2. Personalized Support: AI can focus on individual patient needs, improving treatments and offering tailored medical and financial assistance. 

3. Optimized Healthcare Systems: AI can streamline logistics, supply chains, and resource allocation, ultimately making healthcare systems more efficient. 

4. Error Reduction: AI helps reduce medical errors due to misdiagnosis or incorrect medication dosages, enhancing patient safety. 

The Cons of AI in Healthcare 

1. Job Displacement: Automating certain tasks with AI can lead to job displacement among healthcare professionals. 

2. Integration Challenges: Integrating AI systems into existing healthcare infrastructures can be costly and require significant workflow changes. 

3. Bias Concerns: AI algorithms might inherit biases from the data they are trained on, raising legal and ethical questions. 

AI Improving Healthcare Access in Action: Atlas Health  

Atlas Health uses AI to streamline the enrollment process for patients in various philanthropic aid programs. Their AI plays a critical role in the following aspects: 

1. Automation: AI processes data and uses machine learning to predict patient eligibility for specific programs and their potential benefits. 

2. Predictive Analytics: AI predicts the value of enrolling a patient in a particular program, both for the patient and the provider.  

3. Robotic Process Automation: AI helps monitor numerous programs to serve up the most eligible and available program for the patient.  

The Future of AI in Healthcare 

As AI technology advances, it is expected to play an even more significant role in healthcare. Despite concerns such as job displacement and ethical issues, AI has the potential to empower patient advocates and make healthcare more transparent and affordable. 

AI is on the brink of significantly reducing the financial burden associated with healthcare. As AI evolves, it holds the promise of making healthcare more accessible and affordable, especially for those facing serious medical conditions. 

Resources and Recommendations: 

• Explore AI-powered solutions like Atlas Health to streamline access to financial aid programs 
• Stay informed about AI applications in healthcare to make the most of emerging opportunities 
• Consider potential job roles and training opportunities in AI-related fields within healthcare 
• Keep a close watch on AI adoption in healthcare, as it promises to improve patient outcomes 
• Share this information with others to spread awareness about the potential of AI in healthcare 

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[00:00:45] Stephen: I think the applications for AI and health care are just going to be incredible. We’re touching a lot of patients; we’re providing a very real assistance to these patients. I mean, the first year out there we, essentially were able to provide about 3 million dollars’ worth of benefits to patients, which is, that’s what we’re here for.  

[00:01:09] Allie: If you’ve been listening along to this show, it’s no surprise that the financial aspects of healthcare can be burdensome, frustrating, and at times devastating. It can feel like no one can help and there’s little opportunity for relief.  

[00:01:27] But what if I told you that there were over 20,000 philanthropic medical financial aid programs across the country that fund patient care. You’d probably say that’s great, but how do I find them? And even if I did find a program that worked for me, how would I know if I was eligible?  

[00:01:48] I know I’m not alone when I say that I’ve spent hours upon hours on the phone with hospital billing departments and online searching for best practices surrounding financial relief on medical bills. But could there be a better way?   

[00:02:06] Hello and welcome to The Hidden Costs of Health. In this show, we’re exploring the burden of medical expenses in this country and how a health event can quickly spiral into financial toxicity.   

[00:02:20] I’m Allie Sandler, a producer for Empowered Us.   

[00:02:26] [Music Ends]  

[00:02:26] Artificial intelligence has become one of the phrases I hear all over the place now. From conversations at work to casual chats with friends, AI platforms like ChatGPT are changing the way we work and communicate with one another. The landscape for this type of technology is changing constantly. So, it was only a matter of time before AI was leveraged in the healthcare industry.  

[00:02:53] Like any technology, artificial intelligence has it’s pros and cons in the early adoption phase. Let’s start with the pros. [Music] AI can process and analyze large amounts of medical data quickly and accurately, helping healthcare professionals make faster and more informed decisions. It can focus on individual needs, improving treatments and providing personalized support for medical and financial assistance.  

