Medical Chatbots Use Cases, Examples and Case Studies of Generative Conversational AI in Medicine and Health

Through the rapid deployment of chatbots, the tech industry may gain a new kind of dominance in health care. AI technologies, especially ML, have increasingly been occupying other industries; thus, these technologies are arguably naturally adapted to the healthcare sector. In most cases, it seems that chatbots have had a positive effect in precisely the same tasks performed in other industries (e.g. customer service). Furthermore, there are work-related and ethical standards in different fields, which have been developed through centuries or longer.

Dr. Rachel Goodman and colleagues at Vanderbilt University investigated chatbox responses in a recent study in Jama. Their study tested ChatGPT-3.5 and the updated GPT-4 using 284 physician-prompted questions to determine accuracy, completeness, and consistency over time. I will analyze their findings and present the pros and cons of incorporating artificial intelligence chatboxes into the healthcare industry. Healthcare providers must ensure that chatbots are regularly updated and maintained for accuracy and reliability.

How to Decide Which Features Are Crucial In Your MVP App

New technologies may form new gatekeepers of access to specialty care or entirely usurp human doctors in many patient cases. Further research and interdisciplinary collaboration could advance this technology to dramatically improve the quality of care for patients, rebalance the workload for clinicians, and revolutionize the practice of medicine. Although, if you’re looking for a basic chatbot assisting your website visitors, we advise you to take a look at some existing solutions like Smith.ai, Acobot, or Botsify. Another point to consider is whether your medical AI chatbot will be integrated with existing software systems and applications like EHR, telemedicine platforms, etc.

For example, many patients now require extended at-home support and monitoring, whereas health care workers deal with an increased workload. Although clinicians’ knowledge base in the use of scientific evidence to guide decision-making has expanded, there are still many other facets to the quality of care that has yet to catch up. Key areas of focus are safety, effectiveness, timeliness, efficiency, equitability, and patient-centered care [20]. GYANT, HealthTap, Babylon Health, and several other medical chatbots use a hybrid chatbot model that provides an interface for patients to speak with real doctors. The app users may engage in a live video or text consultation on the platform, bypassing hospital visits. In emergency situations, bots will immediately advise the user to see a healthcare professional for treatment.

What are medical chatbots?

Textbox 1 describes some examples of the recommended apps for each type of chatbot but are not limited to the ones specified. Recently, Google Cloud launched an AI chatbot called Rapid Response Virtual Agent Program to provide information to users and answer their questions about coronavirus symptoms. Google has also expanded this opportunity for tech companies to allow them to use its open-source framework to develop AI chatbots.

Given that the introduction of chatbots to cancer care is relatively recent, rigorous evidence-based research is lacking. Standardized indicators of success between users and chatbots need to be implemented by regulatory agencies before adoption. Once the primary purpose is defined, common quality indicators to consider are the success rate of a given action, nonresponse rate, comprehension quality, response accuracy, retention or adoption rates, engagement, and satisfaction level. The ultimate goal is to assess whether chatbots positively affect and address the 3 aims of health care. Regular quality checks are especially critical for chatbots acting as decision aids because they can have a major impact on patients’ health outcomes.

These chatbots are variously called dialog agents, conversational agents, interactive agents, virtual agents, virtual humans or virtual assistants (Abd-Alrazaq et al. 2020; Palanica et al. 2019). For instance, in the case of a digital health tool called Buoy or the chatbot platform Omaolo, users enter their symptoms and receive recommendations for care options. Both chatbots have algorithms that calculate input data and become increasingly smarter when people use the respective platforms. The increasing use of bots in health care—and AI in general—can be attributed to, for example, advances in machine learning (ML) and increases in text-based interaction (e.g. messaging, social media, etc.) (Nordheim et al. 2019, p. 5). Chatbots are based on combining algorithms and data through the use of ML techniques.

