How syncing wearables with AI chatbots can accelerate recovery time

Smart integration of AI chatbots and data collected by wearable devices can help patients and health care providers respond to early signs of illness.

By Nate MacLeitch, QuickBlox

More effective public health and medical interventions could save 1.2 million lives per year, according to the Organization for Economic Cooperation and Development (OECD).

But the healthcare industry isn’t solely responsible. There is usually a gap between identifying an illness and seeking medical attention. Even when a patient feels unwell, they often don’t know the best path of care and may avoid medical support because they minimize their symptoms, lack physical access to local healthcare, worry about healthcare costs, or simply don’t have a doctor.

Wearable medical devices can bridge this gap by monitoring vital signs — often remotely — to determine irregular behavior in real-time. That data might be most useful when the necessary personnel receive alerts and can act on them seamlessly. This is where integrated AI chatbots facilitate communication and incentivize action for the patient and appropriate healthcare professionals.

AI chatbots and wearables work together, for example, to help guide exercises based on sensor feedback, or creating appointments and consultations based on sensor data.

Let’s look closer at the devices available today and how synchronizing real-time AI chatbot features can support patients.

Wearables help in monitoring and feedback

Many fitness trackers and medical-grade devices accurately track heart rate, sleep patterns, and activity levels, storing the data on a phone, smartwatch or the cloud. These healthcare wearables use biosensors to detect biological, chemical or physical signals and convert them into measurable electrical or optical alerts.

Continuous monitoring and wearable biosensors have experienced remarkable growth and are critical diagnostic instruments for AI-assisted human healthcare. These tools provide a real-time data feedback loop for patients and healthcare professionals.

While there is still work to do before we can display blood-glucose levels data in real-time, the FDA-approved Medtronic MiniMed Gold is an electrochemical-type glucose sensor that uses an enzyme (i.e., glucose oxidase, or GOx) to measure blood glucose levels every 10 seconds over three days, showing opportunity in the area.

With real-time access to a patient’s vital signs, medical teams can track recovery progress and identify irregular behavior, enabling them to take action before symptoms get more severe. We see this with Firstday Healthcare which provides FDA-approved wireless sensors to monitor newborn babies’ vital signs from home. In the case of an abnormal data read or specific event such as a high heart rate, respiratory rate or skin temperature, integrated AI chatbots can send an automated alert to a parent’s phone or iPad. Operating as a command center, the communication platform would open a channel to contact the appropriate healthcare provider, who would have access to those vitals in real time.

AI chatbots as personal health companions

AI chatbots excel at interpreting data from wearables and smart home systems. Their intelligent algorithms analyze vast datasets from sources like electronic health records (EHRs) and medical research to predict issues in chronic conditions and aid in the early detection of diseases like COVID-19. However, that’s not all they excel at.

Natural language processing (NLP) and sentiment analysis have enabled intuitive communication tools that interpret data and translate it to another language, a digestible, emotionally supportive tone, or even convert text to video demonstrations.

A study examining 129,400 mental health website visitors found the number of referrals from using chatbots rose by 15%, including even larger increases among underrepresented groups who are less likely to seek help. Chatbots compliant with the Health Insurance Portability and Accountability Act (HIPAA) let hospitals offer personalized health assessments based on data from wearables to create a safe, judgment-free platform for patients to express their concerns and receive the required help.

It’s important to note that in the study, the detailed information the chatbot collected reduced the time human clinicians needed to assess patients, improving assessment quality and reducing the pressure on staff.

Thanks to their 24/7 availability, chatbots can offer continuous support and motivation to patients who have trouble accessing healthcare, breed fear in self-diagnosis, or misunderstand their condition and treatment. AI chatbots can also break down complex prescriptions and relay information from doctors, send alerts based on irregular data inputs, and facilitate necessary touchpoints, whether automatically opening a direct chat or scheduling an appointment.

Risk mitigation in medical use of AI chatbots

Chatbots are only as intelligent as their training data and will not have the same knowledge as a human healthcare professional, which is why healthcare providers need to remain in the driver’s seat.

When patients request medical advice or an alert from a wearable device is triggered, automated chatbot responses must be approved by medical teams with features to edit and simultaneously train the bot before sending, saving hours of prescription writing. Healthcare providers should include mechanisms for patients to escalate the conversation to a human healthcare professional in sensitive scenarios where the chatbot cannot respond.

By regularly updating the chatbot’s knowledge base with the latest medical information, wearable device data and diverse dataset training, healthcare professionals can enhance the accuracy and understanding of automated response revisions.

With regards to data privacy, transmitting sensitive medical information through a chatbot raises concerns about unauthorized access or data breaches. For this reason, ChatGPT and other versions of conversational AI were not regarded as HIPAA compliant. More recently, however, OpenAI and others have started to offer Business Associate Agreements (BAAs) to some healthcare organizations, certifying their chatbots as HIPAA compliant.

Security measures include robust encryption and protocols to protect user data and guarantee that patient requests, medical history and all other data used in the input cannot be stored by a third party.

In every use case, it’s essential to communicate the limitations of the chatbot to patients and staff, emphasizing both the data policy and that it is a tool for information and support, not a substitute for professional medical advice.

While technology cannot claim to be a doctor of all specialties, it can be trained as such. It can comprehend vast datasets from EHRs, diagnosis analysis, radiology scans and medical research. Pairing these insights with wearable device monitoring provides a comprehensive tool to detect warning signs of illness and shows enormous potential in reducing recovery time by taking action early.

Nate MacLeitch, the CEO of AI communication platform QuickBlox, began his career as a trade representative for the State of California in London and has held key leadership positions at WIN Plc (now Cisco) and Twistbox Entertainment (now Digital Turbine). He is also an advisor and investor in startups like Whisk.com, Firstday Healthcare and TechStars.

How to submit a contribution to MDO

The opinions expressed in this blog post are the author’s only and do not necessarily reflect those of Medical Design & Outsourcing or its employees.