Evaluating the Effectiveness of Artificial Intelligence–powered Large Language Models Application in Disseminating Appropriate and Readable Health Information in Urology

No AccessJournal of UrologyNew Technology and Techniques10 Jul 2023Evaluating the Effectiveness of Artificial Intelligence–powered Large Language Models Application in Disseminating Appropriate and Readable Health Information in Urology Ryan Davis, Michael Eppler, Oluwatobiloba Ayo-Ajibola, Jeffrey C. Loh-Doyle, Jamal Nabhani, Mary Samplaski, Inderbir Gill, and Giovanni E. Cacciamani Ryan DavisRyan Davis https://orcid.org/0009-0002-0408-8380 USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California More articles by this author , Michael EpplerMichael Eppler https://orcid.org/0000-0001-6336-5857 USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California More articles by this author , Oluwatobiloba Ayo-AjibolaOluwatobiloba Ayo-Ajibola USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California More articles by this author , Jeffrey C. Loh-DoyleJeffrey C. Loh-Doyle https://orcid.org/0000-0002-7094-482X USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California More articles by this author , Jamal NabhaniJamal Nabhani USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California More articles by this author , Mary SamplaskiMary Samplaski USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California More articles by this author , Inderbir GillInderbir Gill USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California More articles by this author , and Giovanni E. CacciamaniGiovanni E. Cacciamani *Correspondence: Catherine and Joseph Aresty Department of Urology, University of Southern California,Los Angeles, CA telephone: 626-491-1531; E-mail Address: [email protected] USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003615AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareFacebookLinked InTwitterEmail Abstract Purpose: The Internet is a ubiquitous source of medical information, and natural language processors are gaining popularity as alternatives to traditional search engines. However, suitability of their generated content for patients is not well understood. We aimed to evaluate the appropriateness and readability of natural language processor-generated responses to urology-related medical inquiries. Materials and Methods: Eighteen patient questions were developed based on Google Trends and were used as inputs in ChatGPT. Three categories were assessed: oncologic, benign, and emergency. Questions in each category were either treatment or sign/symptom-related questions. Three native English-speaking Board-Certified urologists independently assessed appropriateness of ChatGPT outputs for patient counseling using accuracy, comprehensiveness, and clarity as proxies for appropriateness. Readability was assessed using the Flesch Reading Ease and Flesh-Kincaid Reading Grade Level formulas. Additional measures were created based on validated tools and assessed by 3 independent reviewers. Results: Fourteen of 18 (77.8%) responses were deemed appropriate, with clarity having the most 4 and 5 scores (P = .01). There was no significant difference in appropriateness of the responses between treatments and symptoms or between different categories of conditions. The most common reason from urologists for low scores was responses lacking information—sometimes vital information. The mean (SD) Flesch Reading Ease score was 35.5 (SD=10.2) and the mean Flesh-Kincaid Reading Grade Level score was 13.5 (1.74). Additional quality assessment scores showed no significant differences between different categories of conditions. Conclusions: Despite impressive capabilities, natural language processors have limitations as sources of medical information. Refinement is crucial before adoption for this purpose. REFERENCES 1. . Digital Around the World. 2023. https://datareportal.com/global-digital-overview. Google Scholar 2. . Odds of talking to healthcare providers as the initial source of healthcare information: updated cross-sectional results from the Health Information National Trends Survey (HINTS). 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Lancet Oncol.2019; 20(11):1491-1492. Crossref, Medline, Google Scholar Submitted March 15, 2023; accepted June 27, 2023; published 000. Support: None. Conflict of Interest: The Authors have no conflicts of interest to disclose. Ethics Statement: All human subjects provided written informed consent with guarantees of confidentiality. © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetailsCited byDi H and Wen Y Evaluating the Effectiveness of Artificial Intelligence–Powered Large Language Models Application in Disseminating Appropriate and Readable Health Information in Urology. Letter.Journal of Urology, Supplementary Materials Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.Keywordsurologytherapeuticsartificial intelligencecommunicationhealthsigns and symptomsMetrics Author Information Ryan Davis USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California More articles by this author Michael Eppler USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California More articles by this author Oluwatobiloba Ayo-Ajibola USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California More articles by this author Jeffrey C. Loh-Doyle USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California More articles by this author Jamal Nabhani USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California More articles by this author Mary Samplaski USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California More articles by this author Inderbir Gill USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California More articles by this author Giovanni E. Cacciamani USC Institute of Urology, and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California AI Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, California *Correspondence: Catherine and Joseph Aresty Department of Urology, University of Southern California,Los Angeles, CA telephone: 626-491-1531; E-mail Address: [email protected] More articles by this author Expand All Submitted March 15, 2023; accepted June 27, 2023; published 000. Support: None. Conflict of Interest: The Authors have no conflicts of interest to disclose. Ethics Statement: All human subjects provided written informed consent with guarantees of confidentiality. Advertisement PDF downloadLoading ...