TY - JOUR
T1 - Assessing ChatGPT responses to patient questions on epidural steroid injections
T2 - A comparative study of general vs specific queries
AU - Olivier, Timothy
AU - Ma, Zilin
AU - Patel, Ankit
AU - Shi, Weibin
AU - Murtuza, Mohammed
AU - Hatchard, Nicole E.
AU - Pan, Xiaoyu Norman
AU - Annaswamy, Thiru M.
N1 - Publisher Copyright:
© 2025 The Authors
PY - 2025/6
Y1 - 2025/6
N2 - Background: Artificial intelligence (AI) is becoming more integrated into healthcare, with large language models (LLMs) like ChatGPT being widely used by patients to answer medical questions. Given the increasing reliance on AI for health-related information, it's important to evaluate how well these models perform in addressing common patient concerns, especially in procedural medicine. To date, no studies have specifically examined AI's role in addressing patient questions related to epidural steroid injections (ESIs), making this an important area for investigation. Objective: This study examines ChatGPT's ability to answer patient questions about epidural steroid injections (ESIs), focusing on response accuracy, readability, and overall usefulness. Our aim was to evaluate and compare the content, accuracy, and user-friendliness of AI-generated information on common peri-procedural questions and complications associated with ESIs, thereby extending the application of AI as a triage tool into pain management and interventional spine procedures. Methods: We formulated and compiled 29 common patient questions about ESIs and tested ChatGPT's responses in both general and specific formats. Two interventional pain specialists reviewed the AI-generated answers, assessing them for accuracy, clarity, empathy, and directness using a Likert scale. Readability scores were calculated using Flesch-Kincaid Reading Level and Flesch Reading Ease scales. Statistical analyses were performed to compare general versus specific responses. Results: General queries led to longer, more detailed responses, but readability was similar between general and specific formats. Subjective analysis showed that general responses were rated higher for accuracy, clarity, and responsiveness. However, neither format demonstrated strong empathy, and some general queries resulted in off-topic responses, underscoring the importance of precise wording when interacting with AI. Conclusion: ChatGPT can provide clear and largely accurate answers to patient questions about ESIs, with general prompts often producing more complete responses. However, AI-generated content still has limitations, particularly in conveying empathy and avoiding tangential information. These findings highlight the need for thoughtful prompt design and further research into how AI can be integrated into clinical workflows while ensuring accuracy and patient safety.
AB - Background: Artificial intelligence (AI) is becoming more integrated into healthcare, with large language models (LLMs) like ChatGPT being widely used by patients to answer medical questions. Given the increasing reliance on AI for health-related information, it's important to evaluate how well these models perform in addressing common patient concerns, especially in procedural medicine. To date, no studies have specifically examined AI's role in addressing patient questions related to epidural steroid injections (ESIs), making this an important area for investigation. Objective: This study examines ChatGPT's ability to answer patient questions about epidural steroid injections (ESIs), focusing on response accuracy, readability, and overall usefulness. Our aim was to evaluate and compare the content, accuracy, and user-friendliness of AI-generated information on common peri-procedural questions and complications associated with ESIs, thereby extending the application of AI as a triage tool into pain management and interventional spine procedures. Methods: We formulated and compiled 29 common patient questions about ESIs and tested ChatGPT's responses in both general and specific formats. Two interventional pain specialists reviewed the AI-generated answers, assessing them for accuracy, clarity, empathy, and directness using a Likert scale. Readability scores were calculated using Flesch-Kincaid Reading Level and Flesch Reading Ease scales. Statistical analyses were performed to compare general versus specific responses. Results: General queries led to longer, more detailed responses, but readability was similar between general and specific formats. Subjective analysis showed that general responses were rated higher for accuracy, clarity, and responsiveness. However, neither format demonstrated strong empathy, and some general queries resulted in off-topic responses, underscoring the importance of precise wording when interacting with AI. Conclusion: ChatGPT can provide clear and largely accurate answers to patient questions about ESIs, with general prompts often producing more complete responses. However, AI-generated content still has limitations, particularly in conveying empathy and avoiding tangential information. These findings highlight the need for thoughtful prompt design and further research into how AI can be integrated into clinical workflows while ensuring accuracy and patient safety.
UR - https://www.scopus.com/pages/publications/105005941826
UR - https://www.scopus.com/pages/publications/105005941826#tab=citedBy
U2 - 10.1016/j.inpm.2025.100592
DO - 10.1016/j.inpm.2025.100592
M3 - Article
C2 - 40511324
AN - SCOPUS:105005941826
SN - 2772-5944
VL - 4
JO - Interventional Pain Medicine
JF - Interventional Pain Medicine
IS - 2
M1 - 100592
ER -