AI-Assisted Skin Assessment for Pressure Injury Prevention in Critical Care Nurses
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorKing Faisal Specialist Hospital & Research Center
About this trial
The goal of this clinical trial is to learn whether an artificial intelligence (AI)-assisted skin assessment tool can improve the accuracy of pressure-injury staging in critical-care nurses. The study also aims to understand whether the AI tool increases nurses' knowledge and confidence in performing skin assessments. The main questions it aims to answer are:
Does AI-assisted assessment improve the accuracy of pressure-injury staging compared with standard visual assessment?
Does the use of AI improve nurses' knowledge and confidence related to skin assessment and pressure-injury staging?
Researchers will compare nurses who use an AI-assisted mobile application with nurses who perform standard manual assessments to see whether the AI tool improves staging accuracy and supports early identification of pressure injuries.
Participants will:
Complete brief questionnaires about their knowledge and confidence before and after training
Perform skin assessments on their assigned ICU patients using either standard methods or the AI tool.
Have their assessments compared with those of a blinded wound-care specialist, who will determine the most accurate staging
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Nurses working within the organisation for at least 6 months
Nurses involved in direct patient care for over 50% of their work time.
Skin assessments and staging for patients at risk for developing pressure injuries (Using the Braden Scoring system).
Adult Patients (18 years and older)
Disqualifiers
Nurses working within the organization for less than 6 months
Nurses involved in direct patient care for less than 50% of their work time
End-of-Life Care or Terminal Illness- patients receiving end-of-life care or those with a terminal diagnosis, where the prevention of pressure injuries may not be a priority and where participation in the study may not align with their care goals.
Severe or active dermatological conditions- patients with active skin conditions such as severe rashes, burns, or other dermatological issues that could interfere with accurate skin assessments by AI or confound the study results.
Trial design
Design model
Parallel
Treatments tested in this trial
ChatGPT Skin Assessment
Other interventionChatGPT Skin Assessment
Treatment groups
90 Participants
are divided into 2 treatment groupsGroup A: Standard AssessmentNo intervention 0 interventions
Group B: ChatGPT-Assisted Skin AssessmenOther 1 intervention
Trial outcomes
Primary outcomes
1
Agreement Between Nurse and Expert Skin Assessment and Pressure Injury Staging Using NPIAP Criteria
The primary outcome explicitly measures agreement between nurse-assigned and expert-assigned pressure injury stages using the National Pressure Injury Advisory Panel (NPIAP) staging criteria, rather than stating a study objective. Agreement will be quantified using Cohen's Kappa statistic, and accuracy will be summarized as the percentage of nurse-assigned stages that exactly match expert-assigned stages. Agreement analyses will be conducted separately for manual nurse assessments and AI-assisted nurse assessments, allowing clear and reportable comparison between study groups. Agreement outcomes will be summarized across individual assessment domains, including erythema, discoloration, edema, temperature, and overall pressure injury staging, using quantitative agreement metrics. The primary outcome will be assessed from Day 1 through 6 months.
Time frame
Day 1 through 6 monthsSecondary outcomes
1
Knowledge- Change From Baseline in Nurse Knowledge Score on the Pressure Ulcer Prevention Knowledge Assessment Instrument (PUPKAI)
Nurse knowledge related to pressure injury prevention and staging will be measured using the Pressure Ulcer Prevention Knowledge Assessment Instrument (PUPKAI), a validated 26-item multiple-choice questionnaire. Each correct response will be scored as one point, and item scores will be summed to generate a total knowledge score ranging from 0 to 26, with higher scores indicating greater knowledge. Total PUPKAI scores will be calculated at two prespecified time points: Day 1 (baseline, prior to the intervention) and Day 1 (immediately post-intervention). The outcome will be reported as change from baseline in total PUPKAI score, calculated as the post-intervention score minus the baseline score. For statistical analysis, descriptive statistics will be used to summarize baseline and post-intervention scores. Within-group changes in PUPKAI scores will be analyzed using paired statistical tests (paired t-test or Wilcoxon signed-rank test, depending on data distribution).
Time frame
Day 1 (Baseline) and Day 1 (Immediately Post-intervention)2
Change From Baseline in Nurse Confidence Score on the Skin Assessment Confidence Scale (SACS)
Nurse confidence in skin assessment and pressure injury staging will be measured using the Skin Assessment Confidence Scale (SACS), a 10-item Likert-scale instrument. Each item is scored on a 5-point scale, and item scores are summed to generate a total confidence score ranging from 10 to 50, with higher scores indicating greater confidence in performing skin assessments and applying pressure injury staging criteria. Total SACS scores will be calculated at two prespecified time points: Day 1 (baseline, prior to the intervention) and Day 1 (immediately post-intervention). The outcome will be reported as change from baseline in total SACS score, calculated as the post-intervention score minus the baseline score. For statistical analysis, descriptive statistics will be used to summarize baseline and post-intervention confidence scores. Within-group changes in SACS scores will be analyzed using paired statistical tests (paired t-test or Wilcoxon signed-rank test, depending on data distr
Time frame
Day 1 (Baseline) and Day 1 (Immediately Post-intervention)Sponsors and contacts
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Source ClinicalTrials.gov