The Chatbot Revolution: Transforming Healthcare With AI Language Models

Woman uses AI chatbot for mental health support, says it is more convenient than visiting a therapist

chatbot in healthcare

The public’s lack of confidence is not surprising, given the increased frequency and magnitude of high-profile security breaches and inappropriate use of data [95]. Unlike financial data that becomes obsolete after being stolen, medical data are particularly valuable, as they are not perishable. Privacy threats may break the trust that is essential to the therapeutic physician–patient relationship and inhibit open communication of relevant clinical information for proper diagnosis and treatment [96]. AI and ML have advanced at an impressive rate and have revealed the potential of chatbots in health care and clinical settings. AI technology outperforms humans in terms of image recognition, risk stratification, improved processing, and 24/7 assistance with data and analysis.

chatbot in healthcare

NEW YORK — Komal Vilas Thatkare says she doesn’t have anyone to ask about her most private health questions. With each answer you give the chatbot, it eliminates a couple of diagnosis options until it finally lands on the most likely ones. Afterward, the chatbot helps you decide on the next steps and choose the best follow-up variant that suits you the best, both in terms of money and convenience. On paper, the company is claiming that it provides a greater level of accuracy in its recommendations, but government bodies are worried about the narrative they are perpetuating. For companies like QliqSOFT, which has focused its solutions on enhancing patient engagement and satisfaction, this comes as little surprise. In the first round of testing with GPT-3.5, the researchers tabulated a median accuracy score of 5.0 and a median completeness score of 3.0, meaning on the first try, ChatGPT-3.5 typically answered the questions nearly accurately and comprehensively.

This methodology is a particular concern when chatbots are used at scale or in sensitive situations such as mental health. 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].

Step 9: Instruction and Training for Users

While chatbots can provide personalized support to patients, they cannot replace the human touch. Healthcare providers must ensure that chatbots are used in conjunction with, and not as a replacement for human healthcare professionals. Deep learning capabilities enable AI chatbots to become more accurate over time, which in turn enables humans to interact with AI chatbots in a more natural, free-flowing way without being misunderstood. However, limitations like understanding complex emotions and maintaining user engagement still need to be addressed. Nevertheless, continuous research, ethical considerations, and improvements hold immense potential for chatbots to transform mental healthcare accessibility and effectively support individuals seeking help.

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).

chatbot in healthcare

Although chatbot technology for health care is continually advancing, little is known about the perspectives of practicing medical physicians on the use of chatbots in health care. It would thus seem beneficial to have medical expert opinions on the use of this technology that is intended to supplement or even replace specific roles of HCPs. The purpose of this study was to examine the perspectives of practicing medical physicians on the use of health care chatbots for patients. As physicians are the primary point of care for patients, their approval is an important gate to the dissemination of chatbots into medical practice. The findings of this research will help to either justify or attenuate enthusiasm for health care chatbot applications as well as direct future work to better align with the needs of HCPs.

Top 7 Product Data Management Best Practices for 2023

Healthcare chatbots have been instrumental in addressing public health concerns, especially during the COVID-19 pandemic. They offer symptom checkers, reliable information about the virus, and guidance on necessary actions based on symptoms exhibited. One of the key advantages of chatbots is their ability to offer up-to-date information about testing centers, vaccination sites, and updated pandemic guidelines.

As the AI field lacks diversity, bias at the level of the algorithm and modeling choices may be overlooked by developers [102]. In a study using 2 cases, differences in prediction accuracy were shown concerning gender and insurance type for intensive care unit mortality and psychiatric readmissions [103]. You can foun additiona information about ai customer service and artificial intelligence and NLP. On a larger scale, this may exacerbate barriers to health care for minorities or underprivileged individuals, leading to worse health outcomes. Identifying the source of algorithm bias is crucial for addressing health care disparities between various demographic groups and improving data collection. Although there are a variety of techniques for the development of chatbots, the general layout is relatively straightforward. As a computer application that uses ML to mimic human conversation, the underlying concept is similar for all types with 4 essential stages (input processing, input understanding, response generation, and response selection) [14].

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]. 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.

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. Healthy diets and weight control are key to successful disease management, as obesity is a significant risk factor for chronic conditions. Chatbots have been incorporated into health coaching systems to address health behavior modifications. For example, CoachAI and Smart Wireless Interactive Health System used chatbot technology to track patients’ progress, provide insight to physicians, and suggest suitable activities [45,46].

Provide mental health assistance

They conducted more than 100 interviews with students, counselors and administrators to design the app, she said. Another app, Replika, has millions of users who create their online friend in the app to overcome loneliness. As per a report in The Guardian, a middle-aged woman named Melissa, living in Iowa, US, relies on AI to get through her day. She has struggled with mental health issues all her life and says that using an AI chatbot is much more convenient than visiting a therapist. For years, we have been relying on therapists and mental health counsellors to help us navigate the challenges of life. There are various factors, such as money, time and convenience, that could stop people from knocking at a therapist’s door.