[00:03:27] AI can optimize healthcare logistics, supply chains, and resource allocation,  helping healthcare systems run more efficiently, which can potentially lower costs. AI can help reduce medical errors caused by misdiagnosis and incorrect medication dosages, improving patient safety.  

[00:03:49] [Music Ends]  

[00:03:49] There is no denying that AI has a lot of potential benefits on the horizon, but it’s important to consider the possible negatives as well. [Music] First off, and perhaps the largest concern, the automation of certain tasks by AI may lead to concerns about job displacement for some healthcare professionals. And while it may enhance healthcare, it can’t replace the human element of care. 

[00:04:16] The adoption and integration of AI systems into existing healthcare infrastructures can be costly and may require significant changes to workflows and processes. Finally, AI algorithms can inherit biases from the data they’re trained on. Which may raise legal and ethical questions.  

[00:04:38] [Music Ends]  

[00:04:38] It’s clear that AI is on the upswing, so I wanted to speak to someone who’s using this technology in healthcare systems and get a little more insight on how it actually works. 

[00:04:48] [Music]  

[00:04:50] Ethan: My name is Ethan Davidoff, and I’m the founder and CEO of Atlas Health. 

[00:04:54] Allie: Atlas Health is a company that streamlines the enrollment process of patients in diverse financial aid programs, assisting in fund flow from philanthropic aid programs to care providers. They address challenges arising from the variability of program criteria, data sources and the need for coordination among various healthcare groups, ultimately easing patient access to these programs and affordability solutions, especially for chronic conditions like cancer.  

[00:05:25] [Music Ends]  

[00:05:26] Ethan: So, where AI comes into play is first with really just automation, accessing all of the data and using machine learning, which is a type of AI to really make predictions on the probabilities of what patients are going to be eligible for what programs or what the best programs are for that particular patient in that moment in time. 

[00:05:50] In addition, predicting what would the reimbursement value of getting a patient into that program mean for that patient in terms of their treatment and the provider getting reimbursed. So, leveraging machine learning is really the core of how we think about applying AI to solve this problem. So, that’s kind of the, the nuts and bolts of machine learning and predictive analytics and how we apply them at Atlas. 

[00:06:15] The second use of applying AI is what we call robotic process automation, and this speaks specifically to how do you keep track of tens of thousands of programs that are changing over time. We’re really looking at leveraging all of the breakthroughs in large language models. And what most people are thinking about with ChatGPT and being able to write very unstructured prompts, asking AI to do things for you, we’re applying that from the perspective of a patient advocate or a financial counselor in order to help them help more patients get into more programs in less time. 

[00:06:55] So, when there is a challenging step in the process, instead of a patient advocate maybe going and asking for help from a, a colleague or their boss, etc., they can now ask questions of that AI and can help them complete that task to help move the patient forward through an application and ultimately in enrollment and getting support. It’s a very exciting time in the industry and just an incredible opportunity to really empower patient advocates and help more patients access these programs. 

[00:07:29] Allie: Can you tell me about how this technology actually works?  

[00:07:33] Ethan: Let’s say you had an appointment at your local health system, cancer center, and they said, you have cancer and here’s your treatment plan and your first round of chemotherapy is going to be next week, what would happen is the next day you would get an outreach and it would be the health system reaching out to say, we’re reaching out about your chemotherapy appointment next week. 

[00:07:55] Based on the data we have; we’ve determined that you’re eligible for a nonprofit foundation to help cover the cost of your chemotherapy. This is a free service that us as the health system provides to the community and if you have a couple minutes and you want to take advantage of this, we can do it right now over the phone.  

[00:08:13] And behind the scenes, really what’s happened is once you’re diagnosed, we’re looking at your clinical data, your insurance data, your demographic data, your financials and we’re proactively matching you up and enabling really the provider to reach out and help their patients and fulfill their mission. Right?  

