This article is sponsored by ExaCare. It is based on a discussion with Jody O’Mara, Chief Nursing Officer at Journey Healthcare, Laird Russell, Founder & CEO at ExaCare, and Ein Findley, Business Development Director at ExaCare. This discussion took place on February 17th, 2025 at the SNN Clinical Conference.

Laird Russell: I am the founder of ExaCare. We started about three years ago. We’re an AI company that helps screen referrals coming in from hospitals, helping you make better decisions clinically and financially. We’ll dive deeper into that, but first, I’d love for the other two to introduce themselves.

Jody O’Mara: My name’s Jody O’Mara. I’m the Chief Nursing Officer for Journey Healthcare, located in Noblesville, Indiana. We have 22 SNFs across six states.

Russell: I’m the Director of Sales here at ExaCare. Great to meet you all, and thanks for having me. Perfect! All right, let’s kick this off. Let’s start with a basic question: what is AI? Any thoughts from the audience on what AI is before I jump in?

Ein Findley: AI is essentially a set of advanced technologies designed to mimic human cognitive functions like logic, reasoning, deduction, and problem-solving. It processes large sets of data quickly, accurately, and in an actionable way.

From my conversations with other executives like you, what I hear most often is that AI empowers staff members to make faster, more informed decisions. A good analogy would be this: Jody, if you and I were having a conversation but I was staring at my phone the whole time, that would be like a keyword search—just scanning for specific words without true engagement. But if I were actively listening and then, in our next conversation, I said, “Hey Jody, tell me more about what your kids were doing last weekend,” that would show I retained information and am building on it. AI does something similar in the healthcare space—it builds on previous interactions to improve decision-making, whether clinically, financially, or operationally.

Russell: Jody, one of the biggest challenges we hear in the industry is trying to get to “yes” more often—helping providers accept more patients while maintaining quality care. How do you see AI improving your team’s ability to say “yes” to more patients?

O’Mara: Absolutely. AI is amazing. We deal with 100-page referrals filled with cumbersome information, trying to extract critical details like diagnoses, special equipment needs, and high-cost medications. AI helps condense all that down to just two pages. It’s efficient, fast, and structured, making it much easier for nurses to process than the traditional way of handling referrals.

Russell: Do you have any examples of how AI has allowed even less clinically trained staff to take on more of the workload or capture important details during the intake process?

O’Mara: Definitely. Previously, only DNSs, EDs, and maybe MDSs were reviewing referrals. Now, with AI, we’ve expanded intake to include central intake teams, ADNSs, and unit managers. We also revamped our referral process—we used to classify cases as green, yellow, or red. AI has allowed us to shift a lot of “yellow” cases into the “green” category, making intake much more efficient. As a result, we now accept about 90% of referrals through central intake, with minimal need for DNS or ADNS review. It’s significantly faster, and more staff members can process referrals. Plus, the referral documents are now 24 pages instead of 100.

Russell: We hear a lot about administrative burden, staff turnover, and burnout. Does AI help alleviate those issues by reducing the more cumbersome parts of the job?

O’Mara: Absolutely. We’re always adding tasks to everyone’s plate, but no one wants to start their day with a 100-page referral—or worse, a 250- or 350-page one. AI removes a lot of that burden. Staff are constantly getting interrupted—risk meetings, compliance meetings, being pulled away from their work. By using AI to streamline referrals into 24 structured pages, we see much higher staff buy-in. When something is simple and easy to use, people embrace it.

Russell: Shifting gears a bit—beyond referrals, AI can play a role in other aspects like reimbursements. What are some areas where operators are excited about AI’s ability to simplify complex administrative tasks?

O’Mara: The best way to sum it up is confidence. AI gives operators more confidence in decision-making, whether it’s case managers, social workers, admissions teams, MDS teams, or administrators. Post-intake, AI helps alleviate burdens by standardizing processes and improving accuracy. AI is also being used in predictive analytics to reduce rehospitalizations and optimize patient care. It’s about peace of mind, oversight, and operational efficiency.

Russell: On the data analytics side—Jody, if you could capture the perfect data set to better understand your patient population, how would that impact how you design specialty units or expand operations?

O’Mara: Right now, we’re essentially shooting in the dark when deciding whether to open a hemodialysis unit or certify a heart failure unit. AI analytics let us see that, for example, 40% of our population has end-stage renal failure or a high prevalence of heart failure. That data helps us make informed decisions—maybe next year’s capital project should involve partnering with the American Heart Association to create a certified heart failure or COPD unit. For us, as a newer operator in six states (soon to be eight), AI provides a much faster way to understand the needs of each community.

Russell: Speaking of partnerships, how does AI help with hospital network partnerships and becoming a preferred provider in new markets?

O’Mara: We receive a high volume of referrals in Georgia, and hospitals appreciate that we’ve invested in AI to expedite our acceptance process. Our response time is significantly faster than previous operators, and hospitals have given us great feedback.

Russell: Are there clinical applications you’re particularly excited about? For example, using AI to generate care plans or improve care quality?

O’Mara: AI doesn’t generate a full baseline care plan, but it extracts all the information needed to create one quickly. It provides a structured, easy-to-read summary, making admissions preparation much smoother.

Russell: Jody, as a relatively new company, do you think being a newer operator gives Journey Healthcare an advantage in implementing AI?

O’Mara: Definitely. AI allows us to understand our communities much faster. And this is just one AI application—we’re using several others. I personally love AI because it drives clinical efficiency, improves accuracy, and speeds up operations. For example, we use Seva for clinical risk assessments to reduce rehospitalizations. Some of our newly acquired facilities had a mid-40% rehospitalization rate, so AI helps us identify risk factors and train staff to bring that number down.

Russell: That’s fantastic. I think it’s important to recognize that AI is leveling the playing field. Traditionally, hospitals and insurance companies had all the data and dictated terms. Now, with AI, long-term care providers have the tools to push back and advocate for fair reimbursement and better care.

ExaCare transforms post-acute and senior care with AI-driven CRM solutions. Streamline admissions, gain actionable insights, and improve patient outcomes. To learn more, visit: https://www.exacare.com/.