Elder Care, Medical Consultation, and Mental Health: How Chatbots Are Shaping the Future of Healthcare

（This article is based on VCBeat’s special feature Pro “Elderly Care, Consultations, Psychological Counseling... Chatting with Chatbots About the Future of Healthcare》Compiled and generated; cases in the text have been slightly abridged.）

A recent research paper published in JMIR surveyed 100 licensed physicians in the United States regarding their perceptions of healthcare chatbots, covering the value, challenges, and risks associated with their application in doctor-patient interactions. The survey revealed that among physicians who had used chatbots, 13% reported being very satisfied, 33% were relatively satisfied, 27% were neutral, and 27% were dissatisfied.

Notably, the survey reveals that physicians have a considerable level of acceptance for chatbots in logistical processes. In clinical care, applications such as helping patients better manage their health, providing more personalized treatment plans, and reducing unnecessary consultations have been well received by the medical community.

Overall, positive feedback far outweighs negative.

In fact, since the rise of chatbots, attempts have been made to apply them across various fields, with waves of both acclaim and skepticism never ceasing. Particularly in 2018, this technology faced widespread skepticism within the tech industry. However, while chatbots cooled off in the broad consumer-to-consumer (To C) market, they have found new vitality in the technological healthcare sector: health management, online consultations, AI-driven healthcare... From elderly care to psychological counseling, the upgraded applications of chatbots are ubiquitous. Against the backdrop of technological advancements and remote medicine becoming a major future trend, chatbots still hold considerable potential.

Chatbots Enter the Healthcare Sector

Chatbots, also known as bots, refer to conversational agents. It is important to note that these chatbots are not physical robots; rather, they represent a service model based on conversational interfaces (which can be text-based or voice-based) designed to address user needs through dialogue, similar to virtual assistants.

In recent years, as mobile communications began to surpass mobile social networking, and with the rise of artificial intelligence and big data, chatbots have come to be seen as a significant opportunity—one that could replace the app model and transform the internet’s existing business models.

Currently, there are three operational modes for chatbots:

The first type is rule-based response. Rule-based response means that users must formulate their queries according to predefined rules, and the chatbot will only respond if the input matches pre-stored phrases. This approach is relatively limited and therefore represents the most basic level.

The second type is a machine learning-based chatbot. On one hand, the system can accurately recognize non-standard language inputs from users; on the other hand, it employs specific logical algorithms to ensure that each response provided by the bot meets user needs to the highest possible standard.

The third model is the remote human-assisted mode. After users submit their information, it is transmitted directly to the backend system, which then forwards the data to the appropriate specialists for consultation. The specialists’ responses are delivered to the user’s chat interface in either text or video format.

This model is primarily applied in complex domains such as healthcare. While it ensures the accuracy of responses, it results in slower response times.

Furthermore, it is important to note that although this model does not employ intelligent response technology, it is inherently designed to address user needs through a chat-based interface; therefore, by definition, it also qualifies as a chatbot.

In China, WeChat and Weibo are platforms that support chatbots. Abroad, platforms such as Facebook Messenger, Slack, and Telegram are more prevalent. Statistics show that the most widely used platforms for chatbots both domestically and internationally are SMS, Slack, and various apps, accounting for 52%, 46%, and 35%, respectively. Notably, the adoption rate of chatbots on Weibo reaches 27%, significantly higher than Twitter’s 5% and WeChat’s 2%.

Furthermore, chatbots are already partially applied in the medical and health sector, with the most extensive adoption occurring at the corporate level, where enterprises leverage chatbots to enhance business synergy.

The Extent of Chatbot Adoption Across Major Social Media Platforms

Chatbot Implementation Cases

Currently, typical real-world applications of chatbots can be broadly categorized into three areas: disease management, behavioral health, and mental health. Given the need for effective deployment of chatbots in the healthcare sector, these implemented solutions primarily rely on machine learning-based chatbots and remote human-assisted models.