• Relevant apps on the iOS Apple store were identified; then, the Google Play store was searched with the exclusion of any apps that were also available on iOS, to eliminate duplicates.
• To limit face-to-face meetings in health care during the pandemic, chatbots have being used as a conversational interface to answer questions, recommend care options, check symptoms and complete tasks such as booking appointments.
• First, it can perform an assessment of a health problem or symptoms and, second, more general assessments of health and well-being.
• This increased efficiency can result in better patient outcomes and a higher quality of care.
• The effects that digitalizing healthcare can have on medical practice are especially concerning, especially on clinical decision-making in complex situations that have moral overtones.
• With the eHealth chatbot, users submit their symptoms, and the app runs them against a database of thousands of conditions that fit the mold.

Creating chatbots with prespecified answers is simple; however, the problem becomes more complex when answers are open. Bella, one of the most advanced text-based chatbots on the market advertised as a coach for adults, gets stuck when responses are not prompted [51]. Given all the uncertainties, chatbots hold potential for those looking to quit smoking, as they prove to be more acceptable for users when dealing with stigmatized health issues compared with general practitioners [7]. Early cancer detection can lead to higher survival rates and improved quality of life.

Smoothing insurance issues

Our review of healthbots aims to classify types of healthbots, contexts of use, and their natural language processing capabilities. Eligible apps were those that were health-related, had an embedded text-based conversational agent, available in English, and were available for free download through the Google Play or Apple iOS store. Apps were assessed using an evaluation framework addressing chatbot characteristics and natural language processing features. Most healthbots are patient-facing, available on a mobile interface and provide a range of functions including health education and counselling support, assessment of symptoms, and assistance with tasks such as scheduling. Most of the 78 apps reviewed focus on primary care and mental health, only 6 (7.59%) had a theoretical underpinning, and 10 (12.35%) complied with health information privacy regulations.

After learning the exercises yourself through repetition, you won’t need a bot to help you stay positive. What started as a personal project grew into an advanced personal nurse chatbot named off of the founder of modern nursing, Florence Nightingale. Iona Mind, designed for an iPad and iPhone, acts as a guide for “fitness of the mind”. It’s a self help app and isn’t designed for the treatment of psychiatric disorders.

How to Develop a Medical Chatbot App?

They could also be thought of as decision aids that deliver regular feedback on disease progression and treatment reactions to help clinicians better understand individual conditions. Preventative measures of cancer have become a priority worldwide, as early detection and treatment alone have not been effective in eliminating this disease [22]. Physical, psychological, and behavioral improvements of underserved or vulnerable populations may even be possible through chatbots, as they are so readily accessible through common messaging platforms. Health promotion use, such as lifestyle coaching, healthy eating, and smoking cessation, has been one of the most common chatbots according to our search. In addition, chatbots could help save a significant amount of health care costs and resources.

In addition to the content, some apps allowed for customization of the user interface by allowing the user to pick their preferred background color and image. There were 47 (31%) apps that were developed for a primary care domain area and 22 (14%) for a mental health domain. Involvement in the primary care domain chatbots in healthcare industry was defined as healthbots containing symptom assessment, primary prevention, and other health-promoting measures. Additionally, focus areas including anesthesiology, cancer, cardiology, dermatology, endocrinology, genetics, medical claims, neurology, nutrition, pathology, and sexual health were assessed.

Healthcare professionals and new decision-making conditions

Chatbots used for psychological support hold great potential, as individuals are more comfortable disclosing personal information when no judgments are formed, even if users could still discriminate their responses from that of humans [82,85]. Chatbots have the potential to address many of the current concerns regarding cancer care mentioned above. This includes the triple aim of health care that encompasses improving the experience of care, improving the health of populations, and reducing per capita costs [21]. Chatbots can improve the quality or experience of care by providing efficient, equitable, and personalized medical services. We can think of them as intermediaries between physicians for facilitating the history taking of sensitive and intimate information before consultations.