Nursing handoffs happen when nurses pass important patient information during shift changes. This helps the next nurse know the patient’s current condition, treatment plan, and any risks. Hospitals move fast and can be complicated, so handoffs can sometimes miss or mix up information. This can cause harm to patients.
At large systems like HCA Healthcare, nurses do shift handoffs about 60,000 times every day across almost 190 hospitals and 2,400 clinics. Nurses usually spend about 40 minutes each shift on handoffs. That adds up to roughly 10 million hours every year just for this task. Spending so much time on paperwork leaves less time for direct patient care. Also, because handoffs rely on memory, details can be missed or unclear.
To fix these problems, HCA Healthcare worked with nurses and tech experts to make a Nurse Handoff app using AI. This tool reads patient data from electronic health records and gives nurses clear, short summaries during shift changes.
The app was made with nurses’ help. Nurses told the developers what information was important and how to organize it. They helped decide what to include and what to leave out. This back-and-forth made the AI more accurate and easier for nurses to use.
When tested, nurses said the AI summaries were 86% factually correct and 90% helpful. New nurses felt more confident and ready for their shifts because of the AI support. Nurse product owner K.C. DeShetler said the app lets nurses spend less time on paperwork and more time caring for patients.
The app shows two screens on hospital phones. One screen shows the original electronic health records. The other shows the AI summaries. Nurses can review, add notes, and arrange the information how they like. This fits well with how nurses usually work and helps them trust the AI.
Dr. Whitney Staub-Juergens, a leader at HCA’s Digital Transformation team, said it’s important that nurses take charge of these AI tools. Nurses don’t need to be tech experts to help with AI. Their clinical knowledge makes sure the AI works correctly.
Hospitals also have trouble making detailed hospital course summaries. These summaries help with planning after a patient leaves the hospital. Making them takes a lot of time and depends on the healthcare provider’s experience.
AI can help by pulling important information from patient records and creating short summaries of key hospital events. This saves time and makes sure summaries are clear and consistent. Care teams use these summaries when planning the patient’s follow-up care.
Clinicians using MEDITECH’s AI tools say they save hours because AI quickly breaks down big medical records into useful information for discharge planning. Tools also find important details fast, like Do Not Resuscitate (DNR) orders or lab tests. This helps doctors make decisions quickly when time is critical.
Brenda Totzke, Director of Infection Control, said AI helps spot infection-related problems like sepsis fast. This helps hospitals meet rules and keep patients safer.
Dr. Joseph Lachica, an emergency doctor, shared that AI cuts down the long time usually spent reading through many pages of records. Having quick access to patient data helps doctors give faster and better care, especially in emergencies.
AI also helps manage patient appointments. It predicts which patients might miss their visits. The AI looks at things like past attendance, type of appointment, time of day, and some social factors to guess no-shows.
With these predictions, clinics can better plan their schedules and reach out to patients who might miss appointments. This lowers wasted time and helps more patients get seen on time. Clinics with many patients and less staff find these AI tools useful for managing operations.
AI works best when it fits well into clinical workflows. Doctors and nurses have to balance paperwork, patient care, and talking with each other. AI can take over repetitive tasks so healthcare workers can spend more time with patients.
Some AI systems listen during patient visits to write notes automatically. Others help find needed information quickly by searching both structured data and written notes in electronic records.
At MEDITECH, they work with companies like Google to build AI search functions that look through old digital records, handwritten notes, faxes, and scans. This helps keep important patient information from getting lost in older or different systems.
AI also improves nursing handoffs and hospital course summaries by creating clear, standard documents. This cuts down mistakes that happen from manual writing or forgetting details.
Bringing AI into healthcare needs good planning and working with everyone involved. Administrators and IT managers should think about:
Healthcare providers in the U.S. want to reduce paperwork, keep patients safe, and maintain smooth care. AI tools for nursing handoffs and hospital summaries show practical help toward these goals.
By automating routine notes and improving communication, AI lets clinicians spend more time with patients. Hospitals that involve users, maintain strong data systems, and provide training will get the most benefits from AI.
Looking forward, hospitals may use even smarter systems that watch patient data all the time and send alerts or advice instantly. As AI improves, it could make healthcare safer and more efficient across the country.
Across the United States, AI automation of nursing handoffs and hospital summaries helps reduce mistakes, saves clinician time, and supports patient safety. Real examples like HCA Healthcare’s Nurse Handoff app show how nurse input and AI work together to improve communication.
AI tools for discharge summaries and appointment management through platforms like MEDITECH also improve workflow. Medical practice leaders and IT managers should consider adopting AI carefully with attention to clinical needs, data quality, and staff involvement to make lasting improvements in healthcare delivery.
AI in MEDITECH’s EHR platform processes massive volumes of data quickly to support clinicians in making informed care decisions while keeping humans in control of those decisions.
AI supports providers by automating tasks like ambient listening to capture conversations, generating visit notes, synthesizing search results, and creating nursing handoff documents, thus improving efficiency and reducing manual workload.
Expanse Patient Connect uses AI-powered agents to engage patients through conversational multi-step messaging, facilitating language translation, message shortening, and conversation summaries to enhance communication.
The no-show prediction AI uses machine learning to analyze patterns from various data, including past attendance, appointment type, time of day, and social determinants of health (SDOH), to assess the likelihood of patient no-shows.
By accurately predicting no-shows, healthcare facilities can optimize scheduling, improve staff efficiency, and prioritize patient outreach to reduce wasted time and resources.
The intelligent search covers structured and unstructured data from all care settings, including scanned documents, faxes, handwritten notes, and legacy EHR data, enabling a comprehensive view of patient information.
Clinicians report significant time savings, improved workflow efficiency, easier access to critical data like scanned DNR orders, and reduced burden in cleaning up and summarizing patient information.
AI automatically extracts and formats key patient details consistently to generate handoff documents, improving clarity, reducing errors, and enhancing patient safety during care transitions.
AI-generated hospital course summaries extract key patient details, reducing variability between providers and saving hours of manual review for post-discharge care teams.
MEDITECH collaborates with partners like Google to provide powerful AI tools such as intelligent search across EHRs, bringing innovative, real-world AI solutions tailored to healthcare workflows.
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