2308 04178 Assistive Chatbots for healthcare: a succinct review


AI Chatbots: An Ever-ready Expert to Revolutionize Healthcare

ai chatbots in healthcare

Watson Health by IBM

IBM Watson Health is a well-known AI platform that combines many AI capabilities, including machine learning and natural language processing, to help healthcare practitioners make deft decisions. Data analysis, therapy suggestions, and research discoveries are all aided by it. Consider AiGenics, a case study where the use of AI chatbots boosted patient engagement and resulted in cost savings, to demonstrate the practical impact of these technologies. This exemplifies how AI chatbots are useful healthcare solutions rather than merely theoretical concepts. As we step forward into the horizon of healthcare, it’s undeniable that AI chatbots are set to redefine how we approach medical care and counseling.

ai chatbots in healthcare

Apart from this, with further advancement, chatbots can be made more efficient in diagnosis and leveraged in many more use cases. Patients can talk to Buoy Health about their symptoms, and the chatbot puts all the information together to lay out possible causes. Once this is done, the platform identifies if the symptoms can be treated with self-care or if urgent intervention is required. Buoy Health also guides patients through their options and helps them to make choices that are financially sound for them. Florence is equipped to give patients well-researched and poignant medical information.

How Do Chatbots Perform?

This is a simple website chatbot for dentists to help book appointments and showcase different services and procedures. With this feature, scheduling online appointments becomes a hassle-free and stress-free process for patients. Patients can book appointments directly from the chatbot, which can be programmed to assign a doctor, send an email to the doctor with patient information, and create a slot in both the patient’s and the doctor’s calendar. Patients can trust that they will receive accurate and up-to-date information from chatbots, which is essential for making informed healthcare decisions. World-renowned healthcare companies like Pfizer, the UK NHS, Mayo Clinic, and others are all using Healthcare Chatbots to meet the demands of their patients more easily.

ai chatbots in healthcare

Patient compliance and medication adherence is an ongoing struggle for healthcare providers. Kore.ai healthcare bots can send patients reminders when they need to take their medication or perform exercises, such as in the case of physical therapy. Our bots can also be used to send reminders to patients that their prescription needs to be refilled, or they are due for a routine checkup, and for other health-related issues. Health insurance providers, likewise, deploy our healthcare chatbots to answer common questions related to coverage, claims, and procedures – freeing up agents to focus on more difficult cases and more productive work.

Improve CX in healthcare with an integrated cloud communications approach

They can be expensive, so you should consider the price and make sure it fits your budget. Whether you have a question about features, trials, pricing, need a demo or anything else, our team is ready to answer all your questions. You can at any time change or withdraw your consent from the Cookie Declaration on our website. Gamification is the use of game-like mechanics and elements in non-game contexts to engage users and motivate them to achieve their goals.

ai chatbots in healthcare

They can also choose their preferred therapist and a convenient day and time for their appointment. Moreover, as patients grow to trust chatbots more, they may lose trust in healthcare professionals. Secondly, placing too much trust in chatbots may potentially expose the user to data hacking. And finally, patients may feel alienated from their primary care physician or self-diagnose once too often. With a messaging interface, the website/app visitors can easily access a chatbot. Chatbots may even collect and process co-payments to further streamline the process.

Understanding B2B Customer Journey Map with Stages & Examples

Technology is constantly changing the face of the healthcare industry, and AI in healthcare presents a new opportunity for this evolution to continue. Support a diverse range of patients and staff with our inbuilt support of multiple languages. The information related to patients is treated with the utmost care, ensuring it remains private and protected. Patients can openly communicate about their health matters without the fear of their information being compromised. The ability to interpret unstructured medical data is a remarkable capability of Generative AI.

Healthcare chatbots can offer this information to patients in a quick and easy format, including information about nearby medical facilities, hours of operation, and nearby pharmacies and drugstores for prescription refills. They can also be programmed to answer specific questions about a certain condition, such as what to do during a medical crisis or what to expect during a medical procedure. While AI chatbots can provide preliminary diagnoses based on symptoms, rare or complex conditions often require a deep understanding of the patient’s medical history and a comprehensive assessment by a medical professional. Undoubtedly, medical chatbots will become more accurate, but that alone won’t be enough to ensure their successful acceptance in the healthcare industry. As the healthcare industry is a mix of empathy and treatments, a similar balance will have to be created for chatbots to become more successful and accepted in the future.

