In a recent blog post, What is Conversational AI and How is it Better than a Chatbot, I discussed the value of Conversational AI and how companies are adopting the technology to optimize operational efficiency and improve experiences for consumers across industries. In this post, I will discuss how companies across the healthcare spectrum, from drug manufacturers to providers to payers, are using conversational AI to provide seamless experiences for interacting with patients.
COVID-19 caused major disruptions in every industry, but arguably impacted the healthcare sector the most due to the overwhelming strain on the system and the need to rapidly adapt to providing virtual care using digital technology. Conversational AI is one of the key technologies being implemented across the healthcare ecosystem to solve the challenges providers, manufacturers, and payers have faced in these challenging times.
Conversational AI Uses Cases for Providers
As the pandemic accelerated the adoption of digital technologies for providers, the use of automation has become even more critical for providing communication and support to patients outside of the office.
It is no longer the case where a portal is enough to provide the experience patients expect. Patients expect to interact with providers across multiple channels and to access their health information across desktop, mobile, phone, text, and email.
Conversational AI is being leveraged by providers to interact with patients to quickly resolve inquiries and provide care when and how they expect. Some examples are:
- Automated Scheduling
- COVID-19 Symptom Checking
- Location Finder
- Co-Pay Assistance
- Patient Onboarding
- And More
Conversational AI Use Cases for Life Sciences & Pharmaceutical Companies
In addition to interacting with providers, patients often interact with drug manufacturers and life sciences companies once they have been diagnosed with a disease and are seeking treatment with a specific therapeutic drug. As access to health information via digital resources has increased over the last decade, patients have also become more involved in managing their own health and no longer solely relying on their doctor for health information. This has led to increased interactions between patients and pharmaceutical companies directly.
Conversational AI is being leveraged by pharmaceutical companies to make those interactions with patients and caregivers seamless across the patient journey. Some examples are:
- Integration with Patient Support Programs
- HCP Locaters
- Co-Pay Information
- Medication Reminders
- Augmentation of Support for Disease Management
Conversational AI Use Cases for Payers
Just as patients expect providers and pharmaceutical companies to interact across channels and resolve their health concerns quickly, they have the same, if not higher, expectations related to their healthcare insurance and coverage. The rising costs of healthcare and potential of increased regulation has shined a spotlight on Payers which has led to increased scrutiny from their consumers (patients). Additionally, as the pandemic fundamentally changed how and when patients received care from providers, the need for payers to adapt and scale to provide support for patients has never been higher.
As detailed above there are many potential use cases within the healthcare space for conversational AI. Even with an end in sight to the pandemic (hopefully), the shift to complete digital adoption within the healthcare ecosystem is going to remain. Patients will continue to expect providers, manufacturers, and payers to create frictionless experiences for interactions. Conversational AI is being leveraged to provide patients the experience they expect and the care they need to ensure successful health outcomes.
If you are in the healthcare space, and interested in learning more about Conversational AI and how to get started Anexinet’s 3-week Conversational AI Strategy & Roadmap Kickstart will ensure your organization takes the right strategic approach to adopting Conversational AI.
Director, Omni-Channel Analytics
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