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Canadian Urological Association Journal logoLink to Canadian Urological Association Journal
. 2024 Jun 17;18(11):E346–E349. doi: 10.5489/cuaj.8762

Implications of using conversational robots (chatbots) in uro-oncology

A patient and physician perspective

Daniel Alfonso Nieva-Posso 1, Daniel Andrés Nieva-Posso 1, Herney Andrés García-Perdomo 1,2,
PMCID: PMC11534396  PMID: 38976890

Abstract

Chatbots, or conversational robots, have become a strategy or support tool for urologic patient care, diagnostic communication, and treatment. With regard to patients, studies have shown that chatbots can answer medical questions with similar percentages of acceptability as urologists. In addition, they can contribute to patient education, allowing them to ask questions that do not arise during medical consultation. They have also proven to be good tools for health promotion and disease prevention. These benefits can also serve doctors, as robots can support medical consultation and the reading of medical records, making patient care more efficient; however, there are several limitations, including the accuracy of bot-generated answers and the acceptability that urologists give to this type of tool.

INTRODUCTION

Artificial intelligence (AI) has changed how we acquire, analyze, and transmit information.1 Currently, there are various forms of AI, but one of the most discussed, used, and promoted is the so-called chatbot or intelligent bot; this is defined as a set of programs that can hold a conversation with a person using a series of algorithms that allow the construction of complex answers through the introduction of data or specific questions. 2,3 By 2023, at least 100 million people worldwide will be using chatbots for a variety of purposes: entertainment, travel assistance, timely information retrieval, transcription, and education.4,5 Several studies have even evaluated the effectiveness and benefits of implementing this type of program in education, customer service, and even in research.6

The application possibilities and benefits proposed by chatbots in medical consultation and as a support for with patients with questions about their disease are high. Ayers et al compared the answers from a chatbot with those offered by general practitioners to patients consulting about their disease. They found that 78.6% of patients preferred the chatbot response because they felt that the AI response had more empathy and quality, especially in patients with terminal diseases or poor prognoses.7 Similar results have been identified in other studies, such as that of Goodman et al, where a group of general practitioners and recently graduated specialists evaluated the answers generated by chatbots on medical knowledge, consultation, identification of clinical signs and symptoms, and found almost perfect answers, with scores of 5.5/6.0.8 Chatbots have proven helpful in medical education as well, especially in prostate cancer patients. Allen et al demonstrated that using chatbots as information and communication channels in African American prostate cancer patients contributed significantly to their knowledge of their disease, improved their treatment decisions, and made them more responsive to their treating urologist.9

Chi et al found that the application of conversational AI systems has benefited physicians in the review of medical records, as it reduces the time it takes to do so by 18% and allows the identification of critical processes within the history much faster,10 increasing the chances of a more effective diagnosis or treatment, a greater concentration of resources, and reduction of errors or omission of data that may occur in some cases, especially in patients who are unable to communicate.

Urologic cancers account for 13% of all cancer cases worldwide, with an estimated 2.6 million cases by 2022, surpassing breast cancer, for which incidence is 2.3 million cases.11,12 Therefore, the workload is high for the health system and the multidisciplinary team of professionals who treat these conditions.

We aimed to review the benefits and limitations of applying conversational robots in uro-oncology consultation, focusing on medical, patient, and caregiver perspectives, well as some uro-oncology education.

USE OF CHATBOTS IN UROLOGY

Patient resource

Chatbots have proven to be an excellent tool to support patients, as they can be available 24 hours a day, help identify signs and symptoms, and understand precautions about medication.13

The main benefits of chatbots have been identified in the area of patient education; chatbots can contribute to the transmission of accurate medical information according to the questions that the patient asks. For example. Kobori et al demonstrated that chatbots can help patients to identify if they have signs and symptoms of a sexually transmitted disease, motivating them to visit their doctor in 97.7% of cases, thus becoming diagnostic support, especially in the younger population.14

