Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review

Healthcare Chatbots and the Future of Chatbot Technology in Healthcare

chatbot technology in healthcare

Thus, their function is to solve complex problems using reasoning methods such as the if-then-else format. In the early days, the problem of these systems was ‘the complexity of mapping out the data in’ the system (Fischer and Lam 2016, p. 23). Today, advanced AI technologies and various kinds of platforms that house big data (e.g. blockchains) are able to map out and compute in real time most complex data structures. In addition, especially in health care, these systems have been based on theoretical and practical models and methods developed in the field. For example, in the field of psychology, so-called ‘script theory’ provided a formal framework for knowledge (Fischer and Lam 2016). Thus, as a formal model that was already in use, it was relatively easy to turn it into algorithmic form.

chatbot technology in healthcare

Over time, they gain acceptance and transform the industry or market they are a part of (Kostoff et al., 2004). A prime example is the digital camera, which eliminated chatbot technology in healthcare the need for film and traditional film processing. However, digital cameras disrupted this market by offering a more convenient and cost-effective alternative.

Challenges that Virtual Assistants can Solve for Better Healthcare

It connects your entire tech stack to answer questions, automate repetitive support tasks, and build solutions to any business challenge. Chatbots are a cost-effective alternative to hiring additional healthcare professionals, reducing costs. By automating routine tasks, AI bots can free up resources to be used in other areas of healthcare. A New York-based hospital chain, Northwell Health, launched a chatbot to curb its 40% colonoscopy no-show rate for follow-up appointments.

chatbot technology in healthcare

Four apps utilized AI generation, indicating that the user could write two to three sentences to the healthbot and receive a potentially relevant response. Most would assume that survivors of cancer would be more inclined to practice health protection behaviors with extra guidance from health professionals; however, the results have been surprising. Smoking accounts for at least 30% of all cancer deaths; however, up to 50% of survivors continue to smoke [88]. The cognitive behavioral therapy–based chatbot SMAG, supporting users over the Facebook social network, resulted in a 10% higher cessation rate compared with control groups [50]. Motivational interview–based chatbots have been proposed with promising results, where a significant number of patients showed an increase in their confidence and readiness to quit smoking after 1 week [92]. No studies have been found to assess the effectiveness of chatbots for smoking cessation in terms of ethnic, racial, geographic, or socioeconomic status differences.

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Such agencies know the latest and trending tech stack and implement them to create high-end solutions. has become so advanced that gone are the days when chatbots used to develop through logic. With the introduction of Natural Language Processing (NPL) and Machine Learning (ML) algorithms, creating a chatbot that learns human intent and language is much easier.

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The best part about scheduling appointments via chatbot is that the staff won’t get overwhelmed when inquiries become high. Organizations should include chatbot services in their insurance plans for employees to prevent reimbursements for unwanted doctor visits. Molly, a virtual nurse bot, assists patients in maintaining treatment plans and records. The everyday data and vital parameters of the patients are also stored, and the physician is notified if there are any health-related risks to the patient.

Top 5 Use Cases of Chatbots in Healthcare

They’re never tired, always ready to ease the burden on clinicians and improve the quality of care for patients. There are many more reasons for a medical business to develop a healthcare chatbot app, and you’ll find most of them in this article. The chatbots store the patient’s information, medical condition, and treatment record for future reference and ease the work of the physicians. Also, the chatbots help book doctor appointments for patients, saving a lot of time and energy.

chatbot technology in healthcare

The healthbots serve a range of functions including the provision of health education, assessment of symptoms, and assistance with tasks such as scheduling. Currently, most bots available on app stores are patient-facing and focus on the areas of primary care and mental health. Only six (8%) of apps included in the review had a theoretical/therapeutic underpinning for their approach. Two-thirds of the apps contained features to personalize the app content to each user based on data collected from them. Seventy-nine percent apps did not have any of the security features assessed and only 10 apps reported HIPAA compliance. The reduction in customer service costs and the ability to handle many users at a time are some of the reasons why chatbots have become so popular in business groups [20].

