Podcast | Healthcare (HC)

Connected Intelligence: Mosai’s AI-Powered Platform for Home-Based Care

January 22, 2026

THL’s Healthcare in Action, Season 2, Episode 1

As demand for home-based care surges, healthcare providers are under increasing pressure to deliver the right care at the right time with fewer resources. In this episode, Jon Lange speaks with Elliott Wood, CEO of Mosai, about how AI and predictive analytics are transforming home health and hospice care. Newly formed from the merger of Medalogix and Forcura, Mosai offers an intelligent care coordination platform that empowers clinicians with real-time insights to optimize care delivery and outcomes. Jon and Elliott discuss how generative AI and predictive modeling are helping providers improve efficiency, tailor care to each patient’s unique needs, and ultimately drive better outcomes. Elliott also reflects on mission-driven leadership, personal experiences that shaped his approach, and the importance of getting care right, particularly for vulnerable populations.

Key Takeaways:

Mosai helps providers determine the optimal level of care for home health and hospice patients with AI-powered insights.
Predictive models support clinicians in aligning on care plans and adjusting for risk and patient needs.
Generative AI is being used to automate clinician research, saving time and enhancing decision-making.
The shift to value-based care and reimbursement makes care planning more important than ever.
Mission-driven leadership, combined with innovation, is essential to driving better solutions in healthcare and healthcare technology.

[00:00:00] Elliott Wood The end of life is such a critical point in a patient’s life to get care right. And we either do or we don’t. And if we do, my experience is it creates this just amazing experience for the patient and for their family, and one that they are very grateful for. And so the driving mission, while obviously we’re spending a significant amount of time with our customers and ensuring what they have to achieve value, we are still, really as a company, focused on the patient and trying to ensure that that patient makes their way home.

[00:00:41] Josh Nelson That’s Elliott Wood. He’s the CEO of Mosai, and I’m Josh Nelson. I’m the Head of Healthcare at THL Partners. This is Healthcare in Action. It’s a podcast that explores the latest developments and innovations transforming the U.S. Healthcare sector, from cutting-edge technology to thoughtful approaches to patient care. I’m here with my colleague, Jon Lange, who will lead us in a conversation about the latest innovations in technology and AI for home-based care. And how new solutions are driving deeper insight, greater efficiency, and better outcomes for patients. Jon, take it away.

[00:01:17] Jon Lange Thanks, Josh. Today, we’ll look at a part of the healthcare system that’s undergoing rapid transformation. The technology, AI, and predictive modeling that are powering home-based care. As patient needs grow more complex, payers tighten margins, and providers face mounting operational pressure, data and AI are becoming essential tools for understanding how to deliver the right care at the right time. Few companies have been as early or as influential in this shift as Mosai. The recent combination of MedaLogix and Forcura. In this episode, I spoke with Elliott Wood, Mosai’s CEO. We discussed the thinking behind the recent merger, how Mosai unifies patient information into a clearer, actionable picture, and how its end-to-end platform brings connected intelligence to home health and hospice providers. Elliott twalked through real examples of how predictive models, workflow automation, and generative AI are helping clinicians coordinate care, optimize utilization and improve outcomes for managing risk to determining how to provide the right care and the right amount of care to address a patient’s needs. We also talked about the broader home-based care landscape, the aging population, shifting reimbursement models, tightening labor supply, and why technology partners who can distill sprawling data and generate actionable insights are becoming increasingly important in driving both higher reimbursement and better care for patients. Elliott shared lessons on mission-driven leadership, the importance of innovation, and personal experiences that keep him focused on using technology as a powerful tool to make patients’ lives better. So let’s get into it. Elliott, thanks so much for joining me.

[00:02:55] Elliott Wood It’s great to be here. Thanks for having me, Jon.

[00:02:58] Jon Lange For those who aren’t familiar, can you tell us a bit about Mosai?

