Can Healthcare Chatbots Improve Care Access and Patient Experiences?
November 16th, 2020
A study on healthcare chatbots looks at their ability to improve care access. Read about the study and uses cases for chatbots in healthcare.
Chatbots are useful for more industries than just eCommerce. Now that consumers are comfortable using them, they can be a great asset to healthcare. A new study published in JAMA looks at healthcare chatbots and their impact on care delivery during COVID-19. The results indicate that there’s really no distinction between chatbot or live agent when patients receive high-quality service.
About the Study
Researchers conducted an online experiment with 371 patients who interacted with a COVID-19 screening session. They used a two-by-two method of evaluation, using two agent types (human vs. chatbot) by two patient severity levels (mild vs. severe). The participants watched a short video vignette of a fictional text chat between an agent and user. The script of conversations came from screening questions from the CDC.
Subjects knew the video was either a chatbot or a live agent, but the videos were the same. Thus, the study was a comparison of chatbot and human agents with the same capabilities.
When users believed the agent’s ability to be the same, they had equally positive responses to the chatbot and live agent. The biggest motivating factor was trust in the provider. There was a slight negative bias toward chatbots but not significant. Other factors in how the user “graded” the experience were patient compliance, integrity, and benevolence.
“Ability and integrity are typically more important for instrumental outcomes associated with transactions (e.g., purchasing) because users are most concerned with whether the technology will work as intended to complete the transaction,” researchers said in the study.
Analysis of the Study: Are Healthcare Chatbots Effective?
As noted, it depends on the quality of the experience. Chatbots aren’t perfect, but neither are humans. Chatbots can improve through interactions, powered by AI and machine learning. They are also highly scalable, cost-effective, and deliver consistent quality.
As more consumers adopt technology as part of their everyday lives, using a chatbot as a patient is no different than using it as a customer. Further, chatbots don’t have bias and aren’t making any “judgments” on patients. This scenario could actually drive patients to disclose more information, leading to a better next step (i.e., testing, telemedicine appointments, etc.).
How Can Providers and Payers Use Chatbots?
Beyond just screening for COVID-19 or any other possible disease, there are many potential uses for chatbots in healthcare.
Here are some use case ideas:
- Assist with appointments: Push patients to chatbots to schedule follow-ups, lab tests, or procedures. Providers often have little capacity to answer the phones, which is frustrating for patients. Chatbots could streamline this and take the burden off front office staff.
- Medication reminders: Medication nonadherence costs the healthcare system billions and endangers patients. Pharmacies could enable chatbots through their app to send reminders to take prescriptions daily and prompt them to get their refill.
- Billing questions: Payers could use chatbots to interact with members when they have questions about claims. This would be broad information but may help some members with what they need, so they don’t have to call.
- Integration with EHRs: As part of the new interoperability rule, patients must have access to their medical history through a portal. This portal is most often a feature of their EHR. Adding chatbots to the system could help patient engagement, queries, and requests.
Healthcare Chatbots Adoption Likely to Rise
Based on the new study and others with similar findings, consumers have no issue interacting with chatbots. It’s all about quality and capabilities. There are many opportunities to leverage chatbots in the healthcare ecosystem. However, sometimes these deployments hit delays due to a lack of internal IT bandwidth.
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