When it comes to increasing patient satisfaction, reducing readmission, and improving your bottom line, what are the possibilities for healthcare chatbots? Technological advances have made a world of difference in the delivery of quality healthcare to patients across the world. From connected medical devices to electronic health records, technology provides doctors and nurses a way to better connect with their respective patient populations in ways that were never even thought of 20 years ago.
What makes any healthcare technology successful is the ability to engage with patients. Experts believe that by involving the patient in their own care, it is possible to greatly reduce the risk of readmission. Secure messaging through mobile apps like our own Qliq Secure Texting has gone far to address these engagement issues by bringing the patient into the conversation with their care team. Telehealth strives to take this further by creating one-on-one connections via video between patients and remote provider locations. Now, there is an opportunity to combine communication technology with artificial intelligence as a way to bridge the remaining communication and engagement gaps.
What is a Healthcare Chatbot?
Enter chatbots. Healthcare chatbots are software integrated into either a website or mobile app and possess any combination of the following attributes:
- Natural Language Processing: The ability for a chatbot or other form of artificial intelligence to understand aspects of language, including syntax and semantics from users of various backgrounds.
- Conditional Logic: Based on the responses a user provides, chatbots that use conditional logic are able to route conversations to the appropriate database or individual.
- Contextual AI: Just as the name suggests, contextual AI takes into consideration the intent of the user as they ask questions and submit responses, thus ensuring the best relevant conversation takes place.
The sophistication of these attributes healthcare chatbots may vary but one thing must remain true for a chatbot to engage patients - it must have bi-directional input. Often times these apps are used as the first point of contact for customer service or technical support needs. They are programmed to respond to basic inquiries utilizing conditional logic and basic database information. Less common, but growing applications rely on artificial intelligence to help provide more in-depth, actionable responses that take intent and context into consideration.
The Rise of Chatbot Technology
Industries across the board currently rely on chatbot technology to connect with customers. This communication can range from general customer service or sales inquiries to technical support and more advanced conversations. Below are a few examples of how several industries are currently using chatbots to expand their relationships with customers.
Retailers, both online and those with brick-and-mortar locations, rely on chatbot technology to serve as a touch point between customers and an online marketplace. Depending on the products being sold, those conversations can range in topic from basic pricing questions to more advanced marketing-driven dialog designed to address items abandoned in a shopping cart. Fashion retailer H&M has been relying on chatbot technology since 2016. Instead of existing on their lives site, this chatbot operates in the Kik messaging app, which is actively used by 40% of US teenagers (the brand’s core demographic).
Banking takes a slightly different approach when it comes to using chatbots. Their aim in many cases is to improve customer satisfaction and engagement with their inventory of financial products. By allowing verified access to backend data, banks can provide a nearly teller-like experience by way of browser. By doing so, customers are able to view account balances and bank statement as well as more advanced tasks such as creating a deposit, transferring funds, and even seek advice on saving and investing. The USAA app employs a chatbot to answer many basic questions and allow customers to make changes "on the fly" for example: Tell the chatbot "I'm going out of town" and a travel note will be added to your account to prevent your strange new debit card activity in Peru from being flagged.
Commercial Air Travel
Airlines, like many of the industries listed above, rely on chatbots to better engage with customers. This technology is deployed at various levels in order to send announcements, provide aid with ticketing, facilitate web check-ins, produce personalized search results, and connect them with travel options outside of a simple seat on a plane. Aeromexico, KLM, and a handful of other airlines rely on Facebook messenger to host their chatbot platform.
Healthcare Chatbot Use Cases
The current state of chatbots in healthcare is something resembling customer-facing applications such as the ones mentioned above.
Traditional Healthcare Chatbot Use Cases
- Scheduling appointments
- Basic Q&A around medications
However, there is a growing opportunity for healthcare chatbots to do much more benefit than current solutions.
Advanced Healthcare Chatbot Use Cases
- Scheduling visits and procedures
- Answering targeted medical questions
- Interacting with patients post-discharge in order to reduce readmissions
- Performing comprehensive medication review
Choosing the Right Healthcare Chatbot Solution
Who is leading the way? While there are many lists of applications, all with their own top 5 or 10 chatbot solutions, it's worth looking at what meets the needs of a particular industry or company. In terms of healthcare, there are just a handful of simple requirements that are vital to the successful rollout and adoption of such technology.
- First, the design must be simple so as to not intimidate users. For example, a simple interface that resembles basic SMS messaging produces few barriers for novice users. Consider a vendor that lets you design your own bot or guides you through that process as opposed to only offering "out of the box" solutions.
- Secondly, the interaction must be authentic. Most organizations utilizing chatbots do so with a certain level of Artificial Intelligence built in. The conversation flow must be able to resemble something organic and any transition between the automated agent to a live human must be seamless so as to avoid interruption.
- Third, and possibly most important is the incorporation of contextual AI, which allows your chatbot application to understand the intent of the patient or clinician who has initiated the dialog. Below are a few examples which illustrate the important role context can play in chatbot discussions:
- Inpatient: Some people think this means anyone in a hospital. However, CMS defines inpatient as anyone who stays OVER two midnights in order to bill an account at that level. If not, those patients must be billed as outpatient or day-surgery.
- Transfer: There is a misconception that transfer refers to a patient being moved from one facility to another. However, it can also refer to their level of care internally. When a patient moves from surgery to PACU, that is a LOC transfer. When they move from PACU to the unit, that is considered yet another transfer.
Implementing a Healthcare Chatbot
Once you have chosen your healthcare chatbot, there are several considerations that must be planned for in order to ensure a successful implementation.
Focus on User Experience
The end-to-end user experience is critical. Make sure that any pre-built conversations produce the desired result. What is the most basic information needed at the initial start of the conversation? What does the workflow look like when users are presented with yes/no or multiple choice questions? Conversely, how does the chatbot respond to questions that are open-ended? Will patients feel as comfortable interacting with a chatbot as if it were a human being? The perception of individual attention can go far in achieving successful adoption.
Introduce in Phases
As with most solutions, chatbots should be rolled out incrementally across an organization. Instead of trying to boil the ocean, consider taking the project in more manageable chunks. For example, design your first healthcare chatbots around only one or two specific use cases in order to provide for a controlled environment where any issues can be addressed easily. Once chatbots have a proven use case, it will be much easier to not only sell the idea to other department heads but also provide real-life testimonials from existing users.
QliqSOFT and Healthcare Chatbots
Secure communication is at the core of everything we do here at QliqSOFT. That’s why we are excited to announce the development of a new chatbot tool that combines artificial intelligence and live-agent interaction all while remaining in the same familiar environment our secure texting users have relied on for years. If your organization is looking to take a leap into the future of clinical collaboration, contact us today.
A lifelong communicator, this Tennessee native got his start in broadcast news before branching out into public media, corporate, communications, digital advertising, and integrated marketing. Prior to joining QliqSOFT as the company's first marketing team member, Ben shared his talents with organizations that include the University of Alabama, iHeartMedia, and The Kroger Company.
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