Anesthesia, Artificial Intelligence, Patient Education, Preoperative Care
Conditions
Brief summary
Patients are waiting for surgery longer than ever before. While hospitals are trying to get patients access to surgery as quickly as possible, a shortage of anesthesia doctors (called anesthesiologists) prevents this. Every surgery needs an anesthesiologist, but anesthesiologists also assess patients beforehand to ensure they can safely undergo surgery and help patients understand what to expect and the risks involved. Ensuring that patients move through surgery as safely and efficiently as possible requires that the limited number of anesthesiologists in Canada work as efficiently as possible. Technology like Artificial Intelligence (AI), in programs such as ChatGPT, might assist by answering common questions patients have, allowing anesthesiologists to focus their limited time on addressing complex and personalized issues for each patient. However, studies conducted so far on how well AI can answer questions about anesthesia and surgery have been poorly designed and have not included patients as members of the research team. This study will determine whether AI can answer patients' questions before surgery as effectively as both patients and expert anesthesiologists would expect, which could be beneficial to patients and the healthcare system.
Interventions
None listed
Sponsors
Ottawa Hospital Research Institute
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
Patients * 1\. Age \> 18 years 2. Elective non-cardiac surgery 3. In-person preoperative anesthesiology consultation 4. Ability to participate and provide informed consent independently.
Exclusion criteria
* 1\. Unable to communicate in English or French 2. Nurse consultation only Physicians Inclusion Criteria: Anesthesiology residents or staff providing service at the PAU at TOH
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| knowledge | From the date of the pre-anesthesia consultation until 2 weeks after the consultation, assessed over a period of up to 2 weeks post-consultation | Patients will be blinded to the source of the two responses (GPT-4 and Anesthesiologist). After reading both responses, they will complete a questionnaire that includes an 11-point Likert-scale question for the primary outcome of knowledge: To what extent does the response address the knowledge or information you hoped to gain? (0 = not at all addressed; 10 = fully addressed) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Patient satisfaction | From the date of the pre-anesthesia consultation until 2 weeks after the consultation, assessed over a period of up to 2 weeks post-consultation | Secondary Outcome: Patient satisfaction, Patient satisfaction will be assessed using a likelihood to recommend measurement based on a 11-point Likert scale (Question: Thinking about the response you received to your question, how likely are you to recommend the response's provider to a family member or friend going for a similar surgery? 0-not at all likely; 10-extremely likely). |
Other
| Measure | Time frame | Description |
|---|---|---|
| Tertiary outcomes | From the date of the pre-anesthesia consultation until 2 weeks after the consultation, assessed over a period of up to 2 weeks post-consultation | Three tertiary outcomes will be assessed using an 11-point Likert scale: 1. Health Literacy:Assessed through the prompt: I have sufficient information to make decisions about my surgery. 2. Perceived Empathy:Evaluated with the question: To what extent did you find the response empathetic? 3. Completeness: Measured by the question: To what extent did you find the response complete? |
Countries
Canada
Contacts
Primary ContactArnaud Romeo, Mbadjeu Hondjeu, MD
Backup ContactDaniel McIsaac, MD
Outcome results
None listed