[00:08:31] So, I think the stats are something like there’s over 400 billion dollars annually in patient out of pocket expenses, right? So outside of insurance, what patients or consumers have to pay. And when you really break it down, there’s really only two ways to solve that problem. Either the patient pays or somebody else does. We focus on the latter. We call it medical financial aid or more specifically philanthropic aid, right, connecting these foundations to these patients. 

[00:09:02] So, when it comes back to machine learning and AI, given there’s only so many dollars on the supply of aid and there’s so much demand for that aid, the real kind of key moment or key opportunity for the market is really leveraging AI and machine learning to match the right patient to the right program at the right time that’s going to have the biggest impact on their clinical outcomes. 

[00:09:35] And for a lot of patients, this is the difference between life or death. There are so many stories of patients that are choosing to stop treatment because they can’t afford the bills or for fear of the bills, or there’s so many stories of patients not even getting checked out with labs or diagnosed because they assume they can’t afford health care. 

[00:09:59] And so with machine learning, with AI, making this more transparent for the entire ecosystem, automating more of the steps so that more of the dollars can go directly to patients and providing that transparency, I think that’s really the North Star on how we’re going to make real impact in this market, and for patients and their families.  

[00:10:23] Allie: How do you predict we’ll see AI show up in healthcare systems in the years to come.  

[00:10:28] Ethan: There’s so much innovation and so many amazing projects to be done integrating with hospitals and health systems that there is, there’s a queue. So, I don’t think it’s a question of “if”, I think it’s more a question of “when”, and I think what we’re seeing is that you really have to have a value proposition that is extremely compelling on all cylinders. 

[00:10:55] It has to improve clinical outcomes. It has to advance health equity. It has to reduce total cost of care. It has to drive patient experience. It has to drive cash and revenue and lift, right? And so, the projects that can touch on all of those key initiatives, that are really going to be the key things for hospitals over the next 10 or 20 years. 

[00:11:21] There is an incredible opportunity here to bring philanthropic aid closer to patients and hospitals and enable all of the players in the market to come together and efficiently get this aid to patients and solve some of the really meaningful access and affordability challenges that plague [Music] our most vulnerable populations. 

[00:11:46] Allie: All of this sounds like a huge step in the right direction for healthcare affordability. Essentially Atlas Health is using AI to tackle a critical issue that could make a real difference for patients all over the country. So, I wanted to speak with someone who’s integrated Atlas Health’s AI tech into their hospital to learn how it actually works in practice and what it’s like to bring new tech into an established healthcare setup.  

[00:12:14] Stephen: My name is Stephen Forney and I am the Senior Vice President and Chief Financial Officer for Covenant Health.  

[00:12:21] [Music Ends] 

[00:12:22] I had exposure to Atlas, my previous job before I came to Covenant. And so, when I got out to Covenant, I went and looked at our hospitals to see if we were doing anything around philanthropic funding or philanthropic aid, and we weren’t.  

[00:12:38] It was obviously part of our mission to provide aid where we could, but we weren’t doing anything around picking up this additional funding. We had other areas covered, we had a very robust Medicaid or traditional financial assistance programs put in place, but like this niche, this hole was not covered. 

[00:12:58] And so, I had introduced Atlas, had Ethan come up and, you know, you’re telling me that we can automate it and we don’t have to do really anything. You’re going to staff it, and we just have to coordinate with our pharmacist. And he’s like, let’s do it. 

[00:13:14] Allie: What was it like integrating a new AI system into your hospitals? Was it difficult?  

[00:13:19] Stephen: It really was not, as far, as you know, this sort of thing, bringing in a new process or a new service and integrating it. This actually, a scale of 1 to 10 with 10 being super difficult, this was probably about a 4. Fairly easy, especially in our case, because we took what we call like a turnkey solution. 

[00:13:41] It’s Atlas staff that really interacts with their software, and that staff also goes into our systems, and they basically get a data feed. They get scheduling information, here’s individuals that are coming in, here’s what the prescription is, the type of drugs they’re going to need. 