Disease-specific chatbots have a higher barrier to entry compared to other types, but since they do not deviate from the core attributes of chatbots, their requirements for artificial intelligence technology are relatively modest.

Moreover, while the upgraded interface experience of chatbots may not appear highly intelligent compared to apps, it aligns with customers’ demand for ultimate convenience. Therefore, a well-designed chatbot has the potential to deliver a more user-friendly experience than an app.

Your.MD is the first company to apply artificial intelligence to the field of health assistance, and its chatbot is currently available on multiple platforms. Its operational model is primarily based on machine learning, helping patients identify their symptoms in a manner akin to preliminary diagnosis. According to its official website, the company maintains a pre-diagnostic database covering more than 1,100 diseases.

The workflow of the Your.MD online platform consists of three steps: first, inquiring about the patient’s symptoms; second, providing options and categorizing the patient’s symptoms through complex logistic regression; and third, delivering a diagnostic result. As the system typically asks about symptoms more than five times, it achieves a high level of accuracy.

HealthTap is a renowned telemedicine company based in California, USA. Not long ago, the company launched a chatbot on the Facebook Messenger platform, which operates through a combination of machine learning and remote human assistance. Unlike Your.MD, HealthTap automatically searches its own case database for similar cases upon receiving an inquiry.

Notably, HealthTap’s responses not only provide diagnostic assessments of symptoms but also guide patients on treatment options. If no relevant records are found in HealthTap’s case database, the platform automatically switches from its machine-learning mode to a remote human-assisted mode, routing the patient’s inquiry to all physicians on the platform and ensuring a response within 24 hours.

HealthTap’s model enables better reuse of historical physician Q&A data, thereby reducing the waste of medical resources to a certain extent and helping to lower costs.

It is worth noting that while Your.MD and HealthTap offer very similar functionalities, an examination of their development histories reveals differences in their strategic focus and initial expectations for chatbot technology, although they appear to have ultimately converged in their outcomes. HealthTap can be classified as a healthcare service company, as it provides direct access to online consultations with remote physicians. In contrast, Your.MD does not deliver medical services directly but instead offers triage and referral services through an open marketplace. Various medical clinics can apply to partner with Your.MD and join its Onestop Health ecosystem, thereby gaining access to patient traffic. This may well be a key reason why Your.MD enjoys greater recognition among physicians.

Renowned UK-based AI-powered triage startup Babylon Health has recently been reported to be set for an investment from an Arab sovereign wealth fund, with this funding round valuing the company at over $1 billion. The exact amount of financing has not been disclosed but is rumored to be between $100 million and $500 million.

Babylon Health is arguably the most prominent startup leveraging AI technology to provide medical symptom consultation services via chatbots. Founded in 2013, the company completed its latest funding round in 2017. The UK’s National Health Service (NHS) has established an in-depth partnership with Babylon Health, aiming to extensively integrate its remote services into the primary care system.

It is worth noting that while Your.MD, Babylon, and HealthTap offer very similar functionalities, an examination of their development histories reveals differences in their initial focus and expectations for chatbot technology, although they appear to have ultimately converged toward similar outcomes. HealthTap and Babylon provide direct access to online remote physician consultations, qualifying them as healthcare service providers. In contrast, Your.MD does not directly deliver medical services but offers triage guidance; it operates as an open marketplace where various medical clinics can apply for partnership and join its Onestop Health ecosystem to gain patient traffic. This may well be a key reason why Your.MD enjoys greater recognition among physicians.

"Cancer Chatbot" is actually a public welfare application spontaneously created by a cancer patient, primarily designed to provide reliable information and supportive assistance from the perspective of cancer patients, especially those who have just been diagnosed.

The Cancer Chatbot does not feature advanced AI capabilities for intelligent diagnostic symptom queries; instead, it provides patients with access to reliable information and connections to trustworthy organizations, serving even as a navigator for credible health resources. Furthermore, it offers emotional support and reassurance to patients. For those facing a prolonged battle against cancer, this application can serve as a long-term companion.

