throw this together very quickly to be able to present it as a webinar, because we felt like this was really important information around how AI can be used for patient engagement and patient communication.

SR Health is the solution that's been developed by Solutionreach designed for enterprise healthcare. So really designed for hospitals, health systems, large rural clinics at federally-qualified health centers and organizations of that type. But we have built it based on our 20 years of experience. So we have been supporting smaller organizations for the last 20 years. We were the first company to send a text message in healthcare. And today we connect over 80 million patients with their providers using our platform. So we do have a lot of experience in this, and we really are a leading innovation in how to use AI-driven solutions in patient engagement and patient communication. 

We're really grateful that you were able to join us today. I'm just quickly going to look to see if we've had any additional questions we want to answer for those of you who are still hanging on with us. Okay. Let's see. So, Nagi, there's a question here about whether or not this kind of AI can be deployed in smaller organizations. Does it have to be... Is it really only for large hospitals and health systems or is it something that's scalable really for organizations of any size? 

NAGI PRABHU: Yeah, I think the technology is scalable at any organization size. Here is the reason why. The underlying algorithm and technology is build using the data that we have across all our customers. If there is an unidentified or confiscated data that has been used to actually train the models and create the right responses and create the right understanding of AI so the data that is being used is across all our customers, which helps in creating the models, but a smaller organization could simply use it even if they don't have all the data that they have accumulated over the years, they can take advantage of the collective intelligence that we bring into the system for a smaller organization. The answer is yes. 

LEA CHATHAM: That's great. I think we will, at some point, start to see AI really being deployed on a much larger scale organizations of all types and sizes. So we do want to let people go make sure we're within the time and not too far over the time that we'd originally set. And we are so grateful that everyone was able to join us today because this is such great content and we did want to make sure that despite the fact that [Adrew 00:50:47] was canceled, we were able to share this. 

I want to say, thank you so much to Kevin and to Nagi for making themselves available, to be able to reschedule this and do this as a webinar today. So thank you for being here. Especially, Kevin, I know you are very busy dealing with a lot of issues for Boston Children's right now around COVID and everything that's going on. So thanks for taking the time today. 

KEVIN PAWL: Thanks so much for having me. And if folks have other questions or if there's things we can learn from folks that have already worked in this space, we'd love to hear from you. 

LEA CHATHAM: Yeah. And I'm throwing up the contact information here for Kevin and Nagi. They've both been generous enough to let us share their emails. If you have additional questions for them, you want to connect with them, they are also both on LinkedIn, I believe. Yeah. I know Nagi is. Kevin, you are too, right?

KEVIN PAWL: Absolutely. 

LEA CHATHAM: Yeah. So feel free to connect with them or ask additional questions. And you're more than welcome also to go to srhealth.com and send us additional questions or connect with us. We're happy to get you to the right person or get you the answers that you need. But thank you so much, everyone, for joining us today. Good luck during this difficult time where we are, hopefully, all together in this, and supporting one another. And we wish everyone the best have a great day, everybody. Thanks again.

NAGI PRABHU: Thank you, everyone.