Chatbot breakthrough in the 2020s? An ethical reflection on the trend of automated consultations in health care PMC

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. In addition, health chatbots have been deemed promising in terms of consulting patients in need of psychotherapy once COVID-19-related physical distancing measures have been lifted. Many experts have emphasised that chatbots are not sufficiently mature to be able to technically diagnose patient conditions or replace the judgements of health professionals. In this paper, we take a proactive approach and consider how the emergence of task-oriented chatbots as partially automated consulting systems can influence clinical practices and expert–client relationships. We suggest the need for new approaches in professional ethics as the large-scale deployment of artificial intelligence may revolutionise professional decision-making and client–expert interaction in healthcare organisations.

The integration of this application would improve patients’ quality of life and relieve the burden on health care providers through better disease management, reducing the cost of visits and allowing timely follow-ups. In terms of cancer therapy, remote monitoring can support patients by enabling higher dose chemotherapy drug delivery, reducing secondary hospitalizations, and providing health benefits after surgery [73-75]. Medical chatbots are AI-powered conversational solutions that help patients, insurance companies, and healthcare providers easily connect with each other. These bots can also play a critical role in making relevant healthcare information accessible to the right stakeholders, at the right time. Most risk assessment and disease surveillance chatbots did not follow-up on symptomatic users. Privacy concerns and regulations may have precluded this since following up requires that chatbots capture identifying information.

Medical Diagnosis And Symptom Assessment

One of the first healthcare chatbot companies we wanted to talk about is Google’s Med-PaLM 2. As a state-of-the-art healthcare chatbot, this technology is the predecessor to Med-PaLM, which only scored 67.5% on the US medical exam. With the creation of ChatGPT and other such chatbots, it’s interesting to see the impact of AI on healthcare as a whole.

Nevertheless, chatbots are emerging as a solution for healthy lifestyle promotion through access and human-like communication while maintaining anonymity. This is partly because Generative Conversational AI is still evolving and has a long way to go. As natural language understanding and artificial intelligence technologies evolve, we will see the emergence of more sophisticated healthcare chatbot solutions. The development of multiple such use cases, including surveillance and logistics, would be especially beneficial as a frugal solution to bridge the digital divide in areas of poor infrastructure. As conversational AI continues advancing, measurable benefits like these will accelerate chatbot adoption exponentially.

Recommended health care components for the different types of chatbots.

We argue that the implementation of chatbots amplifies the project of rationality and automation in clinical practice and alters traditional decision-making practices based on epistemic probability and prudence. This article contributes to the discussion on the ethical challenges posed by chatbots from the perspective of healthcare professional ethics. A healthcare chatbot is a sophisticated blend of artificial intelligence and healthcare expertise designed to transform patient care and administrative tasks. At its core, chatbot healthcare use cases a healthcare chatbot is an AI-powered software application that interacts with users in real-time, either through text or voice communication. By employing advanced machine learning algorithms and natural language processing (NLP) capabilities, these chatbots can understand, process, and respond to patient inquiries with remarkable accuracy and efficiency. Healthcare chatbots, equipped with AI, Neuro-synthetic AI, and natural language processing (NLP), are revolutionizing patient care and administrative efficiency.

By ensuring that patients attend their appointments and adhere to their treatment plans, these reminders help enhance the effectiveness of healthcare. Patients can easily book, reschedule, or cancel appointments through a simple, conversational interface. This convenience reduces the administrative load on healthcare staff and minimizes the likelihood of missed appointments, enhancing the efficiency of healthcare delivery.

The focus will be on cancer therapy, with in-depth discussions and examples of diagnosis, treatment, monitoring, patient support, workflow efficiency, and health promotion. In addition, this paper will explore the limitations and areas of concern, highlighting ethical, moral, security, technical, and regulatory standards and evaluation issues to explain the hesitancy in implementation. The final use case, proactive monitoring (3 cases), involves proactively monitoring at-risk populations, such as the elderly,28–31 by checking whether users are experiencing symptoms or have been exposed to the virus.

• Key areas of focus are safety, effectiveness, timeliness, efficiency, equitability, and patient-centered care [20].
• The web-based chatbot ItRuns (ItRunsInMyFamily) gathers family history information at the population level to determine the risk of hereditary cancer [29].
• Chatbots can also be integrated into user’s device calendars to send reminders and updates about medical appointments.
• Now you’re curious about them and the question “what are chatbots used for, anyway?
• 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].

Implementation of chatbots may address some of these concerns, such as reducing the burden on the health care system and supporting independent living. Chatbots have been implemented in remote patient monitoring for postoperative care and follow-ups. The health care sector is among the most overwhelmed by those needing continued support outside hospital settings, as most patients newly diagnosed with cancer are aged ≥65 years [72].

In this respect, chatbots may be best suited as supplements to be used alongside existing medical practice rather than as replacements [21,33]. Surprisingly, there is no obvious correlation between application domains, chatbot purpose, and mode of communication (see Multimedia Appendix 2 [6,8,9,16-18,20-45]). Some studies did indicate that the use of natural language was not a necessity for a positive conversational user experience, especially for symptom-checking agents that are deployed to automate form filling [8,46]. In another study, however, not being able to converse naturally was seen as a negative aspect of interacting with a chatbot [20].

They simulate human activities, helping people search for information and perform actions, which many healthcare organizations find useful. While there are many other chatbot use cases in healthcare, these are some of the top ones that today’s hospitals and clinics are using to balance automation along with human support. As the chatbot technology in healthcare continuously evolves, it is visible how it is reducing the burden of the already overburdened hospital workforce and improving the scalability of patient communication. Once you integrate the chatbot with the hospital systems, your bot can show the expertise available, and the doctors available under that expertise in the form of a carousel to book appointments.

Other applications in pandemic support, global health, and education are yet to be fully explored. At the onset of the pandemic little was known about Covid-19 and information and guidelines were in constant flux. The public had many questions and concerns regarding the virus which overwhelmed health providers and helplines. We were able to assess the type of information provided for 37 of the 42 information dissemination chatbots (see Table 2 in Appendix 1). Based on the information they provided, we identified 7 use cases for information dissemination (see Figure 2). While many chatbots leverage risk-assessment criteria from official sources (WHO, CDC, or other government health agency), the questions asked vary significantly across chatbots, and as does the order in which they are asked.

Woebot is transparent about how it cannot replace an appointment with a real human being, but it offers a listening ear and advice, often giving users further information and resources on techniques to better manage their emotions over time. Chatbots and conversational AI have been widely implemented in the mental health field as a cheaper and more accessible option for healthcare consumers. The QliqSOFT chatbot provides patients with care information and guidelines for recovery, allowing them to access information and ask questions at any time. Tars offers clinics and diagnostic centers a smoother alternative to the traditional contact form, collecting patient information for healthcare facilities through their chatbots. Since a chatbot is available at all hours, users are able to access medical services or information when it’s most convenient for them, reducing the burden on staff. Most chatbots were text-based (42 cases), 4 were voice-based, and 4 had both text and voice options.