Life is busy, and remembering to refill prescriptions, take medication, or even stay up to date with vaccinations can sometimes slip people’s minds. With an AI chatbot, you can set up messages to be sent to patients with a personalized reminder. They can interact with the bot if they have more questions like their dosage, if they need a follow-up appointment, or if they have been experiencing any side effects that should be addressed. People want speed, convenience, and reliability from their healthcare providers, and chatbots can help alleviate a lot of the strain healthcare centers and pharmacies experience daily. Kommunicate’s healthcare AI chatbot can help insurance companies significantly reduce the time and cost of processing claims. By leveraging Kommunicate’s powerful NLU, the AI chatbot can interact with customers to collect all the necessary information required to process a claim accurately.

A US-based care solutions provider got a patient mobile app integrated with a medical chatbot. The chatbot offered informational support, appointment scheduling, patient information collection, and assisted in the prescription refilling/renewal. Healthcare chatbots are the next frontier in virtual customer service as well as planning and management in healthcare businesses. A chatbot is an automated tool designed to simulate an intelligent conversation with human users. Integrating AI into healthcare presents various ethical and legal challenges, including questions of accountability in cases of AI decision-making errors. These issues necessitate not only technological advancements but also robust regulatory measures to ensure responsible AI usage [3].

Use Case of Generative AI Chatbot in Healthcare and Pharma #3. Prescription summary

First, this issue stems from the lack of a common operational definition for secondary outcomes in the context of chatbot-based interventions. Second, because the AI chatbot intervention domain is relatively new, there are very few measures on feasibility, usability, acceptability, and engagement with tested reliability and validity. Therefore, the researchers in the selected studies had to develop their own measures for assessing outcomes. This led to inconsistency in the measures and their operational definitions across the studies. Future studies should shape the development of common operational definitions for each of these outcomes to enable comparison and standardized reporting. Furthermore, future AI-chatbot–based intervention studies should follow the National Institutes of Health’s quality assessment criteria for controlled intervention studies [19] to assess their studies’ internal validity.

ai chatbots in healthcare

And what’s truly fascinating is how the capabilities of AI chatbots are poised to expand, propelling us toward a future where healthcare is more personalized and accessible than ever before. Furthermore, the cost efficiency achieved through chatbots isn’t just a financial advantage. Patients experience swifter responses, streamlined processes, and improved overall interactions. With powerful features, Healthcare chatbots bring a lot to the table, offering timely information, personalized attention, and improved engagement. This medical chatbot, specifically, helps patients who are fighting against cancer. OneRemission helps cancer patients and survivors by providing them all the information they need including, diets, exercises, post-cancer treatments, etc.

Personalized healthcare is just a conversation away

As AI chatbots continue to evolve and improve, they are expected to play an even more significant role in healthcare, further streamlining processes and optimizing resource allocation. A healthcare chatbot example for this use case can be seen in Woebot, which is one of the most effective chatbots in the mental health industry, offering CBT, mindfulness, and dialectical behavior therapy (DBT). As a result of this training, differently intelligent conversational AI chatbots in healthcare may comprehend user questions and respond depending on predefined labels in the training data. When every second counts, chatbots in the healthcare industry rapidly deliver useful information. For instance, chatbot technology in healthcare can promptly give the doctor information on the patient’s history, illnesses, allergies, check-ups, and other conditions if the patient runs with an attack.

  • Automate summarization of appointment with prescription, diagnosis and other information.
  • The choice of WhatsApp as a platform was a key factor in ensuring the wide reach of this solution, given that WhatsApp is the world’s largest messaging platform, with over 400 million users in India alone.
  • However, the scope and inclusion criteria of this review had several limitations.

This means that the patient does not have to remember to call the pharmacy or doctor to request a refill. The chatbot can also provide reminders to the patient when it is time to refill their prescription. Whatever it is, patients can ask questions and get evidence-based answers back. That happens with chatbots that strive to help on all fronts and lack access to consolidated, specialized databases. Plus, a chatbot in the medical field should fully comply with the HIPAA regulation.


Large-scale healthcare data, including disease symptoms, diagnoses, indicators, and potential therapies, are used to train chatbot algorithms. Chatbots for healthcare are regularly trained using public datasets, such as Wisconsin Breast Cancer Diagnosis and COVIDx for COVID-19 diagnosis (WBCD). Emergencies can happen at any time and need instant assistance in the medical field. Patients may need assistance with anything from recognizing symptoms to organizing operations at any time. Harnessing AI capabilities, chatbots can provide thorough aid and counsel to patients, as well as follow-up consultations and treatments.

ai chatbots in healthcare

Easily test your chatbot within the ChatBot app before it connects with patients. However, for effective chatbot development, you will need a specialized team of software developers who are skilled in machine learning technology and tools. The chatbot helps with setting food reminders and keeping track of food intake. She creates contextual, insightful, and conversational content for business audiences across a broad range of industries and categories like Customer Service, Customer Experience (CX), Chatbots, and more. Qualitative and quantitative feedback – To gain actionable feedback both quantitative numeric data and contextual qualitative data should be used.

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