Surveys show that medical institutions today face three main challenges: competition, staff retention, and staff burnout.
Doctors complain that they have to spend nearly two-thirds of their time on routine paperwork, which results in decreased motivation. Digital solutions like EHR Data Analytics and AI chatbots allow fast document processing and better communication between departments and medical institutions. It relieves the workload and enables medical professionals to spend time more effectively.
In this post, experts from the Belitsoft software development company share their insights about AI-powered chatbot applications in healthcare.
Supplementing without substitution
Narrow AI tools have been in healthcare for quite some time already. They help read MRI scans and X-rays, analyze the database of similar medical cases, and suggest diagnoses.
Generative AI demonstrates a broader scope of functions. ChatGPT appeared in 2022 and demonstrated its main functions of generating text and images. In healthcare, GenAI can create call center scripts, extract and summarize the data from medical documents, provide laboratory results upon request, and deal with other administrative procedures.
People believe their health issues are unique and machine algorithms cannot be helpful in their treatment. Only 10% of US patients would feel comfortable with AI-generated diagnoses and recommendations. At the same time, most interviewed doctors rely on AI-powered diagnosis, with only 2% being skeptics. Therefore, medical staff can use the functionality of AI to help them conduct research or perform paperwork. However, any critical decision should be taken with a “human in the loop” approach, i.e., supervising the AI assistants.
AI chatbot scope of responsibility
While building rapport with patients remains the duty of humans, chatbots can help with administrative procedures and provide general healthcare information to customers.
Gathering symptoms
Virtual assistants can ask about the symptoms, frequency, and intensity, suggest a diagnosis and tests, and make an appointment with a relevant specialist. Integrating AI chatbots with EHRs and business intelligence tools allows for standardized medical data and its safe accessibility across medical providers. As a result, any doctor can find the whole history of a patient, make a thorough diagnosis, and develop an efficient treatment plan.
Another option for AI applications at the stage of diagnosis is asking ChatGPT to choose the right diagnostic method. The latest research in radiology showed that ChatGPT 4 is 98.4% right in selecting the method of relevant breast cancer screenings. Doctors dictate the symptoms to the chat and offer a range of possible tests, like an MRI, ultrasound, or mammogram. The chat selects the best option for a particular case.
Counseling for mental health
AI algorithms know how to support people suffering from depression or anxiety. Thus, a startup called Sonia asks questions about poor sleep, stress, and relationship problems like a real therapist. If any serious situation, like suicide or violence risk, appears, Sonia transfers the user to the national hotline.
Attracting leads
AI chatbots can provide additional sources of information for potential customers and serve as a marketing hook. The fitness startup Wellen introduced an AI chatbot on the website. The project targets people with bone health issues. Visitors to the site can ask the chatbot questions about spine health, osteopenia, and osteoporosis. The bot generates its answers based on blog posts. It notifies at the beginning of a conversation that it does not provide professional medical advice. Thus, the chatbot serves as a competent librarian for the visitors.
Performing triage
AI chatbots help doctors, at peak times, deal with the most severe cases first, which leads to relevant prioritizing of resources.
Conducting research
When medical experts need to summarize theoretical information or clinical trial data, they can ask chatbots to provide them with relevant resources from the library and EHRs.
Scheduling appointments
It might be a challenge to get through to the medical call center to fix an appointment with a doctor. Using a chatbot is, conversely, a swift experience for customers. Virtual assistants can also cancel or postpone meetings if necessary.
Refilling prescriptions
Online retail pharmacies increase customer satisfaction with AI chatbots. The bot asks users their names, email, last visit to the doctor, and the required medicine. After filling out the prescription, it finds the pills in the pharmacy and forms an order for delivery. The bot allows patients to avoid standing in lines and helps them follow the treatment plan rigorously.
Benefits vs. challenges
AI chatbots provide clear advantages to healthcare centers, such as:
- Cost savings, as there is no need to hire call center agents and real operators to answer queries on the website or in the messenger.
- 24/7 availability, as chatbots can answer customers’ questions outside business hours.
- Better resource allocation, as medical staff can spend less time on routine paperwork and more time on practice.
On the flip side, several issues evoke controversial evaluations of AI-generated chatbots in the medical sphere.
Regular data updates
Clinical trial data, WHO guidelines, and recommendations are constantly changing. AI chatbots use machine-learning algorithms that should be up-to-date with the most recent data. Otherwise, the information might be irrelevant or even harmful to patients.
How to cope with that? Make sure your chatbot has all the necessary API connections and integrations. The data should be dynamically changed to ensure always-relevant content.
Disclosing sensitive information
Cybersecurity is a matter of serious concern, as criminals use sophisticated schemes to steal personal data. Behavioral data or information shared by users in the chat can be hacked and transferred across the Internet.
How to cope with that? Any software should comply with safety regulations. In March 2024, the White House Office of Management and Budget (OMB) issued a policy to mitigate the risks of applying AI tools. According to the policy, people should be aware of talking to AI-generated assistants, and chatbots cannot ask customers to share their sensitive data or irrelevant information.
Biased recommendations
AI chatbots train on the datasets. Middle-aged white men comprise the majority of the clinical data. As a result, chatbots might generate faulty information for African Americans, the indigenous, people with disabilities, or those residing in remote areas. The mentioned groups form the limits of the scope of AI chatbot competence.
How to cope with that? The solution lies in adding relevant information to the machine learning algorithms steadily. The principles of open science and sharing diverse population groups’ data anonymously form an objective AI dataset. Besides, the OMB policy highlights that a human should supervise any AI-powered critical diagnostic decision and therefore check the relevance of the data generated by AI.
Final thoughts
With AI chatbots, healthcare businesses can improve customer experience and ease the routine workload for the staff. A productive AI assistant needs constant updates of the knowledge base and iterary testing. Before implementing an AI chatbot, a company board should consider the following points:
- What are the goals of a chatbot? Will medical staff use it? Or will it be used as a source of information for potential customers on the website?
- What are the current privacy and data security regulations?
- Is it more relevant to develop a solution from scratch or use an open-source product?