[00:14:00] And they then take that information, do all the work in their system, and then do all the interactions with the patient in order to get them qualified. From a process perspective beyond that, they then interact with our revenue cycle team, but it’s a hey, guess what, we’re getting free drugs for Mrs. Smith, so you don’t bill for them. 

[00:14:25] AI, it scares the daylights out of pretty much everybody in healthcare. I, I’m very bullish on it. This was, I felt like this really was a good use case for, hey, this is a great way to manage 20,000 different programs and optimize getting people into those programs. 

[00:14:49] Allie: As someone who works daily in the healthcare system, where do you think AI is going, both in your hospitals and medical facilities as a whole? 

[00:14:58] Stephen: Right now, we’re looking at possibly using AI for some of our simple coding solutions, visit coding and things of that nature, and augmenting what the physician can do. I pointed out, I’ve said it a couple of times internally, that I think, I would say that within the next five years, any medical specialty that ends in ology or ologist is going to be supplanted by AI. Because if you think in terms of, say radiology, it’s pattern recognition. That’s exactly what generative AI does. Or pathology, it’s pattern recognition.  

[00:15:37] I think the applications for AI and health care are just going to be incredible. I know Kaiser is using AI out in California at the bedside. Basically, the AI is checking the monitor for anything, any patterns that could be problematic and then alerting nurses. Again, I think that’s fantastic because that’s one of the challenges, is how do you extend nursing staff? 

[00:16:03] The other side of that is, wait a minute, you’re cutting out nursing staff. So, I think there’s going to be a lot of those discussions. I think as a whole in the industry, I think you’re going to see organizations like some larger, well-funded organizations maybe being at the forefront of using AI in a broad sense. I think community hospitals, smaller systems, you’re going to see them try to be mid to late adopters with various products, and they’ll start slow.  

[00:16:36] Allie: So, obviously there are pros and cons, but I’d love to hear a story about how Atlas health and utilizing AI helped one of your patients. 

[00:16:45] Stephen: We had a patient who was Medicare fee for service, didn’t qualify for Medicaid, and she was in treatment at the facility. But she also had outpatient drugs that we should be getting from a specialty pharmacy that she couldn’t afford because the copays were going to be astronomical for her. Because the thing was if she didn’t get that other medication, she wasn’t going to be able to continue the treatment that she needed at the hospital. 

[00:17:17] They both had to go together, but we didn’t have a way to really help that because it wasn’t a hospital provided service. Atlas got her qualified, and so therefore she was able to continue in her ambulatory setting and then continue the other treatment that we were doing at the hospital. We’re touching a lot of patients, we’re providing [Music] a very real assistance to these patients, you know, which is, that’s what we’re here for. 

[00:17:49] Allie: It’s clear that artificial intelligence possesses the potential to serve as a vital tool in relieving patients from crushing financial strains for medical bills. It’s ability to process extensive medical data sets, tailored treatment plans and optimize an intricate web of logistics is transforming healthcare systems.  

[00:18:11] Both Ethan and Stephen anticipate that this technology’s existence will inevitably be integrated into medical practices and hospitals nationwide. In the years to come, we can anticipate that AI will become an indispensable asset within the realm of healthcare as it enhances health equity and benefits patients and their families. 

[00:18:34] We understand that a lot of people learn in different forms, so there will be a corresponding blog to this episode where we fully define the terms and also provide different tips and resources, whether they were mentioned today or in addition to that. So, check it out on empoweredus.org. We’ll link it in the show notes.   

[00:18:52] Also, if you found this episode to be informative and impactful, please share it with anyone else that you think may need to learn about this. It may fill in some of the gaps of their knowledge.  

[00:19:04] We at Empowered Us are committed to advocating for affordable healthcare for all. We look forward to continuing these conversations with patients and experts to both educate and create new solutions. Let’s keep pushing for change together. Take care and see you next time. 

[00:19:23] [Music Ends] 

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