CARES : Customized Aftercare Report for Evaluated Skin Cancer Patients

Overview

Current clinical practices often provide general verbal advice to low-risk patients, which may not sufficiently address individual concerns or offer actionable steps. Generic information on the internet can be overwhelming or unreliable, leading to confusion and unnecessary follow-up visits. This project introduces a tailored approach by combining evidence-based guidelines with personalized details about the patient's risk profile. The discharge letter bridges the gap between clinical expertise and patient understanding, offering clear, specific, and actionable advice that has been shown to improve health behaviors and outcomes in other contexts . The personalized discharge letters are generated using an AI agent trained on validated letters from the hospital's electronic health record system (KWS). Each letter is reviewed and approved by a physician before being provided to the patient, ensuring both accuracy and clinical relevance.

This study is a prospective, parallel-group, open-label, randomized controlled trial designed to evaluate the impact of a personalized discharge letter-with or without digital visual support -on reassurance, knowledge, and self-management in low-risk skin cancer patients following dermatological screening. Study Arms: Participants will be randomly assigned to one of three groups: * Group A - Standard of Care: Verbal information only. * Group B - Personalized Discharge Letter: Tailored written information based on individual risk profile, skin type and consultation findings. * Group C - Personalized Discharge Letter + digital visual support: Tailored written information plus digital visual support (e.g. annotated images, visual summaries). Scientific Rationale Current discharge practices for low-risk skin cancer patients often rely on general verbal advice, which may not sufficiently address individual concerns or promote long-term self-care. Evidence from other medical domains suggests that personalized communication improves patient understanding, satisfaction, and adherence to follow-up recommendations. This study introduces an AI agent trained on validated discharge letters from the hospital's electronic health record system (KWS). The AI helpt collect information from the electronic health record that is relevant for creating personalized letters that are reviewed by a physician before being provided to the patient. These letters aim to improve understanding of personal skin cancer risk, sun protection, and self-monitoring practices. The addition of visual digital support (IntelliStudio) is hypothesized to further enhance patient engagement and confidence by providing clear, visual explanations of findings and next steps. This design allows for a direct comparison of standard care versus increasingly personalized interventions, enabling the evaluation of both individual and combined effects.