Palliative care is a special medical service that helps ease symptoms and improve life for patients with serious illnesses. The work in this area is demanding because doctors and staff must keep detailed records of symptoms, treatments, and patient changes. This documentation takes a lot of time and adds to the mental work for healthcare workers who must also manage complex symptoms and work as a team.
Recently, AI tools using natural language processing models like GPT (Generative Pre-trained Transformer) have been developed. These AI systems can draft medical notes, monitor medicines, spot clinical trends, and summarize information for patients’ families. They are used in hospitals to help healthcare workers but not to replace their judgment.
In April 2025, a palliative care unit in a U.S. hospital started using a GPT-based AI tool to help with patient care. The study looked at how this tool supported doctors with notes and treatment decisions. Doctors entered patient data through text, and the AI made draft notes like daily reports, discharge summaries, and medicine suggestions. Doctors checked these drafts to make sure they were accurate.
The study focused on:
Data from this study helps show how AI can be used safely and well in careful care areas like palliative care.
One big challenge in hospitals is handling clinical paperwork quickly. Doctors often spend a lot of time making discharge summaries, which are important but can be boring and slow. The study showed that the AI helped cut the average time for discharge summaries from about 20.4 minutes down to 6.1 minutes.
This saved time lets doctors focus on other tasks and helps patients leave the hospital faster and move on to the next care step. Hospital managers see this time saving as a way to run things better and cheaper, and staff are happier. Also, faster paperwork means clinical info is more up to date and ready for care teams to use.
Around paperwork, the AI also helped watch patient data for small but important changes. For example, it noticed higher C-reactive protein (CRP) levels in eight patients. CRP shows inflammation or infection, which is very important in palliative care. Spotting this early allowed doctors to check patients sooner and act faster.
The AI also suggested medicine changes which doctors then checked. In six cases, the system gave ideas for adjusting treatments, and doctors agreed. This checking ensures the AI supports safe care. Hospital leaders and IT managers should keep in mind that AI is for helping, not replacing, doctor decisions.
This helps keep patients safe while gaining from the AI’s ability to find patterns in data. The study shows that doctors need to watch AI results carefully to avoid mistakes and keep care safe.
Physician cognitive load means how much mental effort doctors use to deal with patient info, make choices, and write notes. Too much load can make doctors tired, cause mistakes, and slow care. Doctors using the AI said it lowered their mental burden by handling routine note writing and summaries. This gave them more time to focus on patients and making good choices.
Doctors also said the records made with AI were clearer and better organized. Clear records mean less miscommunication among care teams who often have to work together in palliative care. These results will interest hospital leaders who want to improve work quality and reduce doctor burnout, which is a big problem everywhere.
Talking with patients’ families is very important in palliative care. Families need to understand treatment goals and the patient’s health, which can be hard. The AI tool created simple summaries that families understood better. These summaries explained medical info and plans clearly.
This helped families feel more informed and less confused. It also meant doctors got fewer questions and could spend more time with patients. Hospital managers who care about patient experience will see this as a useful way to support families without needing more staff.
In hospital palliative care, workflow automation means making routine or slow tasks quicker. This lets doctors spend more time with patients. The AI tool in this study helped in important workflow areas:
Hospital IT managers and administrators can gain from AI solutions by improving staff efficiency and patient care. But they must spend time training clinicians and customizing systems to fit hospital rules and patients. Also, they have to follow laws that protect patient privacy when using AI.
Healthcare administrators and owners in the U.S. must find ways to work better while keeping patients safe and care good. AI tools like the GPT-based system in this study offer a chance to do this in tough care places like palliative units.
Important points for them to consider include:
IT managers must oversee technology and protect data privacy. At the same time, administrators and owners must ensure clinical work fits the goals and legal rules of their organizations.
This study gives helpful information for hospitals thinking about using AI in palliative care. It shows that AI can cut time spent on paperwork and give useful support for care without taking a doctor’s job. Hospital leaders should think carefully about these results and prepare their teams well to use AI right. Doing this can help improve patient care and how hospitals operate in difficult care areas.
The primary objective is to support clinical workflows by assisting with documentation, trend recognition, and clinical decision support, thereby improving efficiency and clarity in managing complex palliative care patients.
AI assistance reduces documentation time from an average of 20.4 ± 5.6 minutes to 6.1 ± 1.8 minutes for discharge summaries, reflecting a significant time saving.
Beyond documentation, the AI tool assists in drug monitoring, recognition of clinical trends, and generating educational summaries for family communication.
Physicians enter patient data via a text-based interface, and the AI generates draft documentation that clinicians review and finalize, ensuring accuracy and clinical relevance.
No, it does not replace physician judgment but acts as valuable support under appropriate clinical supervision to enhance workflow and clinical awareness.
In eight patients, the AI flagged important clinical trends, such as rising C-reactive protein (CRP) levels, which prompted earlier clinical re-evaluation.
Physicians reported a reduction in cognitive load, along with improved clarity in clinical records when using the AI-assisted documentation tool.
Yes, all therapeutic suggestions made by the AI were confirmed by internal medicine specialists to ensure safety and accuracy.
The AI generated educational summaries that enhanced communication with families by providing clearer, more accessible information.
A retrospective observational study was conducted involving 25 patients in a hospital-based palliative care unit, assessing the AI tool’s impact on documentation and clinical monitoring.
Simbo is using AI agents to automate all phone related workflows. Connect now to know more.
Schedule AI Agents Demo Now© Since 2019, Simbo AI.