Cancer education has been one of the areas in which the implementation of chatbots has had the most significant impact in urology, as it offers remote, easily accessible support. The bots can be programmed to answer questions about treatment, and surgical procedures, allowing patients to take control of their health and contribute positively to the discussions about their cancer.15 Studies, such as the one by Allen et al, have shown that most (62%) patients find the application very good, stating that it significantly increased their general knowledge of their disease, clarified many doubts about the treatment they were receiving, increased by 86% the confidence and expertise with which they make decisions about their treatment, and allows them to have more constructive discussions with their urologist.9

Owens et al evaluated the usefulness of conversation simulation software in African American patients diagnosed with prostate cancer, finding that this type of application stimulates the confidence of patients to ask questions and make decisions by 67%.16 The versatility and programming possibilities of these systems make their applications in the context of the management support of an oncologic patient very broad (Figure 1).15

Figure 1.

Figure 1

Mind map of the main aspects and benefits of chatbots in uro-oncology.

Chatbots have also been shown to be helpful in other urologic problems, such as urolithiasis. Goldenthal et al demonstrated that the use of chatbots in patients who had undergone ureteroscopy made patients feel comfortable identifying non-urgent situations.17 Kim et al evaluated the usefulness of conversational AI in women who frequently suffer from interstitial cystitis, finding that this type of application improves patients’ self-efficacy, making them feel more confident in receiving information from their treating physician.18

Health promotion

Another benefit of chatbots is health promotion. Studies, such as that by Aggarwal et al, found that the programming of chatbots for the acquisition of healthy habits reduced smoking in 4.27% of participants in a short period, and also allowed greater adherence to medications due to its ability to answer patient questions around the clock.19 Studies, such as that by Musheyev et al, found that conversational AI can accurately answer (in a range of 4/5) the typical questions asked by patients and families, becoming an alternative implementation to help combat the misinformation that can be found in conventional media.20

Support for doctors and medical trainees

For physicians chatbots can help identify critical elements in medical records, improving decision-making and contributing to improving efficiency and consultation time. Kim et al demonstrated that the use of chatbots in medical consultations can streamline the diagnosis and medical interview process for ambulatory patients with urologic problems, improving the through-put rates of hospitals, clinics, and urology residents, and allowing for more accurate diagnosis in a shorter amount of time.21 Reviewing the medical records of oncology patients represents one of the main challenges for treaters due to their complexity and length. Chi et al found that the application of chatbots as support for the review of medical records allows the identification of critical aspects of history faster, is more efficient, and reduces the review time by 18%.10

The degree of acceptability by doctors of this type of support tool is high and was most popular during the COVID-19 pandemic; a study by Linares et al found that 66% of doctors have a lot of enthusiasm and interest in the application of AI.22 Chatbots have also impacted clinical research by supporting data analysis, identifying patterns, helping to characterize patients, and extracting data for research processes.23

Urological education

Education has been one of the areas most influenced by chatbots. Currently, the training and practice opportunities offered by AI are many, and the possibility of recreating practice scenarios that allow evaluation, study, and review for students is unlimited.24 Particularly in surgical specialties, AI has become a training tool for residents. Gómez et al found that the use of AI in surgical training improves students’ ability to make complex decisions and understand complex surgeries and improves results, efficiency, and performance.25

It is essential to clarify that chatbots are a support tool and not definitive elements in the training and education of urology students. The teacher-student or specialist-resident interaction is one of the primary keys to guaranteeing efficient academic training.23

Limitations of the use of chatbots urology

It is essential to mention that limitations and negative consequences have been found regarding implementing chatbots, particularly in uro-oncology. Zhang et al have shown that chatbots, or language models, have a high risk of answering some questions with ambiguity, bias, incomplete answers, or omitting information that may be relevant.26 Furthermore, May et al have shown that different types of chatbots have different response accuracy, so it is essential to continuously supervises their implementation.27

Another element to consider is the low acceptability of the use of chatbots, such as ChatGPT, in urological practice. Eppler et al have shown that <47% of urologists use ChatGPT in their daily academic activities, and <20% use it for their clinical activities. More than half (62%) believe there are ethical limitations to using ChatGPT, especially as support in research.28

There are many discussions about the effects of using ChatGPT in education, including the possibility of a decrease in critical thinking or the development of surgical skills. Studies have shown that the use of simulation has a positive effect on students, and a study by Zawiah et al did not find significant differences in the skills of students who use ChatGPT and those who do not.29

For patients, it is essential to consider some limitations, such as accessibility and digital literacy. In 2019, 27% of U.S. inhabitants do not have access to quality internet, and 20% do not have a smartphone, which would limit their possibility of accessing these types of tools to support their health.30 The lack of connectivity represents an enormous challenge to implementation.

