How AI relieves pressure on healthcare industry

    The healthcare industry is under tremendous pressure. Staff shortages, rising costs and an increasing demand for care are creating a growing challenge. Fortunately, there is a powerful ally ready to support us in this endeavor: artificial intelligence (AI).

    At ConsultAssistent we use Large Language Models (LLMs) to summarize our structured anamnesis reports so that - after approval by the physician - it can be placed directly into the Consultation section of the Electronic Patient Record. The expectation is that this could save several minutes per consultation; we are currently validating this. Because there is thus less administrative work to be done, it ensures less repetitive work and more job satisfaction for the healthcare professional.

    We also use AI Machine Learning applications to make predictions based on large amounts of collected structured care data. Examples we are working on are determining the ASA classification, predicting needed investigations, predicting the Differential Diagnosis and ultimately the prognosis of an individual patient compared to many other patients like this one.

    AI is not the future, it is now. And its potential to transform our healthcare is great. Below are nine ways AI is playing and will play a vital role in taking the burden off our care:

    1. Greater Job Satisfaction for Healthcare Providers AI takes over administrative tasks and repetitive work, giving healthcare professionals more time for what really matters: human interaction and providing care. One example of this is the ConsultAssistent automated medical history and follow-up tool, which patients fill out at home and which generates a smart report for the doctor in the EHR.
    2. Digital Assistance for Patients AI chatbots and virtual assistants answer patients' questions quickly and accurately, even outside of office hours. This reduces the burden on primary care.
    3. Smarter Logistics By recognizing patterns, AI can predict which tests or treatments are needed. This saves time, money, and resources. Because ConsultAssistent objectively measures the entire process—from automated medical history collection to follow-up—it generates a continuous stream of structured data as a byproduct of smarter care. This allows, for example, combined appointments to be scheduled more efficiently.
    4. Cost-Effective Care AI provides insight into which treatments are most effective for specific patient groups. This helps prevent waste and reduce costs. For example, when ConsultAssistent data is combined with clinical data, it can shed light on variations in clinical practice: which treatment is most effective and at what cost.
    5. Prevention and “First Time Right” Care Through improved triage and predictions, AI can prevent unnecessary care visits and ensure the right care is provided the firsttime. A good example is preventing unnecessary follow-up visits by effectively monitoring patients online; we are also exploring whether, based on a preoperative screening, we can recommend whether a patient should be seen in person or by phone.
    6. Accessible Healthcare for Everyone With real-time translations, AI helps bridge language barriers. Patients receive care in their own language, which improves the quality of care. Translation apps are already widely used, but the translation and subtitling of materials such as questionnaires and informational materials are also becoming increasingly common.
    7. From Incurable to Treatable The enormous computing power of AI enables us to analyze medical literature and conduct research at breakneck speed. This leads to faster insights into treatment methods for conditions that are currently incurable.
    8. Accelerating Innovation While humans have limited time, AI knows no work schedules. It helps accelerate innovation, even in times of labor shortages. A good example is the various Ambient Listening tools that transcribe conversations with patients, present them to the healthcare provider for review, and immediately recommend the correct DBC codes.
    9. Learning from Every Patient AI makes it possible to continuously learn from data. Each treatment helps improve the next—creating a self-learning healthcare system.

    The question is not whether we will deploy AI in healthcare, but how quickly and responsibly we do so. Let's use its potential to make healthcare future-proof - for professionals and patients alike. It requires careful preparation, implementation and evaluation so that workflow improvements can be scaled up properly and safely afterwards.

    At ConsultAssistent, we are working daily to make sure that we deploy AI in a responsible way where it adds real value to healthcare. We can do that because from the beginning we have always had the vision that you can collect a continuous stream of structured care data as a "byproduct" of delivering care. This dataset helps to learn with each patient how to improve care with the next and provides a good basis for scientific research and for the application of AI.

    Read the original post on our LinkedIn page.