Innovations That Improve Nursing Workflows

Pragmatic, unglamorous innovations are often the most useful. For example, consider NLP to label patient messages rather than Gen AI to answer them. In late 2022, Kaiser started applying its home-grown natural language processing (NLP) algorithms to label patient portal messages with categories such as admin question, medication issue, skin condition, and emergency. Over a five-month study period, the NLP labeled more than 3.6 million messages. Roughly 40% (1.5 million) of these messages were flagged and directed to a centralized “desktop medicine” team, which resolved them before they ever reached the patients’ personal PCP/nurse’s inbox. Pairing a (now) relatively unglamorous type of AI with a pragmatic team-based workflow meaningfully improved this vexing aspect of care. Compare this to the more headline-grabbing efforts to use GenAI to draft responses to patient messages, which has been disappointing so far. At Stanford, clinicians only used 20% of GPT-generated drafts. These drafts did not save physicians time nor reduce turnaround time [doi:10.1001/jamanetworkopen.2024.3201]. At UC San Diego, clinicians who used ChatGPT drafts paradoxically spent 22% more time reading messages/drafts and did not respond any faster [doi:10.1001/jamanetworkopen.2024.6565]. Though I believe GenAI drafts will be useful one day, physicians and nurses overloaded with patient messages need help now. (We must also recognize that editing GenAI drafts is sometimes harder than writing a response from scratch). All this to say, it’s often best to pick the lower-hanging fruit first. Also, tech alone is rarely the solution. What really made a difference at Kaiser was pairing NLP labels with a practical workflow and appropriately resourced centralized (“Desktop Medicine”) team that took work off their physician colleagues’ plates. #healthcareai #patientmessaging #healthcareonlinkedin https://lnkd.in/g5ycmxGb

Investing in healthcare innovation initiatives is essential to the future success of our industry but at what cost? We are constantly asking ourselves "what is the ROI?" especially for digital health projects with artificial intelligence. Here are several ways we, as hospital innovation executives, are seeing return on investment with AI projects: (1) Work collaboratively with a technology vendor who can serve as a partner in refining a product to meet specific goals. We did this with our operating room ambient intelligence project and we have seen a 15% increase in our OR capacity without adding new staff members. (2) Implement change management procedures alongside new technology. When we first launched our virtual nursing program, the bedside nurses were skeptical because they thought their jobs were at risk. Within 10 days, every bedside nurse was asking for a virtual nurse to assist with admissions & discharges because it reduced their time spent on documentation activities and allowed them to better personalize care for their patients. We have since improved our admissions & discharge process leading to better patient & staff satisfaction, eliminated all contract nursing positions, and have added a fresh set of eyes on the patient floors where we have seen great catches in discrepancies. (3) Use AI responsibly with a human in the loop. One of our main goals with using AI technology is to lessen the burden of data mining and documentation for our clinicians. Our predictive analytics tools work in tandem with clinical teams to highlight the most important information in the EHR, saving them from having to dig into the patient's notes and extensive medical history. We have seen that the AI tools we use are 75% more accurate at projecting a patient's discharge date and can identify the highest risk patients who make up 80% of our adverse events so that we can better align the use of our clinicians' time. 👇 Read this Becker's Healthcare article quoting multiple health system leaders across the country sharing their top ROI on AI projects. https://lnkd.in/g9PqcbSq

The Abridge, Mayo Clinic, & Epic AI partnership announcement and what it means for nursing.   Abridge is an AI software that uses ambient listening technology and AI to automate clinical patient summary workflows.   The collaboration with the Mayo Clinic and Epic will put cutting-edge AI into the hands of nurses. Here are 3 things I love about this partnership.   1️⃣ Nurses have a seat at the table This is amazing, because in my opinion, tech will never be adopted as expected if built without engaging the nurses who are meant to use it.   Nurses are directly involved in the tech development, and Mayo Clinic’s CNO, Ryannon Frederick, is championing the initiative. 2️⃣ Less paperwork, more patient care Who can argue against reducing administrative tasks among the nursing workforce? Let’s leverage the power of AI to free nurses from the endless administrative responsibilities that have fallen on us.   Let AI do the heavy lifting. Less time behind computers means more hands-on patient care and training. Nursing has so many inherently human elements that the current state of AI should not put our jobs (nor clinical judgment) at risk.   AI has the power to give us more time and space to do what we are uniquely capable of doing for patients. 3️⃣ Partnership This partnership brings together some of the best in nursing, electronic medical records, and generative AI.   Partnership is more important in healthcare than any other industry (in my opinion) because of its highly risk-averse and regulated nature.   Innovation via net new solutions often doesn’t see the light of day in healthcare. To be disruptive, vendors must operate within practical constraints and workflows – partnering with pre-existing players is a great way to do so.   Healthcare ecosystems are already so fragmented that attaching to existing workflows is more effective than adding new workflows to systems and processes.   – At M7 Health, we’ve had a fantastic partnership with ScionHealth.   Like Abridge & Mayo, Scion & M7 listened to the voices of Scion nurses to build something practical for nurses (that also reduces administrative burden!).   It worked for Scion’s nursing population, and now, M7 is scaling that innovation to serve a diverse nursing population in other systems. In sum, I am bullish on this new AI partnership because: → Nurses are instrumental in developing the solution. → It alleviates administrative burdens placed on nurses. → Abridge partnered with a leading hospital system to develop in a practical way.   This is how you innovate in nursing today.   #nursingAI #innovation #changemanagement