Currently, most chatbots applied in the behavioral health field are of the low-barrier types, such as those focused on weight loss and healthy eating. Meanwhile, health management areas like obesity and diet control are also hotspots attracting significant capital investment. Coupled with users’ strong demand for simplicity, directness, and speed, these chatbots are well-suited to serve as entry points for accessing specific services.

Meanwhile, a chatbot with platform-aggregating capabilities can also serve as a new traffic gateway. Naturally, the tech giants that already dominate existing traffic gateways will spare no effort to further expand their territories, which is a key reason why companies like Google, Apple, and Facebook are heavily investing in chatbots.

Forsky is a chatbot in the field of healthy eating, dedicated to helping users change unhealthy dietary habits. Its operational model incorporates artificial intelligence and is highly engaging. When users report their food intake to Forsky, it evaluates whether the food is healthy. If deemed unhealthy, Forsky provides feedback that is humorous yet brutally honest. Moreover, Forsky invites users’ friends to comment on their food choices and share feedback. Unlike other closed-system chatbots, Forsky integrates social interaction, making it innovative.

Workout Bot is a chatbot designed for exercise. When users ask it how to work out, the product provides some exercise items. All questions are presented in the form of options, and its working mode belongs to the basic rule-based response model. Therefore, it is relatively simple, and this chatbot can only respond to requests without being able to analyze the user's exercise status.

Gymbot is also a fitness-oriented chatbot. However, compared to Workout Bot, Gymbot not only provides exercise recommendations but also logs workout sessions (with a streamlined logging process, similar to selecting options via sliding), tracks fitness progress, and ultimately delivers data-driven insights.

In recent years, psychological counseling combined with digital health has emerged as a new direction in the development of psychotherapy, with chatbots serving as one of the typical application platforms.

Typically, the public’s perception of chatbots is limited to a passive model where users pose questions and the bot merely responds. In reality, however, chatbots can also proactively ask follow-up questions based on context. This more proactive approach better engages users and enhances user stickiness. Compared with conventional web-based interfaces, chatbots offer significantly stronger interactivity.

Joy is the first chatbot designed to address users’ emotional and psychological concerns, currently available exclusively on the Facebook Messenger platform. Powered by artificial intelligence, Joy not only provides coping strategies for negative emotions but also tracks users’ mood patterns. At regular intervals, Joy checks in with users to assess and record their emotional state, offering timely support and recommendations when low moods are detected.

UpLift Health, a digital health company based in Atlanta that specializes in treating depression, recently secured $1 million in seed funding. UpLift Health employs cognitive behavioral therapy (CBT) to assist patients with depression. The platform offers 12 chatbot-guided sessions, each lasting 45 minutes, along with a toolkit. According to the company’s website, users can engage by answering questions, completing mental training exercises, and receiving feedback and guidance from the chatbot. The company charges its users a monthly subscription fee of $29.99 or a quarterly subscription fee of $14.99 per month.

With Woebot, a well-backed pioneer, leading the way, digital therapeutics for depression have gained considerable recognition in European and American markets, yet digital innovations in mental health have seen lackluster performance in the Chinese market.

KokoBot not only leverages artificial intelligence but also harnesses collective intelligence. As a result, this chatbot stands out for its high level of interactivity: users receive guidance from KokoBot itself, while their questions are also answered through peer-to-peer mutual assistance. This approach significantly enhances the scalability and engagement of the responses, and reinforces cognitive therapy through collaborative support.

Chatbot Application Prospects

In the past few years, a large number of apps have flooded into the internet healthcare sector (with over 30% of these healthcare apps incorporating medical robots), while the vast majority of startup teams are still searching for more mature and sustainable business models.

