This article is sponsored by KanTime. It is based on a Hospice News discussion with Ganesh Sundar, Director at KanTime, and Scott Brown, President and CEO of MyDirectives. This discussion took place on April 10, 2025, during the Hospice ELEVATE Conference. The article below has been edited for length and clarity.

Hospice News: With our next session, “Leveraging AI and Other Digital Tools in Hospice and Palliative Care.” For anyone who hasn’t heard from me yet today, I’m Tim Mullaney. I’m the VP and Editorial Director with WTWH Media’s healthcare publications, which includes Hospice News. I work closely with Jim and Holly, and I’m excited to be moderating this session. I’m joined by two great panelists—Ganesh Sundar with KanTime and Scott Brown, President and CEO of MyDirectives. To start, maybe I’ll just ask each of you to briefly introduce yourselves. Ganesh?

Ganesh Sundar: KanTime is an EMR—a single platform for all lines of business in post-acute care: home health, hospice, palliative care—pretty much the entire post-acute care spectrum. We help organizations through technology, improving efficiencies and ensuring compliance. We’ve been doing this for over 15 years.

Scott Brown: MyDirectives was born about 18 years ago out of an end-of-life experience for my grandmother in Oklahoma. It was a terrible experience. At the time, my mother had been diagnosed with multiple sclerosis, and we knew that advance care planning was a problem. Patients don’t have documents, and when they do, you can’t find them—or they’re terrible. We knew my mother would go through the same thing if we didn’t find a better way.

So MyDirectives has worked over the past 18 years to improve the technology that allows providers to help patients with advance care planning so their wishes can be honored. Two months ago today, my mother passed away—not in an ICU, not in and out of hospitals, but at home, surrounded by love, dignity, and the hospice professionals you all send out. The technology works, and now we’re partnering with KanTime to make it even better.

HSPN: Perfect. Ganesh, can you start us off by talking about how AI can help hospice providers—whether in admissions, plan of care, or recertifications?

Sundar: Absolutely. AI has broad applications across the hospice workflow. Starting from intake and referral, AI can help automate processes. Typically, referrals come in and are reviewed manually. With robust integrations, we can now take care coordination documents—CCDAs, for example—parse them, and pre-populate the EMR.

AI takes this a step further. It’s extremely good at processing unstructured data, like physician narratives and discharge summaries. It can summarize this for the admitting nurse, providing a quick overview and helping them understand the patient’s needs. It also helps prioritize admissions based on acuity, diagnosis, and payer type. It considers clinician availability, location, skill sets, and identifies gaps—like whether a PRN is needed or a full-time RN can cover the visit.

So overall, AI is closing the gap between referral and admission, enabling faster care delivery with optimal resource use.

HSPN: Terrific.

Brown: You take all that data Ganesh mentioned, and one of the biggest problems in advance care planning is identifying who is the right candidate. Especially in palliative care—not every patient is at the end of life.

I recently went through cancer treatment myself as a palliative care patient. We need to identify who should be having advance care planning conversations. And those conversations shouldn’t be left only to physicians—they don’t have the time. Social workers, chaplains, case managers, care navigators—these are the people who can do it.

AI can provide culturally appropriate guides and prompts to help these conversations happen. And even if you don’t have a document for a specific patient, you can use data from others with similar demographics to help guide the conversation and generate actionable documents—accessible across the care continuum, even to EMTs at 2 a.m.

On the backend, AI and analytics help you see who’s doing the work, who’s getting it done, and how to improve. So yes, it’s about honoring patient wishes—but it’s also about making your operations sustainable and high-quality.

HSPN: Excellent. Ganesh, how can hospice providers use predictive analytics to better anticipate patient decline and improve care transitions?

Sundar: Predictive analytics is incredibly valuable. It can identify a patient’s decline by analyzing structured and unstructured data: diagnosis, PPS, KPS, vitals, oxygen saturation, hospitalizations, falls—everything. It produces a dynamic risk score, which helps clinicians know if a patient is likely to decline.

