Clinical trial NCT06481436: Use of Artificial Intelligence by Urogynecologic Patients
Official title: Use of Artificial Intelligence by Patients for Understanding of Diagnosis of Urogynecologic Conditions and Its Role in Treatment Decisions
Study type: INTERVENTIONAL
Overall status: ACTIVE_NOT_RECRUITING
Phase: NA
Conditions: Uterovaginal Prolapse
Urinary Incontinence
Lower Urinary Tract Symptoms
Keywords: Artificial Intelligence
Lead sponsor: Hartford Hospital
Sponsor class: OTHER
Collaborators: name: Boston Scientific Corporation
First posted: 2024-07-01
Enrollment: 125
Sex: FEMALE
Minimum age (years): 18
Maximum age (years): 89
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Randomized Controlled Trial
Primary purpose: OTHER

Brief summary: The goal of this clinical trial is to learn about how Urogynecology patients use Artificial Intelligence (AI) Chatbots like ChatGPT, and how it affects healthcare decision making. The main question\[s\] it aims to answer are:

* How does the AI Chatbot affect participants' understanding of diagnoses and participant satisfaction with a urogynecology consultation?
* How accurate is the chatbot-provided diagnosis and counseling information? Participants will be asked to use the ChatGPT chatbot and ask it questions about the main problem the participant is seeing the doctor for, and will also be asked to fill out some questionnaires.

Researchers will compare using the Chatbot before the visit, after the visit, or not at all to see if the way participants understand the information changes based on timing of use.

Detailed description: Artificial Intelligence (AI) in medicine and the use of machine learning to improve patient care and outcomes is a quickly developing field. Interest is building in the use and accuracy of AI chatbot programs such as ChatGPT for patient diagnosis and counseling. A recent study of Chat GPT accuracy compared with patient pamphlets about pelvic organ prolapse found comparable accuracy and completeness.Given the novelty of this field, no current literature exists regarding the use of AI chatbot technology for patient care and patient counseling in Urogynecology.

This will be a single-center, prospective, randomized, non-blinded study examining patient use of AI Chatbot technology (Chat GPT4) at initial visits to supplement understanding of urogynecologic problems. The primary aim of this study is to investigate the effect of use of an AI Chatbot platform on patient understanding of disease processes and treatment options prior to or following a consult with a urogynecologist at the initial visit. The secondary aims are to evaluate the accuracy of the chatbot-provided diagnosis (for participants applicable through randomization) and counseling information, and to evaluate patient satisfaction with the visit.

This study will recruit patients with presenting problems of prolapse, lower urinary tract symptoms, or incontinence into one of three arms: use of an AI chatbot prior to seeing the urogynecologist, use of an AI chatbot following a consult with the urogynecologist, no use of an AI chatbot at the time of the visit. During time of their initial urogynecology visit, data will be collected including demographics, Pelvic Floor Disorders Inventory (PFDI) intake questionnaire data, health literacy, Chat GPT conversation, office consultation diagnoses/treatment, physician questionnaire, and post-consultation questionnaire (Diagnosis and Treatment, Decisional Conflict Scale, Patient Satisfaction, Chatbot Satisfaction). Patients will be asked three months after their visit to complete the post-consultation questionnaire again.

Eligibility criteria: Inclusion Criteria:

* female
* presenting for their initial evaluation by a urogynecology physician for one of the following:

  * urinary incontinence (UI)
  * lower urinary tract symptoms (LUTS)
  * pelvic organ prolapse (POP)
* greater than or equal to18 and less than or equal to89 years old
* any race/ethnicity
* able to read or speak English or Spanish
* able/willing to consent to participate

Exclusion Criteria:

* male
* primary presenting problem other than UI, LUTS, or POP
* non-English or non-Spanish speaking
* pregnant or lactating, as this may affect patient treatment counseling
* unable/unwilling to consent to participate

Primary outcomes:
measure: Patient understanding of diagnosis and treatment - physician understanding of diagnosis
timeFrame: Baseline
measure: Patient understanding of diagnosis and treatment - physician perception of participant understanding
timeFrame: Baseline
measure: Patient understanding of diagnosis and treatment - participant understanding of diagnosis and treatment plan
timeFrame: Baseline and three month follow-up
measure: Patient understanding of diagnosis and treatment - understanding of diagnosis
timeFrame: Baseline and three month follow-up
measure: Patient understanding of diagnosis and treatment - decision making
timeFrame: Baseline and three month follow-up
Secondary outcomes:
measure: Patient satisfaction - medical visit
timeFrame: Baseline and three month follow-up
measure: Patient satisfaction - Chatbot
timeFrame: Baseline and three month follow-up
measure: Patient Chatbot use after urogynecology visit
timeFrame: Three month follow-up
measure: Chatbot information accuracy
timeFrame: Baseline
Other outcomes:
Locations:
city: Hartford
country: United States
facility: Hartford Hospital
state: Connecticut
Study officials:
affiliation: Hartford Hosptial Division of Urogynecology
name: Nicole J Wood, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: Hartford Hosptial Division of Urogynecology
name: Elena Tuntisky-Bitton, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Daykan Y, O'Reilly BA. The role of artificial intelligence in the future of urogynecology. Int Urogynecol J. 2023 Aug;34(8):1663-1666. doi: 10.1007/s00192-023-05612-3. Epub 2023 Jul 24.
citation: Robinson CJ, Swift S, Johnson DD, Almeida JS. Prediction of pelvic organ prolapse using an artificial neural network. Am J Obstet Gynecol. 2008 Aug;199(2):193.e1-6. doi: 10.1016/j.ajog.2008.04.029. Epub 2008 Jun 4.
citation: Serati M, Salvatore S, Siesto G, Cattoni E, Braga A, Sorice P, Cromi A, Ghezzi F, Bolis P. Urinary symptoms and urodynamic findings in women with pelvic organ prolapse: is there a correlation? Results of an artificial neural network analysis. Eur Urol. 2011 Aug;60(2):253-60. doi: 10.1016/j.eururo.2011.03.010. Epub 2011 Mar 21.
citation: Grunebaum A, Chervenak J, Pollet SL, Katz A, Chervenak FA. The exciting potential for ChatGPT in obstetrics and gynecology. Am J Obstet Gynecol. 2023 Jun;228(6):696-705. doi: 10.1016/j.ajog.2023.03.009. Epub 2023 Mar 15.
citation: Johnson CM, Bradley CS, Kenne KA, Rabice S, Takacs E, Vollstedt A, Kowalski JT. Evaluation of ChatGPT for Pelvic Floor Surgery Counseling. Urogynecology (Phila). 2024 Mar 1;30(3):245-250. doi: 10.1097/SPV.0000000000001459.
citation: Acker A, Senapati S, Dokras A. Barriers to access: findings from an implementation study of an artificial intelligence-augmented 2-way chatbot for fertility care. Fertil Steril. 2023 Jul;120(1):199-201. doi: 10.1016/j.fertnstert.2023.04.016. Epub 2023 Apr 20. No abstract available.