Generative AI is ushering in an era of transformation in healthcare, with far-reaching implications for patient care, diagnostics and more. Will technology help overcome some of the biggest problems facing our overburdened healthcare systems and democratize access to healthcare for all? If these use cases are anything to go by, generative AI certainly has the potential to add very real value to the healthcare industry.
Here are six key ways generative AI can improve healthcare delivery.
1. Personalized health advice on demand
Sophisticated generative AI models like GPT-4, combined with the expertise of human doctors, have given rise to a new wave of virtual healthcare assistants. Ada is a doctor-developed, AI-powered app designed to assess symptoms and provide patients with medical advice in multiple languages (including English, German, French, Spanish, Portuguese and Swahili). So far, the app has garnered 13 million users and has achieved over 30 million symptom assessments. It works by asking you about your symptoms (you can also create separate symptom profiles for your loved ones) and then showing you possible conditions and medical advice. The app also tracks your symptoms as they progress.
As millions of people around the world cannot access medical care (either because of their geographic location, for economic reasons, or simply because their local services are too extensive), we can expect to see the Generative AI will take part of the slack.
2. Precision care from busy doctors
I think we’ll see more and more generative AI systems assisting doctors during patient consultations – with AI running in the background, listening, taking notes, and formulating potential questions the doctor might ask in depending on the patient’s history and symptoms. It would be like a cross between a medical chatbot and a diagnostic tool, but designed to be used in one-on-one sessions with patients.
A good example comes from RythmX AI, which created a precision care platform which helps doctors provide hyper-personalized care. Essentially, the system uses generative AI and predictive AI algorithms to provide patient-specific actions and recommendations. Doctors can then drill down on the recommendations via the natural language interface – so it’s a bit like an AI co-pilot for doctors. This type of AI-augmented approach could help doctors get the most out of patient appointments (which may only last 10 minutes).
3. Tailored Treatment and Health Plans
Generative AI can also help doctors improve patient treatment – analyzing large patient data sets to recommend personalized treatment plans, optimizing drug dosages, and predicting potential side effects, all depending on each individual. Additionally, it can help create tailored rehabilitation exercises and therapeutic programs.
Additionally, generative AI could help improve preventive medicine. For example, clinics and hospitals could use generative AI to create personalized health plans based on a patient’s unique genetic makeup, medical history, and lifestyle.
4. Image analysis and early disease detection
AI has been a force in diagnostics for some time, but generative AI will significantly improve medical image analysis. This is why we will increasingly see generative AI tools used to help radiologists identify and diagnose diseases from X-rays, MRIs and CT scans more accurately and quickly.
One study explored the use of AI to interpret chest X-rays and generate X-ray reports in the emergency department. Since many emergency departments do not have 24/7 access to dedicated radiology services, images are often interpreted by a remote radiologist (called “teleradiology”) or even by emergency doctors. The study found that the AI tool generated rapid interpretations and reports of x-rays with levels of quality and accuracy comparable to radiologists’ reports – and at a best quality that teleradiology reports. In one case, the AI performed even better than a human radiologist, detecting a problem that the radiologist had not flagged. This shows that not only can AI help radiologists do their work faster and more efficiently, but it can also help clinicians in other departments interpret medical images and speed up patient treatment.
5. Accelerate drug development
Generative AI is already having an impact on the discovery of new drugs to treat diseases. How? Well, technology can help researchers more easily understand disease markers and find optimal combinations of chemicals (and even invent entirely new combinations) to create new pharmaceutical treatments. As such, generative AI will accelerate drug discovery and development by generating new molecular structures, rapidly screening compounds, predicting drug interactions, repurposing existing drugs for new applications, optimizing assays clinical trials and improving drug formulations.
In the future, this could also help improve personalized treatment, as medications could, in theory, be tailored based on individual patient data.
6. Behind-the-Scenes Improvements in Healthcare Facilities
Although it may not sound as exciting as discovering new drugs or providing personalized care, generative AI can help reduce administrative burden in healthcare settings, including automating tasks such as medical coding, billing, routine inquiries and note taking. This makes a lot of sense when you consider the tasks that generative AI is capable of writing, listening to, interpreting human speech, and understanding text.
A good example comes from NextGen Healthcare and its Ambient Assist note-taking tool, which listens to conversations between patients and clinicians and then provides summary notes. Notes are available for the clinician to review within just 30 seconds of the patient encounter ending, with the tool documenting appointments with more than 90 percent accuracy. Therefore, tools like NextGen help clinicians reduce administrative tasks without compromising clinical records. Since administrative burden is cited as a leading cause of clinician burnoutanything that can ease the administrative burden on clinicians could add enormous value to our health systems.
Clearly, nothing can replace the exceptional care provided by human doctors and other healthcare professionals. But it’s clear that generative AI offers solutions that can help bridge the gap between growing healthcare needs and seemingly diminishing resources. As healthcare systems become increasingly strained, the combination of human and machine expertise will likely be the best way to diagnose patients and provide appropriate treatment.