NCT07438314

Artificial Intelligence-Based Educational Guide

Effectiveness of Artificial Intelligence-Based Educational Guide to Prevent Surgical Site Infection Among Women Delivering Via Caesarean Section

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 300 (actual)
• Sponsor: Mansoura University · Academic / Other
• Sex: Female
• Age: 18 Years
• Healthy volunteers: Not accepted

Summary

The study aimed to evaluate the effectiveness of an artificial intelligence-based educational guide to prevent surgical site infection among women delivering via cesarean section. Research hypotheses: H0: An artificial intelligence-based educational guide will not have any effect on reducing the rate of surgical site infection among women delivering via caesarean section. H1: An artificial intelligence-based educational guide will have a significant positive effect on reducing the rate of surgical site infection among women delivering via cesarean section. A purposive sample of 300 CS delivered women was divided randomly by using computer-generated randomization. into a control and intervention group, 150 women each. The control group received standard care. The intervention group received standard care plus the Artificial Intelligence guide * After discharge, the researcher contacts study subjects every day by WhatsApp and phone call for any questions and to remind them of the upcoming follow-up visit. * Women were asked to photograph the incision site and send it via WhatsApp using an end-to-end encrypted messaging platform to evaluate the wound condition. All photos were deleted immediately after completing the study for women's privacy. * At the 10th postoperative day (±3 days), a follow-up was performed in the Outpatient Clinic because the majority of SSIs developed between POD5 and POD10, and due to the importance of timely identification and referral of SSIs. * According to the study protocol, all women were followed until 30 days after CS. Follow-up was performed in the outpatient clinic, and post-CS SSI screening questions were asked, a physical examination of the patient and determined whether the patient had an SSI as per the Centers for Disease Control and Prevention definition.

Detailed description

Surgical site infections (SSIs) remain a significant concern in obstetric care, particularly following cesarean sections (CS), which are among the most frequently performed surgical procedures worldwide. SSIs not only prolong hospital stays but also increase healthcare costs and contribute to maternal morbidity. Emerging technologies, particularly artificial intelligence (AI), offer promising avenues for enhancing patient education and infection prevention strategies. Recent research demonstrated the potential of AI in healthcare education and infection control. A recent study found that AI-based educational programs significantly improved patients' knowledge and adherence to infection prevention protocols, leading to a 50% reduction in SSI rates post-cesarean section. Many women, particularly those in rural or underserved communities, have limited access to healthcare professionals and postoperative follow-up care. AI-based educational tools, which can be delivered via mobile applications, SMS alerts, or digital platforms, have the potential to overcome geographical and economic barriers. This study supports the scalability and accessibility of AI-driven health education, particularly for vulnerable populations who may otherwise lack essential postoperative guidance

Conditions

• Surgical Site Infection

Interventions

Type	Name	Description
OTHER	Artificial Intelligence-Based educational guide	The artifactual intelligence-based educational guide regarding cesarean section wound care provided for women after delivery and followed through with Daily educational messages, interactive dialogue, Reminders and alerts, Automated symptom checklists, and Photo-based wound monitoring

Timeline

• Start date: 2025-02-17
• Primary completion: 2025-10-10
• Completion: 2025-12-16
• First posted: 2026-02-27
• Last updated: 2026-02-27

Locations

1 site across 1 country: Egypt