In this era of minimizing in-person interactions and increased utilization of digital tools for better patient care, HIPAA compliant ChatBOTs are helping many healthcare organizations, testing labs with its conversational interfaces at the front-end and analytical dashboards at the backend. These solutions help the organizations better engage with their patients through intelligent, remote and effective interactions which enhances the user experiences and extend the reach of organization's various offerings for their patients. ChatBOT connect with patients in cost-efficient and personalized ways than the traditional channels and has the potential to make more impact. They offer users a simple, seamless and efficient experience to get the answers they are looking for in an interactive way with the required actionability. The organizations offering ChatBOTs also get the effective mechanism to gather required information from their patients in an interactive way. Because of the meaningful information exchange, ChatBOTs are preferred as versatile platform for patient interactions— for the basic tasks like symptoms checker, gathering the family history to the most complex tasks like assessing their risk for hereditary cancers or triaging them to the right testing options based on the various guidelines. Data shows that people are 3.5 times more likely to respond to ChatBOTs notifications than an email, and 4 times more likely to click through a link found in a message.
Using the Traditional methods like in-person/tele/email communications, about 1 in 12 individuals who have the family history of cancer is found to be eligible for hereditary cancer screening (Scheuner MT et. al) while the ChatBOT based patient triaging methods have identified 1 in 4 individuals with family history of cancer as eligible candidate for genetic screenings (Dohany et al).
ChatBOT can engage on a 24/7 basis, handling patient enquiries instantly and on-demand basis, which would allow medical information staff/counsellors more time to handle more complex questions if any. Eventually over the time chatBOT get trained to answer increasingly complex questions by machine learning /deep learning capabilities using the training datasets. ChatBOT transcripts also provides insights and analytics for the needs of healthcare providers and patients which can be used to improve services and also the quality of the answers the chatBOT gives.
Many users especially the younger population feel more comfortable talking to a 'virtual companion' about sensitive subjects than talking to a human. They are particularly excited about this technology – 82% of millennial patients would like to see more use of chatBOTs in the healthcare systems for instant healthcare support they need on ongoing basis. This protocol gives them the freedom of on-demand and instant healthcare experience.
Major advantage that any healthcare organization can get from ChatBOT is about handling FAQs (frequently asked questions) from patient community. All chatBOT answers can be pre- approved and if a chatBOT doesn't understand a question, it can direct the user to human help. For simple tasks, chatBOT remove the opportunity for human error. They can't go 'off script' and won't 'forget to respond' to multiple user enquiries. They also have almost unlimited capacity so can respond to peaks in demand. ChatBOT can proactively flag some interactions to reporting channels, wherever there is need for immediate action.
ChatBOT present a low risk, low cost way for organization to carve out a reputation for their brands as innovative, responsive solution providers. Patient interfacing/experience is one of the most obvious applications for automation — and healthcare providers are trying their best for near-total customer service automation, at least for routine queries. ChatBOTS give them additional advantage over their competing organizations and help retain their pool of patients.
Currently chatbot's have come a long way from the static and limited versions users first encountered. Part of this is due to a gradual shift away from rules-based AI (where a chatBOT responds according to pre-determined rule sets) to a fully realized NLU (natural language understanding) based implementations. In the latter, a chatBOT can continually learn and expand its capabilities, growing more accurate and responsive over time.
These AI powered chatBOT applications are used in Healthcare in:
- Automated and remote patient triaging and symptom checkers for various testing and treatment protocols based on the guidelines
- Providing and gathering required information to/from patients in interactive ways
- Carrying out the personalized risk assessments for the patients through innovative interfaces
- Accurate and personalized testing and follow-up recommendations for the patients
- Help patients understand test results and insurance plan benefits
- Getting right insights and analytics for operational efficiencies through the AI powered dashboards