AI can also start to provide first-line support to patients in the form of bots using voice or text. This would be helpful to patients but also free up the care team to focus on more important activities and lighten their heavy load. Emerging applications for passively collecting data from patients, analyzing it for insights and informing providers of the results with a preliminary action plan (rather than just passing numbers to the provider and giving them more to do!) would also improve care and help busy physicians, many of whom are suffering from burnout, especially after COVID. Once again, generative AI is a game-changer here. Models trained on data that’s appropriate for these interactions (unlike ChatGPT, which is trained with both medical and popular literature) can be very effective for creating meaningful and productive interactions with patients.
AI solutions can be involved in a range of clinical and administrative tasks that will benefit the quality of decision making and reduce the amount of work for everyone involved. Areas such as smarter care and top-of-license applications are more futuristic. However, areas like data collection from patients, mining EHRs for relevant information and improving the experience of the providers and patients are much closer to coming to fruition. Improving the ability to generate documents, extracting insights from them, ordering tests and generating referrals create a lot of work for the care team but don’t have to be done by them. Removing this from their to-do list would significantly improve their experience and reduce the pandemic of provider burnout. This would fulfil the promise of AI “augmenting” clinicians.
AI can become a foundational solution for—rather than a contributor to—burnout among physicians and achieving the quadruple aim of improving health, enhancing the experience of care, reducing cost and attaining joy in work for health professionals. Augmented intelligence can be used to increase the capacity of healthcare professionals by combining the power of AI with human perception, empathy and experience. Common consumer applications of AI are already being used to augment human decision making. A few examples of this include:
- Automated suggestions for the names of people in photographs to reduce the burden of manually documenting it (e.g. on Facebook).
- Voice-based communication with a virtual assistant (such as Alexa and Google Voice) decreasing the amount of screen time needed to find information.
- Recommended products and services based on your prior selections saves time and reduces cognitive effort (e.g. on Netflix and Amazon).
In the context of clinical workflows, this can be helpful for documentation, coding, quality improvement and more.