The combined impact of deep learning, large training datasets, increases in computing power, and new model architectures has led to a step change in the performance of Conversational Artificial Intelligence (AI). This technology will transform how healthcare providers interact with their patients, health systems manage their operations, and patients navigate their healthcare needs.
Impact for healthcare providers
For healthcare providers, conversational AI could have a significant impact on operational efficiency. AI has historically excelled at handling high volume routine tasks that consume significant staff time and resources: appointment scheduling, prescription refills, department and provider routing, for example. Conversational AI will not only improve the performance of handling these tasks but will support healthcare providers in addressing the long tail of use cases that are individually less frequent but in aggregate consume time. By allowing healthcare professionals to focus on more complex and urgent tasks that demand their expertise and experience, adopting conversational AI can also improve job satisfaction as healthcare professionals can devote their time to more meaningful and engaging patient interactions.
Moreover, conversational AI can enhance the creation of clinical documentation. Documentation tools can transcribe and digitize patient-provider conversations, leading to more thorough and accurate medical records while reducing provider burden. Whether it’s drafting a patient visit note, a reply in a provider’s inbox, or a handover summary to support a shift change, conversational AI can not only ensure a complete record, but allows clinicians to focus on patient care, not just documentation.
Impact for patients
For patients, conversational AI will offer unprecedented levels of personalization and accessibility. EHR-integrated AI systems can provide personalized health advice and reminders based on a patient’s medical history and current health status. This is particularly beneficial for patients managing chronic diseases, for whom continual monitoring and adherence to treatment plans are crucial for optimal health outcomes. Hallucination remains a risk for large language models (LLMs) but coupling the semantic understanding of these models with clinically validated knowledge sets would allow patients to ask and get answers to questions whenever they need – before a procedure, after discharge, or just managing their health. This will improve patient understanding of their condition and care plans while reducing the burden on clinicians.
Embracing the Future of Healthcare with Conversational AI
These improvements from conversational AI in healthcare provider efficiency, staff satisfaction, documentation, and personalized information will ultimately serve to improve patient care and patient access. These tools are available 24/7/365 and can scale to match demand in real time – whether it’s a public health emergency or just another busy Monday. It is an exciting moment in the development of AI and healthcare with incredible potential for clinicians and the patients they serve.
Carter Dunn is Chief Product Officer at Syllable. Syllable is a leading provider of healthcare contact center and medical practice automation solutions using conversational AI. Syllable’s product, the Patient Assistant, is used by both hospitals and practices to intelligently route calls more efficiently and provide for automated transactions like appointment scheduling and prescription refill on the phone.