NLU is a technology that helps AI systems understand what patients say in normal language. Older systems used fixed menus and key words, but NLU can understand complex sentences, slang, accents, and different ways people talk. This makes patient conversations more natural and useful. In healthcare, NLU can automate simple tasks like answering questions, booking appointments, managing prescription refills, and offering telehealth help. AI virtual agents can have open conversations and understand what patients want without needing them to choose from complicated menus. For example, Nuance Patient Engagement Solutions uses NLU to handle more than 31 billion interactions a year. Their Intelligent Virtual Agent solves about 40% of patient calls without a live person. This lowers wait times and reduces work for frontline staff, helping both patients and workers. Impact of NLU on Patient Experience Patient engagement is very important in U.S. healthcare. Studies show that 82% of patients might change doctors because of poor phone service. Long waits and busy staff make it hard for many offices to give quick, personalized help. AI with NLU helps by giving immediate support anytime. Patients like it when AI understands their questions and gives clear answers or solves problems. A study in the Journal of the American Medical Association found patients thought AI responses were more caring and better than some doctors’ replies. AI can also handle patient frustration by avoiding long menu navigation and chatting like a person. NLU can also understand different languages and speech styles, helping serve all kinds of patients across the U.S. AI that talks in many languages helps remove language barriers. For patients in rural or poor areas, AI is available 24/7, giving support even when offices are closed. The University of Michigan Health-West says their use of AI with NLU improves the patient experience. It takes care of simple questions automatically and lets staff focus on difficult cases. This way, patients get both automation and human help, which builds trust. Improved Efficiency for Medical Practice Operations NLU reduces the workload on human agents. This lets them spend more time on tough questions and care coordination. MUSC Health noticed call centers have less work and appointments happen more smoothly after adding AI call deflection tools. Call deflection means AI handles easy calls instead of humans, sometimes up to 70% of calls. Oracle Digital Assistant users saw a similar effect, with a 20% increase in productivity and big savings on labor costs. Besides lowering call volumes, NLU helps agents by giving real-time transcripts, call summaries, and suggested replies. This lets agents finish calls faster. On average, calls got 53 seconds shorter with AI help. Short calls mean more patients can be served and less frustration from waiting long or repeating information. NLU also works with other healthcare software like Electronic Health Records (EHR), Customer Relationship Management (CRM), and practice management systems. Virtual agents can check patient identity, appointment times, billing info, and give personalized answers. Smooth data sharing keeps records correct and care consistent. AI and Workflow Integration: Enhancing Administrative Efficiency Appointment Scheduling and Management AI can handle appointment reminders, confirmations, cancellations, and rescheduling. It works through phone calls, texts, or patient portals. Automating this reduces missed appointments, lowers errors, and frees staff time. Practices can schedule more care efficiently and keep work flowing. ✓ AI Call Assistant Reduces No-Shows SimboConnect sends smart reminders via call/SMS – patients never forget appointments. Start Building Success Now Prescription Refill Coordination NLU lets patients ask for prescription refills by phone or chat. The AI checks these requests with pharmacy and doctor records. It starts approval if rules are met and tells patients the status. This lowers manual calls and helps pharmacies coordinate better. Voice AI Agents Takes Refills Automatically SimboConnect AI Phone Agent takes prescription requests from patients instantly. Book Your Free Consultation → Billing and Insurance Queries Patients call often with questions about bills, insurance, or payment plans. AI with NLU can explain details and solve many questions alone or pass harder ones to people. Faster and clearer answers cut down backlogs and improve patient trust in money matters. Telehealth Support and Patient Portal Navigation Many patients need help using telehealth or logging into portals. AI with NLU gives step-by-step help and fixes common tech problems. This helps virtual visits run smoothly and lowers frustrations or dropped calls. Real-Time Analytics to Improve Services AI collects data from patient conversations. This gives leaders live feedback on common patient problems, language challenges, and workflow issues. With this info, managers can improve processes, staff assignment, and service design to better meet patient needs. Privacy, Security, and Compliance Considerations Using AI and NLU in healthcare means protecting patient privacy. Handling protected health information (PHI) with speech recognition, chatbots, or virtual agents must follow U.S. laws like HIPAA. Security rules such as HITRUST also apply. Healthcare providers need AI companies to use strong encryption, control who can access data, keep audit records, and watch for breaches. Contracts should clearly say who handles data safety and incident response. Being open with patients about how their data is used and stored builds trust. While AI makes work easier, providers must watch for ethical concerns like bias, consent, and limits of automation in personal care. HIPAA-Compliant Voice AI Agents SimboConnect AI Phone Agent encrypts every call end-to-end – zero compliance worries. Don’t Wait – Get Started → Challenges in Wide-Scale NLU Adoption in U.S. Healthcare Technical Complexity: Adding NLU systems to different existing healthcare IT setups is hard. Many electronic health records (EHR) systems vary. This needs big investments and strong IT skills. Trust and Acceptance: Doctors and staff need training and ongoing help to see AI as an assistive tool, not a replacement. Good user interfaces and ways to give feedback help adoption and improve results. Data Privacy Concerns: Protecting sensitive health data is always important. More cloud services and connected platforms increase risk from cyber attacks. Cost and Resource Allocation: AI saves money over time but costs a lot to set up and maintain.