How Can Chatbots Be Beneficial? In most application scenarios, chatbots that prioritize interface optimization as their core value are unlikely to serve as a lifeline; they can only add icing on the cake. However, in more specialized fields such as elderly care, medical science popularization, consultation, online encyclopedias, tiered diagnosis and treatment, and healthcare customer service, interface upgrades can align with key value propositions.

Older adults have low acceptance of traditional app models, as many struggle to adapt to conventional human-computer interaction interfaces. In contrast, chatbot interfaces are more readily accepted by the elderly. Therefore, chatbot platforms can, to some extent, serve as life assistants for handling emergencies while also providing companionship.

There are already notable cases of chatbot applications in elderly care.

Best Buy will leverage CST’s remote monitoring platform to drive the growth of its home care business. As the largest personal emergency response system (PERS) and remote monitoring service provider in the United States, CST serves over 100,000 elderly individuals. In China, Hangzhou Shengying Zhicheng Robotics Technology Co., Ltd. has launched a cognitive intelligent robot, marking the successful development of the first emotional companion robot for elderly care.

Hangzhou Shengying Zhicheng Robotics Technology Co., Ltd. was registered in June 2019 in the Hangzhou Binjiang High-Tech Industrial Development Zone, focusing on technological research and development in fields such as intelligent caregiving robots. The company has successfully developed its first emotional companion robot for elderly care. Founder Wang Yongan has been recognized as a Leading Talent for Entrepreneurship and Innovation under the Binjiang District Government’s “5050 Plan” and has obtained the qualification for Introducing Overseas High-End Talents from the Zhejiang Provincial Administration of Foreign Experts Affairs. Currently, the company has filed invention patent applications for robotics technologies (patent titles: “A Human-Robot Interaction Robot and Its Control Method,” and “A Sensor for Human-Robot Emotional Interaction”).

At present, it appears more advantageous for chatbots to advance through a B2B2C business model.

Driven by the overarching policy of tiered diagnosis and treatment, products that can efficiently allocate medical resources, save energy for medical staff, and reduce operational costs for healthcare departments will gain a certain level of acceptance. Moreover, the chatbot interface model can better realize pre-diagnosis, triage, and patient guidance.

In the past, many internet healthcare startups have deeply cultivated this field, resulting in fierce competition. Merely improving, optimizing, or entering the market with a chatbot-based model cannot alter the competitive landscape or resolve the fundamental challenges; ultimately, success still depends on multi-dimensional competition.

According to Yang Wengang, Founder and CEO of Mei Daifu, the functions of existing medical aesthetics platforms on the market are mainly reflected in “product seeding” and reducing decision-making costs. However, the needs of doctors for patient-physician connection and personal brand building, as well as patients’ demands for finding suitable doctors, online consultations, and post-diagnosis follow-up, remain unmet.

Therefore, Mei Daifu has established a new business model, positioning itself as the “Haodf.com of the medical aesthetics industry.” This model integrates an online platform with offline shared surgical centers to provide patients with online consultations, appointment scheduling, follow-up care, and in-person diagnosis and treatment. For physicians, it offers a personal branding platform featuring comprehensive professional backgrounds, authentic user reviews, and ranking and recommendation systems based on these reviews, along with facilities for multi-site practice. Specifically, physicians can use the Mei Daifu Workstation to conduct preliminary online consultations, manage electronic health records in the cloud, and collaborate with their teams. They can rent office space within the shared surgical centers for final consultations, preoperative discussions, and assistant workspaces, and perform surgeries there, thereby building their personal brand and increasing income. Consumers can find their preferred physicians online, complete consultations, establish health records, and schedule appointments, followed by in-person preoperative discussions and treatments at the offline facilities.

In the medical aesthetics industry, the revenue-sharing model based on transactions has been thoroughly established in the market. Moreover, since the “mainstream players” in this sector are market-driven institutions—distinct from public hospitals that provide disease-oriented medical care—the commercialization process is advancing more rapidly than that of typical internet healthcare platforms.

