Netherlands Federation of University Medical Centres

Co-creation has emerged as a transformative approach to meaningful collaboration among students, teachers, and other key stakeholders. Although co-creation aims to integrate all stakeholders’ diverse perspectives and foster engagement, motivation, and ownership among them, some practical challenges can impact its implementation. The operationalization of co-creation needs a feasible, step-by-step plan to address interpersonal, practical, and institutional challenges, which can undermine co-creation. This guide examines how Artificial Intelligence (AI) can be leveraged across all phases of the co-creation cycle—preparation, conduction, and follow-up. It offers innovative insights into the intentional deployment of AI tools to enhance collaboration while preserving the relational essence of co-creation. We describe how AI can facilitate recruitment of diverse participants, design and planning of co-creation activities, brainstorming, shared decision-making, process evaluation, dissemination of outcomes, and integration of co-created outcomes into the curricula. This guide applies the Substitution, Augmentation, Modification, Redefinition (SAMR) model and the Technology-Organization-Environment (TOE) framework to theoretically examine how AI can enhance or fundamentally reshape co-creation. It also underscores essential ethical considerations for integrating AI into co-creation. After reading this guide with comprehensive and practical guidelines, educators can effectively integrate AI into co-creation initiatives, aiming to enhance both the processes and outcomes of co-creation.

Youth represent un-tapped potential within the fight against antimicrobial resistance (AMR). This commentary describes the co-creation process of the Youth Manifesto on AMR which seeks to generate consensus on how equitable engagement of youth can be realised, despite policy, power and funding challenges. The Youth Manifesto on antimicrobial resistance (AMR) provides a blueprint for how the change-making potential of youth can be harnessed to promote equitable and sustainable action on AMR from a global, One Health perspective.

ObjectivesValue-based healthcare (VBHC) strives to improve the healthcare system by focusing on value of care, that is, patient relevant outcomes relative to the costs for achieving these outcomes. Within VBHC, patient participation is crucial to identify patient relevant outcomes and value improvement potential. However, patient participation in VBHC initiatives remains limited. Therefore, we aimed to improve patient participation within VBHC teams with the ultimate aim to develop a practical guide for patient participation in VBHC.DesignAn action research study.SettingThis study was conducted in seven collaborating Dutch hospitals from March 2023 to November 2024.ParticipantsSeven VBHC teams were selected to participate in the cyclical action research steps, that is, orientation, planning, implementation, and evaluation, in which patient participation was implemented or improved. These included the following patient groups: prostate cancer, vulnerable elderly, breast cancer, diabetes, maternity care, colorectal cancer and chronic kidney disease.OutcomesBoth qualitative and quantitative data were collected. Qualitative data included observations and minutes of meetings with the intervention teams. Quantitative data included responses to the Public and Patient Engagement Evaluation Tool (PPEET) by multiple members of the intervention (n=7) and control teams (n=94) at three time points (T1=6 months, T2=12 months, T3=end of study). Qualitative data were thematically analysed and quantitative data were analysed descriptively. Finally, the data were triangulated to create an overview of lessons learnt in improving patient participation.ResultsPatient participation goals varied across teams, leading to diverse actions, such as establishing a diabetes patient panel and distributing questionnaires to patients with colorectal cancer. PPEET results show that 71% of intervention team members reported that patient participation had an impact on the team’s outcomes compared with 44% in control teams (T3). Furthermore, 80% of the intervention team members initially wanted training in patient participation (T1), which dropped to 29% at T3. Overall, 22 lessons in improving patient participation in multidisciplinary project teams were identified and compiled into a practical guide.ConclusionsThe action research process improved the process and impact of patient participation in the intervention teams. Furthermore, the results indicate that the action research process enhanced the team members’ knowledge and skills on patient participation. The practical guide developed in this study can be used to support implementation of patient participation in VBHC.