CONCLUSIONS

AI technology has become a strategy with both clinical and teaching applications. If used cautiously, it can be used as a resource for patients, to promote good health and joint clinical decision-making, and to support and educate healthcare professionals.

Footnotes

COMPETING INTERESTS: The authors do not report any competing personal or financial interests related to this work.

This paper has been peer reviewed.

REFERENCES

  • 1.Xu L, Sanders L, Li K, et al. Chatbot for healthcare and oncology applications using artificial intelligence and machine learning: Systematic review. JMIR Cancer. 2021;7:e27850. doi: 10.2196/27850. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Dahiya M. A Tool of conversation: Chatbot. 2017. [Accessed June 11, 2024]. Available from: www.ijcseonline.org.
  • 3.Adamopoulou E, Moussiades L. An overview of chatbot technology. 2020:373–83. doi: 10.1007/978-3-030-49186-4_31. [DOI] [Google Scholar]
  • 4.Eysenbach G. The role of ChatGPT, generative language models, and artificial intelligence in medical education: A conversation with ChatGPT and a call for papers. JMIR Med Educ. 2023;9:e46885. doi: 10.2196/46885. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Ghorashi N, Ismail A, Ghosh P, et al. AI-powered chatbots in medical education: Potential applications and implications. Cureus. 2023;15:e43271. doi: 10.7759/cureus.43271. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Eysenbach G. The role of ChatGPT, generative language models, and artificial intelligence in medical education: A conversation with ChatGPT and a call for papers. JMIR Med Educ. 2023;9:e46885. doi: 10.2196/46885. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Ayers JW, Poliak A, Dredze M, et al. Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA Intern Med. 2023;183:589. doi: 10.1001/jamainternmed.2023.1838. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Goodman RS, Patrinely JR, Stone CA, et al. Accuracy and reliability of chatbot responses to physician questions. JAMA Netw Open. 2023;6:e2336483. doi: 10.1001/jamanetworkopen.2023.36483. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Allen JD, Reich A, Cuevas AG, et al. Preparing African American men to make informed prostate cancer screening decisions: Development and pilot testing of an interactive online decision aid. JMIR Mhealth Uhealth. 2020;8:e15502. doi: 10.2196/15502. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Chi EA, Chi G, Tsui CT, et al. Development and validation of an artificial intelligence system to optimize clinician review of patient records. JAMA Netw Open. 2021;4:e2117391. doi: 10.1001/jamanetworkopen.2021.17391. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Ferlay J, Ervik M, Lam F, et al. Global cancer observatory: Cancer today [2022] [Accessed June 11, 2024]. Available at: https://gco.iarc.fr/today.
  • 12.Ferlay J, Ervik M, Lam F, et al. Global cancer observatory: Breast cancer [2022] [Accessed June 11, 2024]. Available at: https://gco.iarc.fr/today.
  • 13.Temsah O, Khan SA, Chaiah Y, et al. Overview of early ChatGPT’s presence in medical literature: Insights from a hybrid literature review by ChatGPT and human experts. Cureus. 2023;15:e37281. doi: 10.7759/cureus.37281. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Kobori Y, Osaka A, Soh S, Okada H. MP15-03 novel application for sexual transmitted infection screening with an ai chatbot. J Urol. 2018;199:e189–90. doi: 10.1016/j.juro.2018.02.516. [DOI] [Google Scholar]
