Healthcare call centers in the U.S. are at an important point. Studies show that calls to customer care centers may grow by up to 20% in the next few years. This rise happens because of changes in the population, what patients want, and more types of questions, like booking appointments, checking insurance, refilling prescriptions, and billing. Research shows that groups like Gen Z and baby boomers call healthcare providers more than millennials. Gen Z calls about 30-40% more often than millennials. These patients want live phone support as part of good healthcare. So, call centers must be quick and helpful. At the same time, healthcare groups have to deal with tight budgets, not enough staff, and rules about privacy like HIPAA. Because of this, many are interested in AI to handle simple calls, automate work, and let staff focus on harder problems. How AI Enhances Patient Interactions in Healthcare Call Centers AI can collect and study lots of patient data. This helps healthcare groups give more personal and quick care. AI tools like chatbots and virtual helpers can answer common questions all day and night, help book appointments, and send medicine or visit reminders. When AI makes care personal, patients feel better because it knows their needs and history. For example, AI can change responses based on what the patient said before or their health issues. This helps patients feel more satisfied. Studies show personal messages help patients stick with their care and get better results. AI also cuts down the time it takes to solve call problems. A big company outside healthcare used AI and cut call times from 125 minutes to just seconds. Healthcare calls can be harder, but this shows how much time AI can save. Another good thing AI does is smartly sending calls to the right people. It uses rules to match the caller’s needs with the right worker. This helps fix problems in one call more often, which patients like. It also lowers how many times patients get sent around or have to wait. AI’s Role in Improving Employee Efficiency and Experience Healthcare call center workers often have a lot of work and repeat similar tasks. This can make them tired and want to quit. AI can take over some simple tasks like writing what is said in calls, making short summaries, and logging patient info. This lets workers spend time on harder questions that need care and understanding. Studies say workers save about 6.3 hours a week when using AI. Almost half of that saved time helps workers have a better work-life balance. When workers feel better, they do a better job, and patients get better care. Also, AI tools give workers quick access to patient info, clinical rules, and insurance details. This makes calls faster and more reliable. Patients trust care providers more when they get correct answers quickly. AI helps with planning too. It looks at past call data to guess how many workers are needed. This helps schedule staff wisely, so patients wait less and the office saves money. This kind of scheduling is important when call numbers change due to seasons or health issues. ✓ AI Call Assistant Manages On-Call Schedules SimboConnect replaces spreadsheets with drag-and-drop calendars and AI alerts. Don’t Wait – Get Started Strategic Implementation of AI in Healthcare Call Centers Using AI in customer care is becoming common in U.S. healthcare. More than 80% of companies want to use AI tools soon, like chatbots, automatic emails, agent help tools, and data analytics. Early users see clear improvements. For example, a European bank saw a 20% better chatbot within seven weeks. Healthcare leaders know AI is not to replace humans but to help them, especially with tough or private calls. AI helps workers by showing patient info quickly, suggesting answers, and guiding steps that follow the law. Groups using AI in customer service report about 20% shorter call times and better patient satisfaction. They also have fewer patients hanging up because AI offers callbacks instead of long waits. To get the most from AI, healthcare centers train workers to use AI well. About 67% of care leaders focus on training workers to work with AI. Training helps workers do better and feel good about their jobs. It also helps them change roles to focus more on helping patients and solving problems. Some centers hire outside companies for part of their customer care. More than half do this now, and many more plan to in the next two years. Outside partners often have better AI and skilled workers that may be hard to keep in-house. AI and Workflow Integration in Medical Practice Call Centers AI works best when it links many tools together to make front-office jobs easier. This means combining AI helpers with electronic health records (EHR), appointment systems, customer management software, and billing programs for smooth work. For example, AI can check appointment openings from management systems, confirm times with patients, check insurance in back databases, and update records all during the call or chat. This lowers mistakes from typing by hand and avoids extra follow-ups. Call centers also use knowledge bases that hold clinical guides, common questions, and troubleshooting tips. When used with AI, they help workers answer patient questions fast and make call records for audits and quality checks. Automated processes reduce the work by sending calls based on how urgent or hard they are. Simple calls like lab result notices can be handled by bots, while tricky questions about treatment go to trained staff quickly. AI checks important numbers like how long calls last, how often one call solves a problem, how many people hang up, and patient satisfaction. It looks for problems and helps managers improve. This helps patient service and lowers stress for workers. AI Call Assistant Skips Data Entry SimboConnect recieves images of insurance details on SMS, extracts them to auto-fills EHR fields. Let’s Chat → The Future Outlook for AI in U.S. Healthcare Call Centers Looking forward, nearly

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.