Conversational AI in Healthcare Guide with Examples

What is Conversational AI in Healthcare?

Conversational AI in healthcare refers to the wide range of voice-enabled technologies powered by artificial intelligence to help practitioners provide better care to patients.

Combining AI and automation functions, healthcare conversational AI is typically composed of virtual assistants and advanced chatbots. It can automate scheduling of appointments, simulate human conversations, and accommodate details of clinical inquiries. This transformative technology makes patient engagement more seamless, contributing to an overall convenient care experience.

In fast-paced settings like hospitals and clinics, time is a resource that is never scarce but always in demand. Today, conversational AI in healthcare saves time for providers by offering clinical touchpoints and summaries. In turn, benefits go both ways: clinicians are happier and patients feel safer.

What Conversational AI for Healthcare is Not

Since conversational AI for healthcare is a topic too broad to tackle, it’s best to discuss what it is not:

• Agentic AI - These tools typically handle decision-making, as they are systems capable of autonomous initiatives.
• Ambient AI - This AI technology focuses on capturing conversations while running passively in the background.
• Robotic Process Automation (RPA) - It is an automation technology using “bots” to automate repetitive tasks previously done manually.
• Predictive analytics - Based on patterns from historical data, this AI uses algorithms to predict future outcomes.

In this article, we’ll focus on the top use cases of conversational AI in real-world contexts, the benefits, and the examples clinicians typically consider when looking for useful conversational AI features.

Top Conversational AI Use Cases for Healthcare

Use cases for conversational AI in healthcare range from humanizing chat interactions to booking appointments, helping clinicians and patients in various ways. However, it is important to note that this section does not convey types of conversational AI.

Rather, we discuss contexts where conversational AI and other AI functions intersect to create a larger impact on healthcare systems. Main examples are listed as follows. 

Use Case 1: Streamlined Triage and Patient Support

One solution conversational AI offers is the gathering and presentation of details for clinicians' review. This can include automatic analysis, symptom triaging, or even recommendations for care pathways. By optimizing the care process from the outset, clinicians gain valuable time savings, allowing them to engage with or serve more patients.

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Conversational AI tools can be embedded in chat or voice systems to detect unmet patient needs. In some instances, providers offer chatbots that manage wellness check-ins, explain care plans, and facilitate personalized follow-ups.

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By offering multilingual conversational capabilities and 24/7 access, conversational AI removes language barriers and equalizes the general patient experience, making care delivery more accessible, especially outside of clinic hours.

Use Case 2: Clinical Workflow Automation

Healthcare conversational AI makes it possible for AI systems to document patient conversations automatically. Combined with ambient AI functions, it listens, extracts content, and pushes structured SOAP notes into EHRs. An example of a product utilizing this technology is an AI medical scribe.

AI medical scribe providers sometimes include conversational AI chatbots in their offerings. These chatbots act as assistants in that they transcribe patient conversations in real-time so that clinicians can allot more time to facing patients.

Use Case 3: Medication Adherence Monitoring

Conversational AI bots, integrated into telehealth, can help with checking patient adherence to medications and routines in chronic care. This way, AI can not only provide real-time education but can also help reduce readmissions and improve long-term outcomes. Even better, data from these types of conversational AI enablement can be leveraged to aid reporting on patient engagement trends.

Benefits of Conversational AI Technology in Healthcare

Conversational AI doesn’t seek to replace healthcare clinicians. Instead, it allows thoughtful delegation of administrative tasks that consume clinicians’ time, but can safely and effectively be undertaken by AI. Beyond that, conversational AI benefits healthcare in more ways than one:

• Expanded access to care - A study by the CHI revealed that care recipients tend to feel more comfortable disclosing sensitive information to conversational AI agents than humans. This shows that conversational AI expands care access by reducing the stigma or hesitation of patients to disclose information.
• Greater patient engagement - Research from JMIR also showed that usability and adoption of conversational AI usage are positive among healthcare providers. On a broader note, this also contributes to the increase in job satisfaction among them.
• Reduced administrative burden - Healthcare professionals significantly cut down documentation time, which frees them from clerical burden. This was highlighted in a pilot study presented by the SHM.

