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:
- More job satisfaction for caregivers
AI takes over administrative tasks and repetitive work, so that healthcare professionals have more time for what really matters: human contact and providing care. An example of this is the ConsultAssistent auto-anamnesis and follow-up that is completed by patients at home and of which a smart report is offered to the doctor in the EPR. - Digital assistance for patients
AI chatbots and virtual assistants answer patient questions quickly and accurately, even outside office hours. This reduces pressure on primary care. - Smarter logistics
By recognizing patterns, AI can predict which examination or treatment is needed. This saves time, money and resources. Because ConsultAssistent objectively measures the entire process of auto-anamnesis and follow-up, a continuous stream of structured data emerges as a byproduct of smarter care. For example, combination appointments can be scheduled more intelligently. - Cost-conscious care
AI provides insight into which treatments are most effective for specific patient groups. This helps prevent waste and reduce costs. For example, when the ConsultAssistent data is combined with clinical data, practice variation can be understood: which treatment is most effective and at what cost. - Prevention and 'first time right' care
Through better triage and predictions, AI can prevent unnecessary moments of care and ensure the right care at once. A great example is the prevention of unnecessary repeat consultations by properly monitoring patients online, we are also investigating whether we can recommend whether a patient should be seen physically or by phone based on a preoperative screening. - Accessible care for all
With real-time translations, AI helps bridge language barriers. Patients are helped in their own language, which improves the quality of care. Translation apps are already widely used but translation and subtitling of, for example, questionnaires and educational information are also becoming more common. - From incurable to treatable
The enormous computing power of AI enables us to analyze medical literature and conduct research at breakneck speed. As a result, new insights into treatment methods for currently incurable conditions are emerging more quickly. - Accelerating innovation
Where humans have limited time, AI has no work schedules. It helps accelerate innovations, even in times of labor scarcity. A good example are the various Ambient Listening tools that transcribe conversations with patients and offer them for review by the healthcare provider and immediately also recommend the correct DBC codings. - Learning from each patient
AI enables continuous learning from data. Each treatment contributes to improving the next - thus 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.
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