Dyspnoea is an existentially burdensome symptom in patients with advanced and progressive diseases such as cancer, chronic obstructive pulmonary disease (COPD) and advanced heart failure. Recent studies have highlighted that symptomatic treatment of dyspnoea is often ineffective and may depend on the underlying disease. Immersive virtual reality (IVR) has emerged as a ‘digital therapeutic’ for conditions such as pain, anxiety, and dyspnoea. Brain functional MRI (fMRI) offers the opportunity to identify distinct patterns of dyspnoea. Current findings are mainly limited to healthy volunteers, but clinical data from patients with life-limiting conditions are needed. The aim of this study is to assess the feasibility of identifying dyspnoea patterns in different life-limiting conditions using fMRI and IVR.

This is an observational monocentric feasibility study, conducted in a tertiary university centre. Healthy volunteers and patients diagnosed with advanced cancer, COPD, or heart failure and suffering from persistent dyspnoea will undergo an fMRI of the brain using IVR. The primary outcome of feasibility will be evaluated using descriptive statistics. Secondary outcomes include analysis of fMRI patterns of dyspnoea across populations, patient-reported burden of participation, and correlation between dyspnoea and psychological symptoms. These preliminary data will help determine the sample size required for a future study evaluating differences in dyspnoea patterns. Exploratory comparison between the characteristics of all four groups will be assessed with Fisher’s test (for proportions) and either independent Student’s t-test or Mann-Whitney test, depending on distribution. Correlations between variables will be tested using the Pearson’s correlation coefficient. Statistical analysis will be performed using STATA.

This study protocol received ethical approval on 23 April 2025 from the Commission cantonale d’éthique de la recherche in the Canton of Geneva, Switzerland. The identification number is 2024-02289. Submission to peer-reviewed journals and presentation in international congresses for the dissemination of the study findings are planned.

Clinical Trials number is NCT07319039; Pre-results.

Healthcare logistics involves the coordination of resources, services and infrastructure to ensure timely and efficient care delivery. Process mining offers data-driven insights into logistical workflows such as patient transport, inventory management and scheduling. This systematic review aims to synthesise evidence on the application of process mining in healthcare logistics, focusing on its impact on operational efficiency, resource utilisation and service delivery.

A systematic search will be conducted in MEDLINE, Embase, Google Scholar, Web of Science and ABI/Inform for studies published from 1999 onward. Eligible studies will include observational studies, case reports, conference papers and meta-analyses focusing on process mining applications to logistical processes in healthcare settings. Studies screening, data extraction and methodological quality assessment will be conducted using the Mixed Methods Appraisal Tool. Data will be extracted on key dimensions and performance indicators and will be presented in a structured format. A narrative synthesis will be conducted, and findings will be categorised and thematically analysed where appropriate. Primary outcomes include improvements in logistical efficiency, traceability, resource utilisation and sustainability. Secondary outcomes include implementation challenges, data integration issues and limitations in applying process mining techniques to logistical workflows.

The results of the systematic review will be disseminated via publication in a peer-reviewed journal and presented at a relevant conference. The data we will use do not include individual patient data, so ethical approval is not required.

CRD420251164812.