To accelerate the technology adoption process and to give those leaders greater confidence in their selections, Panda Health devoted its team of digital health experts to extensively evaluate conversational AI industry solutions/tools. Panda conducted market research on best use cases and practices to build on the input we received from our buyer health systems to define a clear set of criteria to be met. Panda hosted live demos, performed thorough Information Security evaluations and tested live instances of supplier chatbots.
Panda then sifted through scores of chatbot solutions – both health care-specific and industry-agnostic – to generate a long list of companies meeting the health care organizations’ use-case needs and criteria. With a custom RFP that actually got rave reviews from suppliers, Panda narrowed that group down to a small number of best-in-class providers that were invited to join the Panda marketplace.
Over the course of that evaluation process, Panda identified three key considerations that any health system should keep top-of-mind when adopting AI chatbot technology:
Consideration One: Ensure AI chatbots really are conversational.
Health systems should attempt to peel back sales claims by reference checking these live chatbot solutions via the health systems they are deployed in. The truth is many health care chatbots are not as conversational as they claim. If a patient says they have cough and fever symptoms, for example, a chatbot may be able to suggest a primary care provider but little else. The real giveaway is when a chatbot fails to understand the patient, hits a dead-end, and then keeps asking, “How can I help you?” No technology – not even human intelligence – is perfect, and there is always a risk of hitting a dead-end. But the leading conversational chatbots minimize these shortfalls and at their best they have the ability to ask probing questions to fully engage the patient. Conversational chatbots should have straightforward conversations with intuitive, natural language experiences—all with HIPAA compliant chat platforms.
Lesson Two: Help patients meet their goals.
Advanced AI chatbots should be able to determine intent, allowing patients to search for relevant providers across multiple locations and self-schedule appointments in real-time. With the ability to create and manage complex question-and-answer interactions, advanced chatbots connect patients to actionable solutions like visiting a specialist or scheduling a test. For improved experiences, robust conversational AI also allows users to select their preferred communication channel, including text-based and voice-based options across multiple languages. By meeting patients where they are, health care organizations can optimize navigation and discoverability.
Lesson Three: Seek rich and actionable analytics.
Healthcare teams can better understand user searches with rich analytics features to determine at what point patients leave the chatbot experience and where they go when they leave. Robust analytics provide actionable insights to determine how well patients’ needs are being met—and help inform more reliable decisions for the future. By integrating the insights with broader digital marketing metrics, health care organizations can tailor consumer engagement strategies to granular segments of their market.
Panda Health can help your organization find best-in-class technology that empowers your patients with conversational AI and creates a robust digital front door. If you are a health care organization looking to elevate and accelerate your digital strategy—or a digital health company with best-in-class technology—reach out to one of our experts.