[00:03:02] Elliott Wood Absolutely. So Mosai is the strategic combination between two companies for Forcura and MedaLogix. And so each of these companies has been providing software solutions to home health and hospice companies for about 10 years. And so the combination of these two companies into what is now Mosai was a strategic merger that occurred this year in March. Mosai at its core is an intelligent care coordination platform. And we are taking data and people and processes and uniting those together to try to help patients receive the right care at the right place at the right time. And what that means in real life is we are helping clinicians understand how much care should be provided to a patient, is there risk changing over time, are we sending an appropriate order to the physician, are we getting that order back from the physician. And so each of the like points in time where a clinician is making a decision about a care plan, Mosai is showing up at that point in time to offer either a suggestion or additional information that would help the clinician make the best possible decision for that patient.

[00:04:31] Jon Lange For those who aren’t spending all their time in the home-based care market, can you just frame up the landscape a bit? What are some of the key challenges that providers are facing? And how do your offerings help with that?

[00:04:44] Elliott Wood Sure, absolutely. So one is receiving care in the home is the preferred destination of care, especially for patients who are older. And these older patients are becoming more complicated. Two, there is significant challenge with payers for our customers whether it’s traditional Medicare where it’s Medicare advantage margins are tightening. And then three, there is massive consolidation happening in the space. And so you have a patient population changing. You have financial pressure. You have operational challenges. And all of those issues are stacking on top of each other. And so as a software company, it is critical that we are helping our customer be more efficient, and not only be more efficient, but ensure that while they’re being more efficient, they are providing the optimal amount of care. And that is the sweet spot that we’re endeavoring to help our customers.

[00:05:51] Jon Lange To make it even more concrete, if you take an example of a home health provider, what were they doing, say, five years ago before a partnership with you? And how does the intelligence that you provide allow providers to improve patient care and optimize reimbursement?

[00:06:11] Elliott Wood Sure. So a great example of this is how we are able to provide simply a recommendation around how much care is likely needed for the patient. So before these predictive models were created, before they were delivered to the clinician, often what was happening is the clinician is going into the home, they’re doing their initial assessment of as, let’s say, an RN, as a nurse. And that RN is doing their assessment and then coming up with a plan of care in a vacuum today. Two or three days later, the therapist comes in to do the therapist assessment. They are coming up with a plan of care from a therapist’s perspective. And what we find is in most cases, the nursing team and the therapy team are not on the same page about what the plan of care is. And so, as we have now shifted to more of a value-based approach in PDGM and with value-based purchasing, our customers are having to be very intentional about how much of that utilization is necessary for that patient to achieve a good outcome. And so what we are doing is now incorporating these analytics into the workflow. After the clinician has done their assessment and providing a recommendation around what is essentially a budget of how many visits are likely necessary for this patient over the course of the next 60 days, and the nursing team and the therapist are now having an interdisciplinary conversation around how do we work together as a nursing team as a therapy team in order to provide the most efficient but also best care possible for this patient. And what we found because of that care coordination is the delivery of care is often more coordinated and more tailored to what that patient needs from their agency during their episode.

[00:08:24] Jon Lange Got it. And I think this is such an interesting application of data and AI, because fundamentally, this is a really hard problem. You’re sort of trying to answer the problem of how much care does this patient need to get a good outcome, while at the same time, not providing too much care, right unnecessary burden to the system. And, you know, without going and all the details. There are regulations around this. And payers try to do some of this themselves and say, well, you need at least X, but you shouldn’t provide Y because that would be too much. That’s too much utilization. And what you’re doing is making the conversation more accurate and more data-driven rather than just a nurse and a therapist saying, well, this is our best guess. You’re giving them the tools to say, based on all of the data we have and all of prior experience we have, this is the absolute best guess based on the data of what will get the best outcome.

[00:09:22] Elliott Wood That’s exactly right. And I think part of the challenge for our customers today is before PDGM and 2020, they were paid to do visits. They were paid for the volume of care that they provided. Once PDGM occurred, it flipped that dynamic so that they were paid essentially episodically, but ultimately for the outcomes that they were generating. And so you have a financial dynamic that’s changing for the customer, but then layer on top of that financial dynamic, that is new, a labor shortage in the industry. And so, for a variety of reasons, our customers cannot afford to over-utilize for patients who don’t need the care, but they also can’t afford to underutilized for patients, who do need more care. And so what this capability is really intended to do is help them navigate to the best answer. And I think it’s important also to note this capability is intended to be support. So it isn’t replacing the clinical judgment that isn’t replacing the clinician’s experience or their education. It’s intended to be like a fourth leg of that stool, right? And how do you tie all of that together so that the patient is getting the care plan that they need in order to be successful?