ChatGPT is also a disruptive technology with the potential to fundamentally change how we interact with technology and perhaps to revolutionize the way medical professionals engage with patients. While ChatGPT has the potential, as a disruptive technology, to improve access to healthcare services, there are also concerns relating to its use as a medical chatbot. One concern is the accuracy and reliability of the medical information provided by ChatGPT, as it is not a licensed medical professional and may not have access to up-to-date medical knowledge. Additionally, there are concerns about the transparency of the chatbot model and the ethics of making use of user information, as well as the potential for biases in the data used to train ChatGPT’s algorithms. As such, it is important to carefully consider the potential risks and benefits of using ChatGPT as a medical chatbot, and to ensure that appropriate safeguards are put in place to address these concerns.

Hiring and onboarding new employees can be cumbersome and time-consuming, especially in a large healthcare company. That’s why they implement AI chatbots to make the job of the HR department easy. In this ultimate guide, we will discuss everything you need to know before implementing As the demand for healthcare workers is higher, the firms onboard many candidates for different roles. This is a tiring job for the HR department, and they will not be able to focus on other employee-related strategies. To increase the efficiency of HR, the chatbots can perform the paper works for the new hires and get the work done from them too.

Conversely, closed-source tools are third-party frameworks that provide custom-built models through which you run your data files. With these third-party tools, you have little control over the software design and how your data files are processed; thus, you have little control over the confidential and potentially sensitive data your model receives. Forksy is the go-to digital nutritionist that helps you track your eating habits by giving recommendations about diet and caloric intake. This chatbot tracks your diet and provides automated feedback to improve your diet choices; plus, it offers useful information about every food you eat – including the number of calories it contains, and its benefits and risks to health. Informative chatbots provide helpful information for users, often in the form of pop-ups, notifications, and breaking stories. Use case for chatbots in oncology, with examples of current specific applications or proposed designs.

chatbot technology in healthcare

While there are many lists of applications, all with their own top 5 or 10 chatbot solutions, it’s worth looking at what meets the needs of a particular industry or company. In terms of healthcare, there are just a handful of simple requirements that are vital to the successful rollout and adoption of such technology. Chatbots can be accessed anytime, providing patients support outside regular office hours. This can be particularly useful for patients requiring urgent medical attention or having questions outside regular office hours. The possibilities are endless, and as technology continues to evolve, we can expect to see more innovative uses of bots in the healthcare industry.

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In these ethical discussions, technology use is frequently ignored, technically automated mechanical functions are prioritised over human initiatives, or tools are treated as neutral partners in facilitating human cognitive efforts. So far, there has been scant discussion on how digitalisation, including chatbots, transform medical practices, especially in the context of human capabilities in exercising practical wisdom (Bontemps-Hommen et al. 2019). 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.

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In practice, however, clinicians make diagnoses in a more complex manner, which they are rarely able to analyse logically (Banerjee et al. 2009). Unlike artificial systems, experienced doctors recognise the fact that diagnoses and prognoses are always marked by varying degrees of uncertainty. They are aware that some diagnoses may turn out to be wrong or that some of their treatments may not lead to the cures expected. Thus, medical diagnosis and decision-making require ‘prudence’, that is, ‘a mode of reasoning about contingent matters in order to select the best course of action’ (Hariman 2003, p. 5). The development—especially conceptual in nature—of ADM has one of its key moments in the aftermath of World War II, that is, the era of the Cold War. America and the Soviets were both keen (in their own ways) on find ways to automatise and streamline their societies (including decision-making).

  • Similar to other technologies, a healthcare chatbot comes with a few disadvantages and shortcomings.
  • However, a biased view of gender is revealed, as most of the chatbots perform tasks that echo historically feminine roles and articulate these features with stereotypical behaviors.
  • In the aftermath of COVID-19, Omaolo was updated to include ‘Coronavirus symptoms checker’, a service that ‘gives guidance regarding exposure to and symptoms of COVID-19’ (Atique et al. 2020, p. 2464; Tiirinki et al. 2020).

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.

chatbot technology in healthcare

As a result of patient self-diagnoses, physicians may have difficulty convincing patients of their potential preliminary misjudgement. This persuasion and negotiation may increase the workload of professionals and create new tensions between patients and physicians. Healthcare professionals can’t reach and screen everyone who may have symptoms of the infection; therefore, leveraging AI bots could make the screening process fast and efficient. The Indian government also launched a WhatsApp-based interactive chatbot called MyGov Corona Helpdesk that provides verified information and news about the pandemic to users in India. At Topflight, we’ve been lucky to have worked on several exciting chatbot projects.






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