Ahead of Intelligent Health (13-14 September 2023, Basel, Switzerland), we asked Yurii Kryvoborodov, Head of AI & Data Consulting, Unicsoft, his thoughts on the future of AI in healthcare.   Do you think the increased usage of Generative AI and LLMs will have a dramatic impact on the healthcare industry and, if so, how?   Generative AI is just a part of the disruptive impact of all AI tech on the healthcare industry. It allows to dramatically reduce time efforts, costs and chances of mistakes. Generative AI and LLMs are applied to automating clinical documentation, drug discovery, tailoring of treatment plans to individual patients, real-time clinical decision support and health monitoring, extracting valuable insights from unstructured clinical records, streamlining administrative tasks like billing and claims processing, providing instant access to comprehensive medical knowledge. And this list continues.

We sat with Benjamin von Deschwanden, Co-Founder and CPO at Acodis AG, to ask him his thoughts on the future of AI in healthcare.   Do you think the increased usage of Generative AI and LLMs will have a dramatic impact on the healthcare industry and, if so, how?   I think that the strength of Generative AI lies in making huge amounts of information accessible without needing to manually sift through the source material. Being able to quickly answer any questions is going to be transformative for everyone working with increasingly bigger data sets.The challenge will be to ensure that the information we get by means of Generative AI is correct and complete – especially in healthcare – as the consequences of wrong data can be fatal. We at Acodis are actively working on practical applications of Generative AI inside our Intelligent Document Processing (IDP) Platform for Life Science and Pharma clients to drive efficiency and accelerate time to market, whilst controlling the risks.

Intelligent Health 2024 returns to Basel, Switzerland on 11th–12th September. We’ve got prominent speakers. An extensive programme. Groundbreaking advancements in #HealthTech. And much, much more. Our incredible 2024 programme will dive deeper than ever before. From sharing the latest innovation insights to exploring use cases of AI application in clinical settings from around the world. All through our industry-renowned talks, limitless networking opportunities, and much-loved, hands-on workshops. Read on to discover what themes await at the world’s largest AI and healthcare summit. 

We sat down with Margrietha H. (Greet) Vink, Erasmus MC’s Director of Research Development Office and Smart Health Tech Center, to ask her for her thoughts on the future of AI in healthcare.   Do you think the increased usage of Generative AI and LLMs will have a dramatic impact on the healthcare industry and, if so, how?   The integration of Generative AI and LLMs into the healthcare industry holds the potential to revolutionise various aspects of patient care, from diagnostics and treatment to administrative tasks and drug development. However, this transformation will require careful consideration of ethical, legal, and practical challenges to ensure that the benefits are realised in a responsible and equitable manner.