[00:10:54] Jon Lange And I think this is such an interesting cutting edge of healthcare, because of course, there’s been so much talk over the past 20 years about value-based care. And I think one thing you’re getting at is it’s really easy to optimize for fee for service. You just provide more service, and you sort of hope that value is being provided and outcomes will be positive, but it’s an easy reimbursement model. But when you try to shift to value, when the whole system is trying to provide the best value and the best outcomes, that raises a really hard question which is what is value? What is the level of service, level of utilization to get good outcomes without providing too many services to add cost to the system? And one thing you’re doing is really enabling that conversation.

[00:11:42] Elliott Wood Absolutely.

[00:11:44] Jon Lange It’s impossible to know how to provide value-based care unless you have some data on what value even means.

[00:11:51] Elliott Wood Right. And I would say, to the value is implicit in the service line and ultimately what our customer is charged to do. And so in home health, the charge to the home health agency is we need to take these patients that are being sent to us and provide care to them that stabilizes them so that they can return successfully back to the community and be independent. And hospice, it’s a little different. You have a very similar challenge, but you are optimizing to a different outcome. And so understanding the status of this patient in hospice what their likely length of stay is, if we believe that next week is likely to be their last week, hospices can now with these models optimize the utilization of their providing so that a patient in the last week of life has someone with them every day. And we know that that is important because bad outcomes and hospice happen when you are in the patient’s home with the family every day in the last week of life. And so there is an opportunity to take the resources that we have and with this information schedule them appropriately so that we’re helping these patients achieve the best outcome possible.

[00:13:18] Jon Lange I think there is this interesting common thread between hospice, between home health and probably many other specialties as well, which is there is an optimal level of care. And, you know, patients don’t want a nurse in their house every day all the time when they’re not needed. And the outcomes aren’t better if you overutilize. At the same time, you want a provider to be helpful. You want a provider to provide service when you need it to provide the best outcome. And so what you’re doing is bring to bear the right data at the right time with insights and AI on top of it, to support the provider to make the best decision to get the best outcome to provide the best care. And by the way, there’s an overlay of if you’re doing that, then payers will reward you and reimburse you even better.

[00:14:14] Elliott Wood Yeah, absolutely. I would say in a joking manner, my grandmother doesn’t want me in her house every day, right? And so if she doesn’t want me at her house every day. These patients don’t want clinicians in their house every day. And in some cases we see just without intelligence, such poor scheduling practices where there are some patients who not only do they have an overload of like clinicians in their home throughout the week, they may even have an overload in their own in one day. And so we see cases all of the time where you have multiple types of therapy being scheduled for a patient on the same day. And so our products in a lot of ways are really trying to find that optimal amount, not only to ensure that the agency themselves has a good kind of outcome with an episode, what did the patient and their experience of that care is a good one.

[00:15:20] Jon Lange Elliott, you guys have really been pioneers in bringing data and AI to bear to improve care and drive efficiency at providers. And you guys were doing it really even before it was cool, even before this genAI revolution. So can you talk about what was the idea behind that? How did you guys get into it so early? And what are you most excited about on the horizon for AI and in particular generative AI to drive even better outcomes in the future?

[00:15:51] Elliott Wood Sure, what we found very early on was there was a huge void for analytical solutions for our customers, and where we really developed the most traction early was helping our customers who had home health and hospice identify when they had a patient who was on home health who was actually likely to pass away. And so that became our very first solution, I would say, in the market that became broadly adopted. And it was because humans and even experienced clinicians have trouble seeing the markers of decline early enough to make a difference in that patient’s stay on hospice. And so the first solution really for us 12 years ago was helping the customer solve that problem. We have continued to develop those types of solutions that are more modeling based where we’re predicting outcomes and then we’re helping the customer understand how to use those predictions like risk of hospitalization or risk of mortality in a way that involves their understanding of what the care plan should be. But one of the challenges and this is like, I think where the excitement around generative AI comes into play is often when we are making a recommendation and or providing insight to risk that triggers workflow that requires the clinician to then go do more research about, okay, well, what should I do about this risk, or this patient may be likely to pass away, but are they actually hospice eligible? And so what we’re finding in terms of like early successes with generative AI is that we can do that research for the clinician. And so we are providing the either recommendation or the notification about risk. We are then going and doing the research for the clinicians, which is saving them a significant amount of time. And then also ensuring that they are achieving the outcome that they want to achieve with the patient.