However, there are different levels of maturity to a conversational chatbot – not all of them offer the same depth of conversation. Informative chatbots provide helpful information for users, often in the form of pop-ups, notifications, and breaking stories. Furthermore, hospitals and private clinics use medical chat bots to triage and clerk patients even before they come into the consulting room.

We recommend using ready-made SDKs, libraries, and APIs to keep the chatbot development budget under control. This practice lowers the cost of building the app, but it also speeds up the time to market significantly. Another point to consider is whether your medical AI chatbot will be integrated with existing software systems and applications like EHR, telemedicine platforms, etc.

It saves time and money by allowing patients to perform many activities like submitting documents, making appointments, self-diagnosis, etc., online. Yes, many healthcare chatbots can act as symptom checkers to facilitate self-diagnosis. Users usually prefer chatbots over symptom checker apps as they can precisely describe how they feel to a bot in the form of a simple conversation and get reliable and real-time results. Patient inquiries span the full spectrum of human health, from guidance on healthy living to support with mental health. Watsonx Assistant AI chatbots can field a full range of patient inquiries and respond with intelligent, actionable recommendations and patient guidance in real time.

These bots ask relevant questions about the patients’ symptoms, with automated responses that aim to produce a sufficient medical history for the doctor. Subsequently, these patient histories are sent via a messaging interface to the doctor, who triages to determine which patients need to be seen first and which patients require a brief consultation. 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.

  • With abundant benefits and rapid innovation in conversational AI, adoption is accelerating quickly.
  • They are trained to have empathetic conversations with patients, so when you’re experiencing a mental health issue, they’re there to provide mental support, and necessary resources, and teach you coping methods to help you deal with almost any situation.
  • Therefore, it has become necessary to leverage digital tools that disseminate authoritative healthcare information to people across the globe.
  • Obviously, chatbots cannot replace therapists and physicians, but they can provide a trusted and unbiased go-to place for the patient around-the-clock.
  • Such probabilities have been called diagnostic probabilities (Wulff et al. 1986), a form of epistemic probability.

Key areas of focus are safety, effectiveness, timeliness, efficiency, equitability, and patient-centered care [20]. Today, chatbots offer diagnosis of symptoms, mental healthcare consultation, nutrition facts and tracking, and more. For example, in 2020 WhatsApp collaborated with the World Health Organization (WHO) to make a chatbot service that answers users’ questions on COVID-19. IBM watsonx Assistant helps organizations provide better customer experiences with an AI chatbot that understands the language of the business, connects to existing customer care systems, and deploys anywhere with enterprise security and scalability. Watsonx Assistant automates repetitive tasks and uses machine learning to resolve customer support issues quickly and efficiently. Ensuring compliance with healthcare chatbots involves a meticulous understanding of industry regulations, such as HIPAA.

Chatbots and conversational AI have enormous potential to transform healthcare delivery. As a healthcare leader, you may be wondering about the top use cases for implementing chatbots and how they can benefit your organization specifically. While there are some challenges left to be addressed, we’re more than excited to see how the future of chatbots in healthcare unfolds. They are trained to have empathetic conversations with patients, so when you’re experiencing a mental health issue, they’re there to provide mental support, and necessary resources, and teach you coping methods to help you deal with almost any situation. Let’s dive a little deeper and talk about a couple of the top chatbot use cases in healthcare. It’s also not realistic to expect every patient to be on board with digital-care solutions beyond their current use in this pandemic.

chatbot in healthcare

We are a global strategy consulting firm that assists business leaders in gaining a competitive edge and accelerating growth. We provide technological solutions, clinical research services, and advanced analytics to the healthcare sector, and we are committed to forming creative connections that result in actionable insights and innovations. The Myna Mahila Foundation is also partnering with another Gates grantee to propose developing privacy standards for handling data for reproductive health. The foundation, which is working with an outside technology firm to develop the chatbot, is also considering other steps to help ensure the privacy of users. Dr. Christopher Longhurst, chief medical officer at the UC San Diego Health, has led the implementation of AI tools in health care settings and said it is important to test and measure the impact of these new tools on patient health outcomes.

There are three primary use cases for the utilization of chatbot technology in healthcare – informative, conversational, and prescriptive. These chatbots vary in their conversational style, the depth of communication, and the type of solutions they provide. Patients love speaking to real-life doctors, and artificial intelligence is what makes chatbots sound more human. In fact, some chatbots with complex self-learning algorithms can successfully maintain in-depth, nearly human-like conversations. The use of chatbots in health care presents a novel set of moral and ethical challenges that must be addressed for the public to fully embrace this technology. Although efforts have been made to address these concerns, current guidelines and policies are still far behind the rapid technological advances [94].