As healthcare systems become more modern, the question is not whether you have to adapt to modern solutions like conversational AI. It is rather a question of when you start adopting it into your practice.

Before Heidi, Dr. James Woolley, Consultant Psychiatrist at Schoen Clinic Chelsea, shares their concerns about new tech in healthcare: “Amongst clinicians, there’s quite a lot of ambivalence about new IT initiatives. They often end up creating more work.”

Thankfully, they found Heidi, a robust, minimally disruptive conversational AI tool that streamlined their workflow.

“This is where the greatest time-saving has been. We’re now able to squeeze additional patients in if needed in crisis situations, because we are not needing to worry quite so much about having a large chunk of admin time available in order to also complete the work. This, in turn, improves flow along with patient and clinician experience.” 

Real-World Healthcare Conversational AI Examples

Talking about conversational AI use cases in healthcare is one thing, but the minute details of how they improve workflows are often overlooked. To illustrate how conversational AI is transforming healthcare today, let’s take a look at a real-world example: Heidi Health.

Conversational AI Example 1: Ask Heidi

Ask Heidi is a smart chatbox that accommodates prompts through speech or text. You can converse with Heidi for support across a variety of use cases, such as creating a referral letter for patient X to a specialist. If your notes need structure, reformatting, or a complete overhaul, you can Ask Heidi to do so in one go.

Conversational AI Example 2: Text and Voice Interaction

Almost every element of Heidi’s conversational AI platform now supports voice interaction, so you can deliver a more hands-free, conversational experience. To automate your own workflows, you can easily dictate to Heidi or see as it does live transcription during your sessions. This way, you can easily adjust your notes from the data it captured as you deem fit.

Conversational AI Example 3: Heidi Calls

Another real-world example of conversational AI in healthcare is Heidi Calls. While Heidi automatically transcribes your patient conversations in person, you can now instruct Heidi to call a patient, and Heidi will transcribe and summarise the call for you. You can even instruct Heidi to set follow-up sessions with patients before the thought goes out of mind.

Try Heidi Health’s Conversational AI Platform for Free

Heidi is a conversational AI software at the forefront of clinical innovation, ensuring that clinicians like you can come home to dinner on time. It is the medical scribe that incorporates conversational AI to benefit you, your patients, and healthcare administrators. With Heidi integrated into your sessions, you can benefit from free time as it can:

• Schedule automated appointment calls
• Handles inbound calls automatically
• Ask Heidi about guidelines and medication interactions based on notes

Heidi facilitates over 2 million weekly patient consultations, upholding international standards and local regulations, and supports more than 110 languages. The platform ensures data localization for clients in Australia, Canada, the United States, the United Kingdom, and other regions. 

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FAQs About Conversational AI in Healthcare

Is there a difference between conversational AI vs. generative AI?

Yes. Conversational AI allows you to converse with the AI system through speech or text. Generative AI, conversely, is designed to create content that is new, in the form of text, images, or code. Conversational AI mimics a human-like way to respond through chatbots and virtual assistants, while generative AI has a mechanism to generate based on previously learned data.

What is a conversational AI chatbot?

Conversational AI chatbots generally answer questions or respond to a prompt, regardless of its length. This is not to be confused with ambient AI, which focuses on listening, capturing, and analyzing dialogue. While both have distinct functions, they often go together for AI documentation tools, like AI medical scribes. 

How do I evaluate the best conversational AI companies for my needs?

You can start by assessing the needs for your clinic or hospital: What use cases and business goals do you aim for? Additionally, consider the cost-effectiveness of specialty-agnostic AI tools such as Heidi, which can serve various disciplines, compared to AI tools designed for a single specialty. Lastly, consider how it will impact the delivery of high-quality healthcare.

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