AI and healthcare communication

Doctors can often be poor at explaining health-related concepts to patients who are not medically trained. This can lead to misunderstandings and unnecessary anxiety.

However, AI can be used to improve healthcare communications considerably, helping doctors explain their diagnoses and prognoses to patients, and providing information about a patients’ physical and mental health that they, or their relatives, might otherwise struggle to understand.

In addition, AI can be used to communicate to medical practitioners, perhaps simplifying or translating things patients are saying so that they become more medically relevant. In situations when professionals are under stress, and especially in environments where blame is a major part of the culture (as it is with the NHS), better outcomes can be created and risks such as unnecessary testing can be prevented.

AI is therefore an essential tool in optimising communication in healthcare settings.

Helping doctors talk to patients

AI supports healthcare professionals by enhancing their communication skills. By facilitating better patient understanding of what healthcare professionals are saying, more meaningful discussions can take place. For example, doctors can use language models to simplify complex medical concepts, making them more comprehensible for patients and ensuring patients grasp essential details.

AI can also be used to help in the training of healthcare professionals, contributing to more effective doctor-patient dialogues. For example, doctors in training could use AI to generate “best practice” answers to circumstances that they are unfamiliar with, such as explaining to a child what will happen to their parent in hospital.

In some circumstances, there can be an understandable temptation to use metaphors to “soften” unpleasant news (such as “we lost him” as a way of announcing a death to a relative). But this isn’t always helpful. AI could potentially monitor conversations and explain where greater clarity would have prevented misunderstandings, or even provide real-time prompts for doctors to be more understandable.

Helping patients talk to doctors

As well as helping doctors to talk to patients more clearly, AI can also help patients explain how they are feeling to doctors. For example, if AI is used to outline the patient’s medical history to the patient, the patient might find it easier to describe the progression of their symptoms. AI-based symptom analysis can also help patients describe their symptoms more accurately and in a way that doctor will find helpful.

AI-driven systems can also allow patients to ask preliminary questions before appointments, or indeed to answer questions. This helps in articulating concerns and ensures more focused discussions during a face-to-face consultation. And during the consultation, AI can also use emotion recognition to detect the mood of the patients, for example detecting when a patient has an unexpressed question or worry, prompting them to ask a question or share more information. It can also pick up on symptoms, such as an unsteady gait, that the doctor may have missed. In this way the AI acts as an observant assistant.

Language and cultural barriers

AI also has the potential to bridge language and cultural barriers in doctor-patient interactions. By leveraging advanced language processing capabilities, AI tools can assist in real-time translation, ensuring that medical information is conveyed accurately and comprehensively. This is likely to be better than using a family member as a translator as the family member may wish to sugarcoat bad news, or may simply misunderstand or refuse to accept what is being said.

More subtly, information can be adapted to fit cultural circumstances, with words that might be acceptable to one group of people substituted for different words. For example, the culture of medical professionals can be very factual and scientific. This may be off-putting to some people who are more focussed on a holistic approach to medicine, including spiritual elements. In these circumstances, AI can potentially suggest alternative ways of explaining things.

Automating telehealth

Telehealth involves health professionals helping patients to manage their health conditions over the internet, rather than through face-to-face meetings. One way this can be achieved is with the assistance of AI-powered chatbots. Using these, rather than humans, to have conversations with patients can be a very efficient way of saving health professionals’ time.

In addition the chatbot may well be more efficient and finding information and communicating it clearly than a human can be. They can provide tailored support to patients based on their needs and preferences, using data analysis to deliver customised health information and advice. This can improve the patient’s trust levels and satisfaction with the service.

AI chatbots can also enhance patient engagement by creating interactive and engaging conversations. They can use gamification, storytelling or humour to motivate and reward patients for achieving their health goals, or following their treatment plans. They can also use social media to reach out to patients in their preferred channels, and encourage them to stay connected and informed.

As well as providing a channel for communication between patient and doctor, telehealth systems can also deliver a monitoring solution, where the patient’s health indicators are regularly checked, and health professionals alerted to any worrying changes. These virtual health assistants can enable patients to receive immediate guidance and support, even when they have not initiated a conversation.

Chatbot transparency will always be important: trying to fool a patient to thinking they are talking to a human is an easy way to destroy trust. While this may be a disincentive for some people to engage, the ability of a chatbot to respond immediately (rather than a patient having to wait for a professional to call them) is an advantage. In addition, in some cases patients may prefer communicating with a machine than with a human.

Facilitating improved communication

AI health systems can facilitate feedback and treatment improvements by collecting and analysing data from multiple and individual patient interactions. This data can be used to measure the effectiveness, satisfaction and impact of doctor-patient communication, and identify areas for improvement. As well as doctors learning, AI chatbots can also evolve, using machine learning to improve their performance and adapt to the changing needs and expectations of the patients, and the healthcare environment.

Ultimately, AI can empower doctors to be better communicators while enabling patients to communicate more effectively with their doctors. Communication is at the heart of successful medical interventions, and AI will increasingly play a part in fostering the positive relationship with healthcare providers that will support these positive outcomes.