PurposeTo explore travel burden in patients with self-reported curable and incurable cancer.MethodA 2-day flash mob study was conducted in March 2023 among patients visiting medical oncology departments in 65 Dutch hospitals. Disease status was self-reported. Patients completed a questionnaire on travel time (one-way), travel problems, and willingness to travel. Descriptive analyses and logistic regression analyses were used to assess travel burden and its associated factors.ResultsIn total, 991 patients with curable and 1959 with incurable cancer were included. Patients with curable cancer more often reported daily or weekly hospital visits (63% vs. 22%, p < 0.001) and a travel time of less than 30 min (78% vs. 73%, p = 0.005). Almost one-third of patients with curable (28%) and incurable cancer (29%) experienced some travel problems. Patients with worse physical functioning and longer travel times were more likely to experience travel problems. Disease status was not associated with experiencing travel problems or the willingness to travel for oncological care. Instead, willingness to travel was associated with patients’ level of education, physical functioning, and tumour type.ConclusionBeing diagnosed with self-reported curable or incurable cancer was not associated with experiencing travel problems or the willingness to travel for oncological care. Experiencing travel problems was associated with physical functioning and travel time, and the willingness to travel was associated with level of education, physical functioning, and tumour type. To ensure accessible and patient-centred care, physicians should be aware of these potential barriers and aim to provide well-coordinated, personalised care close to home.

Abstract BackgroundThe miniECG, a smartphone-sized, multi-lead device, offers a simple and fast alternative to the 12-lead ECG. We aimed to demonstrate the potential of the miniECG to record and detect amplitude and intraventricular conduction ECG abnormalities via interpretable models.MethodsA miniECG was captured for patients undergoing a conventional 12-lead ECG in the University Medical Centre Utrecht. MiniECGs of patients with normal ECGs (controls), amplitude abnormalities (low QRS voltage (Microvoltage) and left ventricular hypertrophy (LVH)), conduction abnormalities (left or right bundle branch blocks (LBBB, RBBB), left anterior fascicular block (LAFB), bifascicular block (BfB)) were selected. Standard ECG-features were used as input for decision trees (DTs) for binary (normal vs abnormal) or multiclass classification, employing 10-fold stratified cross-validation.Results1717 patients were included. For binary classification of conduction abnormalities, the decision tree showed an AUROC of 0.97±0.01 (NPV 0.95±0.03, sensitivity 0.95±0.02). For multiclass classification, AUROCs were 0.95±0.02 (BfB), 0.85±0.03 (LAFB), 0.87±0.05 (LBBB), 0.94±0.04 (RBBB) and 0.93±0.03 (controls). For binary classification of amplitude abnormalities, the AUROC was 0.76±0.04 (NPV 0.83± 0.05, sensitivity 0.84±0.06). For multiclass classification, the AUROCs were 0.80 ± 0.06 (LVH), 0.78±0.05 (microvoltage) and 0.76±0.05 (controls).ConclusionThis is the first study to detect ECG abnormalities in amplitude and intraventricular conduction, with a four precordial electrodes set-up. DTs based on miniECG features offer an interpretable detection method with a performance that was comparable to other less interpretable models. Before clinical implementation, further research is necessary to optimize DT-structures and analyze abnormalities beyond the current study.Author SummaryElectrocardiograms (ECGs) are vital for detecting abnormal electrical heart signals, but traditional 12-lead ECGs are often limited to in-hospital settings due to complexity. Our study introduces the miniECG, a smartphone-size device with four electrodes to be placed on the chest, that records eight leads. We evaluated its ability to detect amplitude and conduction cardiac abnormalities using interpretable machine learning models. In a hospital-based sample of over 1,700 patients, we trained decision trees (DTs) on standard ECG features to classify abnormalities. The models demonstrated accurate diagnostic potential, particularly for conduction abnormalities, while maintaining transparency and clinical interpretability. Further optimization is needed, but this tool could enable broader ECG acquisition and easier detection of cardiac abnormalities.