Shriners Hospitals for Children has partnered with Boys Town National Research Hospital to provide telehealth consultations to patients located several hours away from Shriners facilities. Notably, Boys Town will serve as Shriners’ first telemedicine site within its service area. Shriners patients will be able to visit Boys Town for certain routine examinations, during which Boys Town clinicians will establish a remote connection with Shriners specialists to conduct patient assessments. During these appointments, Shriners clinicians will be able to virtually evaluate wound healing, monitor joint mobility, and assess other functional capabilities.

MSK Announces Partnership with California-Based More Health to Expand Expert Consultation Services to China via MORE’s “Co-Diagnosis” Connected Care Platform. This telemedicine collaboration will help broaden Chinese cancer patients’ access to MSK’s expertise and provide a platform for communication between MSK and Chinese physicians, thereby improving the standard of cancer care in China.

Deploying chatbots to partially replace human agents in customer service is a technology already adopted across many industries. Healthcare institutions also have significant customer service needs, similar to those of customer centers in other sectors. However, this application has limited intrinsic connection to medical care itself and represents a typical B2B business model.

Duomei Vision has launched a new product for healthcare service enterprises—the Xiaoyi Medical Robot Customer Service System—completing its transformation from consumer-facing (C-end) services to business-facing (B-end) services. Yu Guo, CEO of Duomei Vision, stated that the Xiaoyi Medical Robot is positioned as a medical consultation robot. Leveraging “strong technology and long-term R&D accumulation,” it can help enterprises reduce costs by 90%. The system serves not only consumers in sub-health conditions and patients but also a large number of B-end healthcare service institutions.

U.S. startup Replicant recently secured $7 million in funding to develop AI-powered intelligent voice customer service bots. The intelligent customer service sector is one of the areas where chatbot technologies are most widely applied. It is reported that, compared with typical robotic customer service agents, which often speak more slowly and require users to simplify complex phrases to accommodate machine limitations, Replicant offers a superior conversational experience. Its dialogue technology achieves a level of interaction comparable to that of human agents integrated into client systems. Replicant claims its system can better understand speech, process information faster, and respond rapidly.

Challenges and Risks: It Is Better to Leverage Strengths and Avoid Weaknesses Than to Tackle Hard Problems Head-On

Returning to the survey in the JMIR paper, the study indicates that the questionnaire also assessed the current challenges and risks associated with medical chatbots.

More than half of physicians (53%) agree to some extent with the various challenges associated with the use of healthcare chatbots. Most notably, 76% of physicians believe that chatbots cannot effectively address patients’ comprehensive needs. Regarding risks, the most prominent issues include patients too frequently using chatbots for self-diagnosis (71%), chatbots’ inability to provide specific explanations for patient diagnoses (71%), and patients’ inaccurate understanding of diagnoses (74%). Based on the above feedback, it is evident that the identified risks are primarily concentrated in the area of diagnosis.

Rather than challenges to be addressed, these listed existing deficiencies and risks are realities that should be accepted. Instead of expending considerable effort to overcome them, it is more advisable to adopt a strategy that leverages strengths and mitigates weaknesses, thereby fully realizing the value that can be delivered.

Chatbots demonstrate particular value in enhancing the accessibility and convenience of healthcare services, facilitating the dissemination and acquisition of pharmaceutical knowledge, and improving patient self-management outcomes. However, they are not proficient in diagnosis and treatment planning, which also pose significant risks. In line with the principle of leveraging strengths while mitigating weaknesses, it is essential to further reinforce their advantages. The most viable current path for medical chatbots lies in deepening their capabilities in accessibility, convenience, information dissemination, and patient self-management.

This article is based on VCBeat’s special feature Pro “Elderly Care, Consultations, Psychological Counseling... Chatting with Chatbots About the Future of Healthcare》Compiled and generated; some cases in the text have been slightly abridged. Updates on chatbot developments will continue. To gain a comprehensive understanding of industry trends and access more chatbot case studies, please scan the QR code below to read further.！

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