[00:18:14] Jon Lange Maybe switching gears, you are the leader of a really innovative healthcare IT company. For someone aspiring to be a leader in a similar company and aspiring to really make a difference in healthcare, what qualities do you think are important or what experiences should they pursue to really make an impact?

[00:18:34] Elliott Wood I think this is true in any industry with any company understanding why the company exists. What is the mission of that company? What difference is the company attempting to make in the world? And then as you’re like interviewing with that company trying to understand do they believe in that mission? Has it permeated down through the organization in a way that is more than just like a marketing slogan? Is it true that the team and that company are waking up every day in order to further that mission? And so I do think that that while maybe cliche I believe that companies who not only have a strong mission statement but believe it outperform companies who don’t. So that would be one. I think the second is when you’re evaluating companies, are there innovative people in the company? Because usually people who are innovative want to work with other people who aren’t innovative. And so there is a multiplier effect that happens when you believe in your mission and you’re following it, but you’re also really building your team full of people who are not only capable but want to work in an innovative space. And so that I think those would really be the the two that I would offer.

[00:20:06] Jon Lange And maybe flipping it, as the leader of a mission-driven organization, how do you foster that mission-driven culture? Are there things you can do to make sure you’re hiring, setting the right tone to advance that?

[00:20:22] Elliott Wood So you have to talk about your mission frequently. Because as a leader, if you aren’t talking about your mission, then your team will think that you don’t care about it. And so at Mosai, we spend a significant amount of time talking about the mission and why we’re here and why we’re doing what we’re doing. We also spend a lot of time talking about our values as an organization, and we try and weave values into who are the people that we hire, who are the people we promote. And so I would say key questions around whether or not people should be on the bus or should not be on the bus are largely driven not just by their skills and their capability, but do they uphold the value system that we’re trying to create at the company?

[00:21:20] Jon Lange And as you think about mission, are there any personal stories that have been really impactful to you that have driven you to be part of this company, to lead this company and to drive it forward?

[00:21:32] Elliott Wood Sure. So I have multiple grandmother stories, and maybe without diving too deeply into like either one, I would say I have one grandmother who had a fall, and after her fall had a very bad experience going through the post-acute system, and ultimately ended up living the last probably 50 of her 55 days in patient rehab facility as opposed to being at home. I have another grandmother who fell, went to the hospital, and went immediately home. And not only made her way through that injury but she was able to get better and recover and become independent again largely because of my customers today. And so I think most people who work at Mosai have a similar experience, whether that’s with a grandmother, a parent, a friend, where the end of life, and especially when we’re taking care of patients who are aging, it is such a critical point in a patient’s life to get care right. And we either do or we don’t. And if we do, my experience is it creates to this just amazing experience for the patient and for their family, and one that they are very grateful for. And so the driving mission, while obviously we’re spending a significant amount of time with our customers and ensuring what they have to achieve value, we are still really as a company focused on the patient, and trying to ensure that that patient makes their way home.

[00:23:31] Jon Lange It’s so simple and yet so powerful. And as you say, we all have these stories reminds me of stories in my family. But you’re bringing all of this data to bear in all of these quite sophisticated machine learning and AI tools to make the right decision to help support clinicians as they’re grappling with these issues. But exactly as you said, it comes down to are we making the right decisions or the wrong decision at a critical point in care for someone who is very likely vulnerable, maybe even at the end of life. It’s just so important to keep that in mind. And when you get it right, that’s when you know it’s meaningful and you’ve made a difference.