Nurses are healthcare. If we are to improve healthcare delivery so it is patient-centered, supporting the great work that nurses do is imperative. I have been waiting. Nurses spend as much if not more time in front of a computer screen as physicians, advanced practice providers, and therapists. That takes them away from patient care. I am happy to see that nursing documentation is now a focus for Abridge (https://lnkd.in/dHC6inWS). From their CEO, Shiv (Shivdev) Rao, "A big focus for us this year is nursing. That’s one key area of continuous development. We previously announced that we were starting work with the Mayo Clinic and [electronic health record company] Epic on a nursing solution. This is the year where we’re going to be deploying that work and getting feedback, iterating upon it, and hopefully scaling it across the country." What ambient documentation and #GenAI could do for nursing? 🟢 Real-time, context-specific clinical narratives; #Ambient #AI listens during patient encounters, rounds, or procedures, generating structured notes in real time while also tagging key clinical events, patient quotes, and care preferences. 🟢 Intelligent care plan alignment; Ambient documentation integrates with the EHR to auto-map what’s discussed or done at the bedside into the patient’s personalized care plan, flagging deviations or updates needed. 🟢 Automatic patient education summaries; While nurses provide education at the bedside, ambient AI captures the conversation and instantly generates a clear, literacy-adjusted patient/family education handout in their preferred language. 🟢 Handoff improvements; Ambient AI listens during shift handoffs and bedside reporting, generating structured SBAR summaries (Situation, Background, Assessment, Recommendation) with embedded links to relevant EHR data. 🟢 Earlier detection of trends/patient risks; NLP/LLM plus ML continuously analyzing nurse’s spoken surveillance and observations, vital sign trends, and patient-reported symptoms to highlight subtle patterns (e.g., early sepsis indicators, wound deterioration) before they appear in standard monitoring alerts (See already great work being done by the CONCERN warning system by Sarah Rossetti, RN, PhD, David Albers, Kenrick D Cato (He, Him) PhD, RN, CPHIMS, FAAN, FACMI (https://lnkd.in/ddzrpFA3. and https://lnkd.in/dXqpQd6s). If nurses are supported better in doing their work, patient care and outcomes will improve.... not rocket science. They should have been a focus of this AI evolution from the very beginning. Better late than never I guess. #UsingWhatWeHaveBetter

Sharing the latest chapter in our AI journey at the Froedtert & the Medical College of Wisconsin health network with post 2 1/2 of 3, highlighting our collaboration with Layer Health. Excited to share how our partnership with Layer Health is transforming clinical workflows 🚀 At Inception Health, we're strategically investing in AI innovations that make a real difference. Layer Health's Distill platform has revolutionized our registry abstraction process with impressive results: ✅ 65% reduction in chart review time ✅ 100% sensitivity in detecting severe COPD history ✅ Streamlined workflows (15 clicks → just 1) Layer is helping our clinical teams work smarter, not harder. As one nurse abstractor put it: "I couldn't imagine going back to our old way of doing things." The best part? We're just getting started. We're now expanding Layer Health's applications to optimize site-of-care decisions for ambulatory surgery centers and beyond. This is what responsible AI implementation looks like in healthcare - augmenting human expertise, not replacing it. Read our full case study on Medium to learn more about this transformative partnership: https://lnkd.in/edS4GbgZ #HealthcareInnovation #AI #DigitalHealth #ClinicalWorkflows #maybeMoreThan3Posts

