The length of hospital stay for patients with physical illnesses is longer for those with mental health comorbidity, particularly in the presence of severe physical multimorbidity. Integrating psychosocial risk screening at hospital admission, with a subsequent care pathway, could address psychosomatic and social care needs early and reduce length of stay. However, implementation may be hindered by organisational factors such as increased staff workload and timely integration into existing processes. In addition, patient factors such as low acceptance of screening and follow-up may affect uptake. This pilot study aims to assess the feasibility of implementing this integrated approach to screening and follow-up in preparation for a confirmatory trial.

The present study is a single centre, randomised feasibility study conducted on a pilot ward. Patients will be enrolled and assigned to the intervention or the control group. Only the intervention group will receive tablet-based psychosocial risk screening conducted by ward physicians or medical students in their practical year. If the psychosomatic screening is positive and the patient agrees, he or she is referred to the psychosomatic consultation service. If the social service screening is positive, the patient will be seen by a social worker. The main objective of this study is to assess the feasibility of conducting a full-sized confirmatory trial. An informed consent rate of 30% of eligible patients is set as the feasibility criterion. A study period of 4 months is planned for the feasibility study. The feasibility study will be analysed using descriptive statistics.

The study protocol was approved by the Ethics Committee of the Medical Faculty of Heidelberg University (S-301/2024) on 24 May 2024. The results of this feasibility study will be published in a peer-reviewed journal.

NCT06651164.

Visual Patient Predictive (VPP) is an AI-based extension of the Visual Patient Avatar (VPA) that integrates deep learning models to predict upcoming vital sign deviations and display them as dashed visual elements. By explicitly showing anticipated changes, the system aims to support level 3 situation awareness—the projection of future patient states. This multicentre simulation study will evaluate whether predictive algorithms and visualisations integrated into the VPA (resulting in VPP) improve clinicians’ ability to anticipate critical vital sign changes compared with conventional number-based and waveform-based monitoring and examine its effects on decision-making, confidence, workload and user acceptance.

This investigator-initiated, randomised, within-subjects crossover, computer-based simulation trial will be conducted at five academic centres in Switzerland, Germany and the United States. Medical professionals from anaesthesiology departments will complete scenario-based prediction tasks using both VPP (as the index test) and conventional monitoring (as the reference standard) in randomised order, with the same participant evaluating both modalities and the identical underlying clinical scenario used in each condition, following video-based training and a learnability test. The primary outcome is recall (true positive rate) of vital sign deviation predictions. Secondary outcomes include average lead time, precision, prediction confidence, number and correctness of proposed interventions, perceived workload (NASA-TLX) and qualitative usability feedback. Quantitative data will be analysed using a logistic generalised linear mixed model with random intercepts for centre and participant, and a random slope for the intervention effect. Qualitative interviews will undergo thematic analysis.

The leading ethics committee (Zurich, Switzerland; BASEC-Req-2023–00465) reviewed and approved the study protocol. Ethics committees at the other participating centres have obtained their respective approvals or waivers. Bonn: 2025–144-BO, Boston: 2025P000501, Heidelberg: S-376/2025, Munich: 2025–357 W-CB. As this simulation study involves only healthcare professionals performing prediction tasks based on simulated vital sign scenarios—without collection of patient data or any medically relevant personal data—it does not constitute human subjects research under applicable regulations. Study results will be disseminated through peer-reviewed publications and presentations at scientific conferences.