[00:24:10] Elliott Wood Yeah, absolutely.

[00:24:12] Jon Lange Elliott, what excites you most about the path ahead for Mosai?

[00:24:17] Elliott Wood So we brought these companies Forcura and MedaLogix together because we believed we could do bigger things, have a bigger mission, as one company as opposed to two companies that we’re partnering together. And so, I am excited that we now have an end-to-end platform where we can provide these insights about patients to clinicians. And, so, while we have focused historically on home health and hospice really with both companies, we also see as a combined and platform an opportunity to elevate our, I would say, our customer stature with their upstream partners. Whether that is health systems or SNFs or physician groups, we are really excited about the opportunity to work across those lines and have this patient information that’s critical to understand with other stakeholders in the healthcare industry.

[00:25:21] Jon Lange Elliott, thank you so much for joining me today.

[00:25:23] Elliott Wood It’s always a pleasure. Thank you, Jon. Thanks for having me.

[00:25:28] Jon Lange As we wrap this episode, I’m joined by my colleague Andrew Garske, Vice President in the Technology and Business Solutions Group at THL. Andrew, one thing that came through in the conversation with Elliott was just how much technology has the potential to change the landscape for home-based care. Can you talk about how you’re seeing that from your vantage point as an investor?

[00:25:48] Andrew Garske So I think about it in two ways. One is from a societal perspective, there is just a tremendous unmet need and a lack of clinical workers and caregivers to really meet that need, given the increased demand for aging in the home. And then, as you can imagine, from an investing perspective, that creates tremendous opportunities to find ways and solutions that actually are able to meet those needs. And part of that imperative is using technology, because there’s truly just are not enough people and trained clinicians to actually serve the demand today. So that gets me really excited, both one from a societal perspective, this is just you’re doing good in the world and providing better care in the right setting at the right time. And then there’s also from a business and technological perspective, a lot of challenge in finding ways and new models that actually make that happen in the real world.

[00:26:39] Jon Lange Andrew, as an investor, given the pace of change, particularly in AI, but also in other new emerging technologies, how do you evaluate these companies? How do you get a sense of who will be the winners in this new technology regime?

[00:26:52] Andrew Garske And the pace has certainly accelerated in the past couple of years. So maybe two key elements that we look for. One is the ability to have ongoing and sustainable access to different sources of data and the ability to actually integrate and make sense of all that data in a way that takes burdens off the customer base. And then a second component is really what is your pace of innovation and ability to adopt and deploy the right new technologies against the right use cases to actually deliver value to customers. And then how thoughtfully aligned is your ongoing roadmap to that? And I think that’s the thing where companies really differentiate is that pace of innovation, but then aligning it with the commercial and customer pain point value propositions.

[00:27:37] Jon Lange Finally, Andrew, given what you’re seeing in the market, what makes you most excited about the future of home-based care technology and the potential for technology to drive care and experience and outcomes forward?

[00:27:51] Andrew Garske I think maybe the most exciting thing coming back to where we started is the role that technology has to play in just providing care in a distributed environment to the millions and millions of people who are underserved today. And I think uniquely technology and these tools have an ability to keep the human element of care delivery. You know, you think about someone coming into your home, it’s immensely personal. But today those clinicians spend a lot of their time figuring out, you know, what’s my round? What are my shifts. Am I in the right place? And also spending time on documentation, making sure that they get paid. And technology can play a critical role in really freeing that person up to spend more time on patients and really driving efficiencies, while also introducing new care models such as virtual care management and just really making the current clinical workforce a lot more extendable and scalable, which is a huge societal imperative as we look at 20 years.

[00:28:45] Jon Lange Andrew, thank you so much for joining me. Really appreciate it and look forward to continuing the conversation with you and with Elliott very soon.

[00:28:53] Josh Nelson Thank you, Jon.

[00:28:55] Jon Lange Thank you for listening to Healthcare in Action, brought to you by THL. To help Healthcare In Action reach more listeners like you, either share this episode with a colleague, subscribe to the show, or rate and review us on Apple Podcasts. And for more background on THL’s Healthcare Vertical, visit thl.com/verticals/healthcare.