Ask any nurse what they'd like to change about work, and they'll tell you it's their documentation: excessive documentation burdens nurses and other healthcare providers. While documentation is crucial, hospitals often prioritize comprehensive documentation to mitigate legal risks and ensure regulatory compliance, making the current systems cumbersome and time-consuming. Lack of input from nurses can lead to inefficient processes, such as pages of patient reassessments that must be repeated endlessly, wasting nurses' time. However, some hospitals are focused on supporting their nurses and getting it right. Case in point: Johns Hopkins Hospital has saved nurses 170,620 clicks in four months."Conversations about nursing documentation revamp began in March 2023, when leaders received feedback from a survey where nurses were asked to share "anything that drove them crazy" about documentation…The hospital began putting that feedback into action this year." The result was a staggering 170,620 reduction in clicks that nurses did not actually need to do to provide safe, effective patient care. How do other organizations follow their lead? Involve nurses in decision-making. Nurses should be included in designing and evaluating nurse documentation systems to ensure they're user-friendly and clinically relevant. Utilizing support staff by employing scribes or administrative assistants to handle non-clinical documentation can free nurses to focus on patient care. Providing ongoing training on efficient documentation practices can help nurses use existing systems more effectively. Investing time and money in EMR documentation is smart for any healthcare organization, and the return on investment is enormous. Any action that supports nurses spending less time in the EMR and more face-to-face time with patients saves lives, and the data show this. #nursesonlinkedin #nursedocumentation #nurses #nurseleaders #nurseinnovation

AI in Nursing: A Tool for Progress, Not a Replacement (Sound Familiar?) AI is reshaping nursing—streamlining workflows, improving patient monitoring, and offering decision support. A recent study, Artificial Intelligence in Nursing: An Integrative Review of Clinical and Operational Impacts, dives deep into AI’s role in modern nursing. The findings? AI is helping, but it’s no magic fix. Article: https://lnkd.in/g2Qgynx9 📌 AI-powered monitoring is catching early warning signs of sepsis, fever, and pain—things nurses already look for but often under pressure and without enough staffing. The tech assists, but it doesn't replace the critical thinking, sciences, and clinical intuition that define nursing. 📌 Workflow automation is making documentation and scheduling less of a headache. AI-driven tools in EHRs are cutting down on paperwork, letting nurses focus on patient care. Being honest— we can’t afford to implement tech for tech’s sake. If AI tools don’t tangibly improve workflows, they need to be reworked or scrapped. 📌 Ethical concerns can’t be ignored. Data privacy, algorithmic bias, and AI decision-making risks all demand serious oversight. AI is only as good as the data it's trained on—if we’re not careful, it could reinforce existing disparities rather than fix them. (Garbage in, garbage out) The takeaway? AI in nursing is a tool—a powerful one—but only when it’s implemented ethically and intelligently. It should support nurses, not replace them. The conversation isn’t about if we use AI in nursing, but how we ensure it works for both nurses and patients. #nursing #healthcare #nursinginformatics #artificialintelligence #nursesinleadership #aiinnursing #digitalhealth #nursingworkflow #patientcare #healthtech #nursingethics #nurseadvocacy #aiethics #workforcedevelopment #automation #ehr #clinicaldecisionmaking #informaticsnurse #healthcareleadership #patientoutcomes #futureofnursing

On average, 50% of a nurse's time is spent on indirect or non-patient care activities.* Our customers are saying that Vocera is transforming how they think about care coordination by connecting people with the technology they need to help support dynamic workflows, reduce cognitive burdens, and facilitate seamless communication. They’re also excited about the rich insights it provides, freeing up more time for nurses and helping to enhance patient care. It's essential that we continue to find ways to streamline processes for care teams as demands on their time continue to grow. . .  . .   *Douglas, S., Cartmill, R., Brown, R., Hoonakker , P., Slagle, J., Schultz Van Roy, K., Walker, J. M., Weinger, M., Wetterneck , T., & Carayon , P. (2013). The work of adult and pediatric intensive care unit nurses. Nursing research, 62(1), 50 58.

I've been watching the Mayo Clinic's approach to AI in nursing documentation, and it's a pretty cool concept... Unlike those frustrating tech "solutions" we've all endured (you know the ones—designed by people who've never spent a day a full day on the unit), this system was built WITH nurses, FOR nurses from the ground up. Its focus is capturing all those "invisible" aspects of care that typically go undocumented despite being absolutely critical to patient outcomes. Nurses across seven Mayo sites are literally "nursing out loud," and what they say and do is being captured to help optimize the AI in real-time, all while creating comprehensive records of countless assessments and interventions that previously went unrecognized. Could this finally be the tool that allows administrators to see the full scope of nursing practice? For the first time, we might have #AItechnology that actually quantifies what #nurses have always known: our work extends far beyond what shows up in traditional documentation. What impact do you think this will have on staffing, compensation, and the advancement of the nursing profession? #AI #Nursing #NursingInnovation #HealthcareAI #HealthcareBoss