When that score rises, it can alert teams to prepare—for example, checking GIP bed availability, confirming transportation, or updating medication. It helps transition patients more smoothly between levels of care.

It also reduces unnecessary hospitalizations. If a patient’s pain increases, we can adjust treatment proactively to keep them at home, with dignity.

HSPN: Scott, thoughts?

Brown: Absolutely. Frailty scores and predictive analytics go both ways. They inform the conversation—and they also reflect that conversation. Sometimes, a patient doesn’t realize they’re in decline until you show them the data.

It’s also about capturing what the patient wants, not just what the data shows. You might have all the clinical indicators, but if you don’t know whether they want to be transported or not, you’re missing critical information.

And unless their preferences are documented and accessible—say, to an EMT at 2 a.m.—they’ll likely get transported. Technology and interoperability are critical here.

HSPN: Let’s talk about challenges. Scott, what are the biggest hurdles you see in adopting AI and digital tools?

Brown: First, AI can’t yet fully automate advance care planning conversations—these are too nuanced. And there’s still cultural bias in the systems, because AI is trained on the internet.

Second, there’s mistrust in AI—some of it well-earned. Post-COVID, patients and clinicians are wary of how data is collected and used. So AI must support, not replace, human interaction.

HSPN: Ganesh, anything to add?

Sundar: Yes—AI is often seen as a threat. But it’s not replacing people; it’s a tool that equalizes skills and improves consistency.

Key challenges include adoption—getting teams comfortable with it—and the need for long-term data. Early results are promising, but we need multi-year outcomes to validate them.

And finally, accuracy. AI can hallucinate, as we’ve seen with ChatGPT. So it’s important to test AI in small, controlled environments before scaling.

HSPN: Let’s shift to efficiency. With margins tight and staffing strained, how can AI reduce the administrative burden?

Sundar: AI helps clinicians reduce documentation time through speech-to-text and NLP. It supports smarter data entry and decision support—like flagging missing pain scores or unsigned CTIs.

Schedulers and intake coordinators benefit from AI’s ability to optimize caseloads and resource allocation. QA teams can identify inconsistencies or conflicting documentation. Billing can be audited automatically, ensuring everything is in place before submission.

AI can help every department work smarter.

Brown: Absolutely. We can now extract actionable information from open-ended forms like Five Wishes. AI can distill those narratives into data that informs decisions—and that data can be shared across the team.

This way, everyone—from physicians to CNAs—can contribute to care planning at their level, with less burden.

HSPN: Ganesh, how does AI support interdisciplinary teams and care coordination?

Sundar: AI aggregates data from all disciplines. It identifies gaps between desired and actual outcomes, updates risk scores, and notifies the right team members—maybe the caregiver needs respite, maybe the volunteer coordinator should be alerted.

It also helps structure care plans personalized to the diagnosis. For example, a dementia patient might get a suggested care path including CNA visits and specific interventions.

It’s always a recommendation—clinicians retain control—but it enables smarter planning.

HSPN: Scott, any thoughts?

Brown: Interdisciplinary teams need the same information. If you lose that data during a care transition, it’s useless.

Embedding goals of care into the EMR ensures every team member sees it. And by referencing large datasets of similar patients, we can add one more layer of insight to improve outcomes.

HSPN: We’re nearly out of time. Let’s wrap with any final thoughts or unanswered questions. Scott?

Brown: We’re facing a healthcare workforce shortage and an aging population. We need technology to help us do more with less.

AI is only going to get better. Start integrating it now, just like we did with telehealth.

HSPN: Ganesh, final word?

Sundar: The role of technology has evolved. It’s no longer just about billing and documentation. With AI and other innovations, tech is now central to decision-making and care quality.

Partnering with the right technology is essential for growth, sustainability, and better care delivery.

KanTime streamlines all aspects of your agency from beginning to end. From patient intake to scheduling, billing, and payments, our solutions allow you to do what you do best – deliver quality care to your patients. To learn more, visit: https://kantime.com/.