How we search for information in healthcare has come a long way. As artificial intelligence (AI) technology advances, conversational AI solutions are making it even easier. Whether you’re a clinician looking for medical literature to support patient care, or a patient seeking information about your condition or hospital visit, advancements in AI technology are lowering the cognitive burden of information retrieval in the healthcare industry, and beyond.
Conversational AI systems are simplifying search, with benefits for patients, clinicians, and healthcare organizations too. This post will explore use cases of conversational AI in healthcare, with a spotlight on clinical decision support and important safety considerations.
Conversational AI technology is a type of artificial intelligence that simulates human conversation using natural language processing (NLP) algorithms. With machine learning and generative AI, conversational AI systems such as AI chatbots and virtual assistants, can understand and respond to human language in a manner that feels natural.
Examples of conversational AI solutions include AI-powered virtual assistants that help patients by answering specific questions about their conditions in human-like interactions. For instance, conversational AI can provide a direct answer to a question, pulling relevant details from patient education documents or FAQs so patients don’t have to dig through pages of information.
The healthcare sector is benefiting from advancements in conversational AI tools. Let’s take a look at example use cases creating significant advantages for patients, healthcare professionals, and healthcare organizations:
Conversational AI can enhance the patient experience by supplementing patient interactions with healthcare providers. AI-powered tools like chatbots and virtual assistants can provide timely information to help educate patients on their condition and care plan follow-ups.
This can be of particular help for chronic disease management, for example, a patient with hypertension can ask a virtual assistant what to do if they miss a dose of their medication or share blood pressure readings between check-ups. Real-time responses to patient questions help users feel supported through their healthcare journey, boosting patient satisfaction. What’s more, clarity around treatment can improve patient engagement and medication adherence, with the potential to improve overall health outcomes.
For healthcare professionals, administrative tasks are often a source of significant workload and burnout. Conversational AI solutions can streamline workflow tasks that involve searching for information to support patient care.
The volume of published medical evidence is expanding rapidly, making it harder for clinicians to quickly find treatment and medication management insights they need to ensure safe patient care. Trusted clinical decision support systems that leverage conversational AI to help surface the latest curated clinical evidence, speed up access to accurate answers to support their decisions, even in complex patient care scenarios.
In this use case, AI assistants allow clinicians to ask specific questions, such as whether a medication is safe during pregnancy, rather than manually searching through pages of text for the information. This streamlines the clinical workflow and frees up more time for healthcare professionals to focus on patient care.
However, the effectiveness of conversational AI tools for this use case relies heavily on the quality and completeness of the underlying body of clinical evidence.
Medication errors are a persistent challenge in healthcare. The increasing volume of medical evidence makes it difficult for clinicians to access the latest and most relevant information—but the right tools can make a difference. By pairing AI chatbots with the large content repositories underlying clinical decision support systems, critical insights can be delivered even faster, in a way that better supports the clinical workflow to accelerate decision-making. Applying conversational AI to the search functionality within these trusted, high-quality datasets based on curated evidence is a game-changer. Especially in terms of boosting the “findability” of specific information needed to support medication safety.
Healthcare systems constantly face pressure to optimize resources. Conversational AI tools can help alleviate staff from some of the queries they would traditionally deal with on phone calls by routing patients directly to the right resource based upon individual patient needs, whether that’s appointment scheduling, clinical triage, prescription refills or another topic.
This can free up healthcare staff for more complex tasks and in some cases help organizations reduce wait times. These efficiencies contribute to better resource management, potential cost savings, and a better user experience for healthcare services that are more accessible to everyone.
While conversational AI offers numerous advantages, it’s critical to approach its implementation thoughtfully and ethically. Patient health, safety and data privacy must always remain the top priority.
Handling health records and patient information securely is paramount. Conversational AI platforms must comply with regulations like the Health Insurance Portability and Accountability Act (HIPAA) to ensure patient data and health information is managed responsibly and securely.
When using generative AI in healthcare, it’s essential to validate the underlying knowledge sources for AI-driven answers and ensure clinicians are involved in development and continuous quality monitoring. This collaborative approach minimizes risks and ensures the AI system delivers accurate and reliable insights.
The future of conversational AI in the healthcare setting lies in collaboration. Close partnerships between healthcare providers, AI developers, and clinicians will drive innovation while maintaining the integrity and safety of healthcare services.
To make an impact in healthcare, AI-driven technology needs to be applied in meaningful ways to support healthcare staff and improve patient outcomes. By adopting solutions that reduce the cognitive load on clinicians, streamline healthcare workflows, and empower patients to take an active role in their own care, healthcare systems can better meet staff and patient needs.
With continuous advancements in conversational AI, healthcare organizations are poised to create smarter, more efficient systems that prioritize both patient care and operational efficiency.
Watch this 15-minute webinar for expert insights from both a seasoned clinician and a data scientist perspective, examining how AI can unlock greater value from the rapidly growing universe of clinical evidence. The discussion explores considerations around human judgement, content sources, clinical validation and patient safety.