Clinical Research Directory

Artificial Intelligence in Surgical Practice in Sudan: National Survey of Doctors

This is a national survey of doctors in Sudan who are involved in providing surgical care. The aim is to understand their awareness, experiences, and opinions about using artificial intelligence (AI) in surgery. The survey includes all cadres-house officers, medical officers, registrars, residents, specialists, consultants, and general practitioners who perform surgical procedures-working in public, private, NGO, and military hospitals across Sudan. Participants are asked about their familiarity with AI, barriers to its use (such as poor infrastructure, lack of training, or cost), interest in training, and possible uses in Sudan's health system, especially in conflict-affected areas. The study does not test any AI tools but collects information to help design future AI solutions that work offline, in low-bandwidth conditions, and meet the needs of surgeons and surgical teams in Sudan.

TELENURSING IN THE IMMEDIATE PREOPERATIVE PERIOD OF ELECTIVE SURGERIES

Introduction: Telenursing encompasses Nursing Consultation, Interconsultation, Consulting, Monitoring, Health Education and Reception of Spontaneous Demand mediated by Information and Communication Technology. Objective: To perform a cost-effectiveness analysis of telenursing in the immediate preoperative period of adult patients undergoing elective surgeries in a university hospital of the SUS. Materials and method: Cost-effectiveness analysis nested in a clinical trial or empirical economic analysis of the piggyback evaluation type. Divided into 2 phases: a) Experimental research - randomized clinical trial to be carried out in a university hospital located in Rio de Janeiro and part of the SUS, with two parallel groups - intervention and control - with 1:1 allocation. The inclusion criteria will be adult patients, of both sexes, in the immediate preoperative period who are admitted on the day of elective surgery from their home. Patients who are hospitalized, patients in ophthalmology and obstetrics specialties, and those who will undergo examinations in the surgical center will be excluded. The sample size calculation was performed with a 95% confidence level and a sample loss of 5%, totaling 352 patients. The sampling will be random. Randomization and allocation concealment will be performed by the independent researcher. Patients in the GI will receive telenursing on the day before surgery with an anamnesis script for telenursing by the main researcher. On the day of surgery, all patients on the surgical map who came from their residence will be directed to the nursing assessment room where the auxiliary researcher will apply the in-person anamnesis script. The data will be processed by two independent researchers in an electronic spreadsheet and will be analyzed using descriptive and inferential statistics. The research will respect all legal and ethical frameworks necessary for its implementation; b) Prospective analysis of complete economic evaluation - in the piggyback evaluation modality - of the cost-effectiveness type. The effectiveness of telenursing will be verified by the outcome of surgical cancellation. A decision tree model will be used with a view to analyzing the SUS user at the local level (microcosting). The time horizon will be two days. The cost-effectiveness threshold will be 1 GDP per capita and the data analysis will include deterministic and probabilistic sensitivity. Expected results: It is expected to prove that telenursing can be a safe and efficient method for guiding patients before surgery, generating greater patient satisfaction, increasing access to information about health care for users through remote communication with nurses, reducing the waiting list by reducing surgical cancellations and possible incorporation of telenursing as a consolidated practice in the university hospital studied.