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Taylor WL, Cheng R, Weinblatt AI, Bergstein V, Long WJ. An Artificial Intelligence Chatbot is an Accurate and Useful Online Patient Resource Prior to Total Knee Arthroplasty. J Arthroplasty 2024; 39:S358-S362. [PMID: 38350517 DOI: 10.1016/j.arth.2024.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 02/05/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Online information is a useful resource for patients seeking advice on their orthopaedic care. While traditional websites provide responses to specific frequently asked questions (FAQs), sophisticated artificial intelligence tools may be able to provide the same information to patients in a more accessible manner. Chat Generative Pretrained Transformer (ChatGPT) is a powerful artificial intelligence chatbot that has been shown to effectively draw on its large reserves of information in a conversational context with a user. The purpose of this study was to assess the accuracy and reliability of ChatGPT-generated responses to FAQs regarding total knee arthroplasty. METHODS We distributed a survey that challenged arthroplasty surgeons to identify which of the 2 responses to FAQs on our institution's website was human-written and which was generated by ChatGPT. All questions were total knee arthroplasty-related. The second portion of the survey investigated the potential to further leverage ChatGPT to assist with translation and accessibility as a means to better meet the needs of our diverse patient population. RESULTS Surgeons correctly identified the ChatGPT-generated responses 4 out of 10 times on average (range: 0 to 7). No consensus was reached on any of the responses to the FAQs. Additionally, over 90% of our surgeons strongly encouraged the use of ChatGPT to more effectively accommodate the diverse patient populations that seek information from our hospital's online resources. CONCLUSIONS ChatGPT provided accurate, reliable answers to our website's FAQs. Surgeons also agreed that ChatGPT's ability to provide targeted, language-specific responses to FAQs would be of benefit to our diverse patient population.
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Affiliation(s)
- Walter L Taylor
- Department of Adult Reconstruction and Joint Replacement, Hospital for Special Surgery, New York, New York
| | - Ryan Cheng
- Department of Adult Reconstruction and Joint Replacement, Hospital for Special Surgery, New York, New York
| | - Aaron I Weinblatt
- Department of Adult Reconstruction and Joint Replacement, Hospital for Special Surgery, New York, New York
| | - Victoria Bergstein
- Department of Adult Reconstruction and Joint Replacement, Hospital for Special Surgery, New York, New York
| | - William J Long
- Department of Adult Reconstruction and Joint Replacement, Hospital for Special Surgery, New York, New York
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Slavotinek A, Prasad H, Outram S, Scollon S, Rego S, Yip T, Hoban H, Foreman KM, Kelley W, Finnila C, Berg J, Murali P, Bonini KE, Martin LJ, Hott A. Information-seeking preferences in diverse patients receiving a genetic testing result in the Clinical Sequencing Evidence-Generating Research (CSER) study. Genet Med 2023; 25:100899. [PMID: 37212252 PMCID: PMC10524447 DOI: 10.1016/j.gim.2023.100899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 05/03/2023] [Accepted: 05/07/2023] [Indexed: 05/23/2023] Open
Abstract
PURPOSE Accurate and understandable information after genetic testing is critical for patients, family members, and professionals alike. METHODS As part of a cross-site study from the Clinical Sequencing Evidence-Generating Research consortium, we investigated the information-seeking practices among patients and family members at 5 to 7 months after genetic testing results disclosure, assessing the perceived utility of a variety of information sources, such as family and friends, health care providers, support groups, and the internet. RESULTS We found that individuals placed a high value on information obtained from genetics professionals and health care workers, independent of genetic testing result case classifications as positive, inconclusive, or negative. The internet was also highly utilized and ranked. Study participants rated some information sources as more useful for positive results compared with inconclusive or negative outcomes, emphasizing that it may be difficult to identify helpful information for individuals receiving an uncertain or negative result. There were few data from non-English speakers, highlighting the need to develop strategies to reach this population. CONCLUSION Our study emphasizes the need for clinicians to provide accurate and comprehensible information to individuals from diverse populations after genetic testing.
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Affiliation(s)
- Anne Slavotinek
- Division of Medical Genetics, Department of Pediatrics, University of California, San Francisco, San Francisco, CA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA.
| | - Hannah Prasad
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA
| | - Simon Outram
- Institute for Health & Aging, School of Nursing, University of California San Francisco, San Francisco, CA
| | - Sarah Scollon
- Department of Pediatrics, Baylor College of Medicine, Houston, TX
| | - Shannon Rego
- Division of Medical Genetics, Department of Pediatrics, University of California, San Francisco, San Francisco, CA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA
| | - Tiffany Yip
- Division of Medical Genetics, Department of Pediatrics, University of California, San Francisco, San Francisco, CA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA
| | - Hannah Hoban
- Division of Medical Genetics, Department of Pediatrics, University of California, San Francisco, San Francisco, CA; Institute for Human Genetics, University of California, San Francisco, San Francisco, CA
| | - Kate M Foreman
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | | | | | - Jonathan Berg
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Priyanka Murali
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA
| | - Katherine E Bonini
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Lisa J Martin
- Division of Human Genetics Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH
| | - Adam Hott
- HudsonAlpha Institute for Biotechnology, Huntsville, AL
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