  • 15.Talyshinskii A, Naik N, Hameed BMZ, et al. Potential of AI-driven chatbots in urology: Revolutionizing patient care through artificial intelligence. Curr Urol Rep. 2024;25:9–18. doi: 10.1007/s11934-023-01184-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Owens OL, Felder T, Tavakoli AS, et al. Evaluation of a computer-based decision aid for promoting informed prostate cancer screening decisions among African American men: iDecide. Am J Health Promot. 2019;33:267–78. doi: 10.1177/0890117118786866. [DOI] [PubMed] [Google Scholar]
  • 17.Goldenthal SB, Portney D, Steppe E, et al. Assessing the feasibility of a chatbot after ureteroscopy. Mhealth. 2019;5:8. doi: 10.21037/mhealth.2019.03.01. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Kim EK, Brown LA, Seltzer EK, et al. Development of a patient–centered text message-based platform for the self–management of interstitial cystitis/bladder pain syndrome symptoms. Neurourol Urodyn. 2023;42:510–22. doi: 10.1002/nau.25115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Aggarwal A, Tam CC, Wu D, et al. Artificial intelligence-based chatbots for promoting health behavioral changes: Systematic review. J Med Internet Res. 2023;25:e40789. doi: 10.2196/40789. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Musheyev D, Pan A, Loeb S, et al. How well do artificial intelligence chatbots respond to the top search queries about urological malignancies? Eur Urol. 2024;85:13–6. doi: 10.1016/j.eururo.2023.07.004. [DOI] [PubMed] [Google Scholar]
  • 21.Kim Y, Kim JH, Kim YM, et al. Predicting medical specialty from text based on a domain-specific pre-trained BERT. Int J Med Inform. 2023;170:104956. doi: 10.1016/j.ijmedinf.2022.104956. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Linares A, Bramstedt K, Chilukuri M, Doraiswamy Pm. Physician perceptions of surveillance: Wearables, Apps, and Chatbots for COVID-19. Digit Med. 2022;8:10. doi: 10.4103/digm.digm_28_21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Javid M, Reddiboina M, Bhandari M. Emergence of artificial generative intelligence and its potential impact on urology. Can J Urol. 2023:11588–98. [PubMed] [Google Scholar]
  • 24.Kim JK, Chua M, Rickard M, Lorenzo A. ChatGPT and large language model (LLM) chatbots: The current state of acceptability and a proposal for guidelines on utilization in academic medicine. J Pediatr Urol. 2023;19:598–604. doi: 10.1016/j.jpurol.2023.05.018. [DOI] [PubMed] [Google Scholar]
  • 25.Gómez Rivas J, Toribio Vázquez C, et al. Artificial intelligence and simulation in urology. Actas Urol Esp (Engl Ed) 2021;45:524–9. doi: 10.1016/j.acuroe.2021.07.001. [DOI] [PubMed] [Google Scholar]
  • 26.Zhang Y, Li Y, Cui L, et al. [Accessed June 11, 2024];Siren’s Song in the AI Ocean: A survey on hallucination in large language models. 2023 Available at: http://arxiv.org/abs/2309.01219. [Google Scholar]
  • 27.May M, Körner-Riffard K, Kollitsch L, et al. Evaluating the efficacy of AI chatbots as tutors in urology: A comparative analysis of responses to the 2022 in-service assessment of the European Board of Urology. Urol Int. 2024. Epub ahead of pint. [DOI] [PMC free article] [PubMed]
  • 28.Eppler M, Ganjavi C, Ramacciotti LS, et al. Awareness and use of ChatGPT and large language models: A prospective cross-sectional global survey in urology. Eur Urol. 2024;85:146–53. doi: 10.1016/j.eururo.2023.10.014. [DOI] [PubMed] [Google Scholar]
  • 29.Zawiah M, Al-Ashwal F, Gharaibeh L, et al. ChatGPT and clinical training: Perception, concerns, and practice of Pharm-D students. J Multidiscip Healthc. 16:4099–110. doi: 10.2147/JMDH.S439223. 202. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Goldenthal E, Park J, Liu SX, et al. Not all AI are equal: Exploring the accessibility of AI-mediated communication technology. Comput Human Behav. 2021;125:106975. doi: 10.1016/j.chb.2021.106975. [DOI] [Google Scholar]

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