Through natural language understanding algorithms, these virtual assistants can decipher the intent behind the questions posed by patients. This allows them to provide relevant responses tailored to the specific needs of each individual. One of the key advantages of chatbots is their ability to offer reliable and up-to-date information sourced from trusted medical databases or institutions. By accessing a vast pool of medical resources, chatbots can provide users with comprehensive information on various health topics. The implementation of chatbots also benefits healthcare teams by allowing them to focus on more critical tasks rather than spending excessive time managing appointment schedules manually. By automating this administrative aspect, medical professionals can dedicate more attention to patient care and complex cases that require their expertise.

A brief historical overview, along with the developmental progress and design characteristics, is first introduced. 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. To facilitate this assessment, we develop and present an evaluative framework that classifies the key characteristics of healthbots. Concerns over the unknown and unintelligible “black boxes” of ML have limited the adoption of NLP-driven chatbot interventions by the medical community, despite the potential they have in increasing and improving access to healthcare.

chatbot in healthcare

Mental health chatbots like Woebot, Wysa, and Youper are trained in Cognitive Behavioural Therapy (CBT), which helps to treat problems by transforming the way patients think and behave. The idea of a digital personal assistant is tempting, but a healthcare chatbot goes a mile beyond that. From patient care to intelligent use of finances, its benefits are wide-ranging and make it a top priority in the Healthcare industry. Deliver your best self-service support experience across all patient engagement points and seamlessly integrate AI-powered agents with existing systems and processes.

The framework proposed as well as the insights gleaned from the review of commercially available healthbot apps will facilitate a greater understanding of how such apps should be evaluated. While chatbots offer many benefits for healthcare providers and patients, several challenges must be addressed to implement them successfully. Chatbots provide patients with a more personalized experience, making them feel more connected to their healthcare providers. Chatbots can help patients feel more comfortable and involved in their healthcare by conversationally engaging with them. When using chatbots in healthcare, it is essential to ensure that patients understand how their data will be used and are allowed to opt out if they choose.

Chatbots Revolutionizing Access to Mental Health Care: A Deep Dive – Medriva

Chatbots Revolutionizing Access to Mental Health Care: A Deep Dive.

Posted: Wed, 21 Feb 2024 18:58:02 GMT [source]

Not only can they recommend the most useful insurance policies for the patient’s medical condition, but they can save time and money by streamlining the process of claiming insurance and simplifying the payment chatbot in healthcare process. Customized chat technology helps patients avoid unnecessary lab tests or expensive treatments. Our tech team has prepared five app ideas for different types of AI chatbots in healthcare.

Usually, chatbots in healthcare use natural language processing (NLP) algorithms or large language models (LLM) and ML techniques to understand user queries and generate relevant responses. Moreover, chatbots empower patients to provide valuable feedback on their healthcare experiences. Through conversational interfaces, they create an environment where individuals feel comfortable sharing their thoughts, concerns, and suggestions. This feedback is invaluable for providers as it helps them identify areas that require improvement and enhance the overall quality of care.

chatbot in healthcare

The benefit of using chatbots for smoking cessation across various age groups has been highlighted in numerous studies showing improved motivation, accessibility, and adherence to treatment, which have led to increased smoking abstinence [89-91]. 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].

First, we introduce health chatbots and their historical background and clarify their technical capabilities to support the work of healthcare professionals. Second, we consider how the implementation of chatbots amplifies the project of rationality and automation in professional work as well as changes in decision-making based on epistemic probability. We then discuss ethical and social issues relating to health chatbots from the perspective of professional ethics by considering professional-patient relations and the changing position of these stakeholders on health and medical assessments. Finally, to ground our analysis, we employ the perspective of HCPs and list critical aspects and challenges relating to how chatbots may transform clinical capabilities and change patient-clinician relationships in clinical practices in the long run. We stress here that our intention is not to provide empirical evidence for or against chatbots in health care; it is to advance discussions of professional ethics in the context of novel technologies.

By streamlining workflows across different departments within hospitals or clinics, chatbots contribute significantly to cost savings for healthcare organizations. They ensure that communication between medical professionals is seamless and efficient, minimizing delays in patient care. For example, when a physician prescribes medication, a chatbot can automatically send an electronic prescription directly to pharmacies, eliminating the need for manual intervention. Moreover, as patients grow to trust chatbots more, they may lose trust in healthcare professionals.

Still, it may not work for a doctor seeking information about drug dosages or adverse effects. First, the chatbot helps Peter relieve the pressure of his perceived mistake by letting him know it’s not out of the ordinary, which may restore his confidence; then, it provides useful steps to help him deal with it better. This allows doctors to process prescription refills in batch or automate them in cases where doctor intervention is not necessary.

Leave a Comment

Your email address will not be published. Required fields are marked *