Coordinating a large-scale digital health project requires a unique mix of scientific leadership, administrative skill, and human sensitivity. Drawing from our experience leading CAPABLE, a European Horizon 2020 project aimed at improving the quality of life of cancer patients through AI and telemedicine, we present ten practical rules for navigating the complex landscape of multi-partner biomedical research. These rules address challenges such as building balanced consortia, managing timelines and regulatory requirements, ensuring cultural alignment, and promoting long-term impact through dissemination and exploitation. The paper specifically addresses international research projects at the intersection of healthcare and IT and their peculiar challenges, typically connected to the interplay of different actors such as academics, healthcare personnel, and industry partners located in different countries, each from diverse backgrounds and different working practices. Our goal is to provide researchers and project coordinators with concrete guidance to increase the likelihood of success in future large digital health initiatives.

Inflammatory Bowel Disease (IBD) is a term that includes two chronic conditions characterized by inflammation of the gastrointestinal tract, i.e., Ulcerative Colitis and Crohn’s Disease. IBD can be associated to symptoms that significantly reduce quality of life and can lead to serious complications, therefore proper disease monitoring and treatment is necessary. To this end, Telemedicine has been identified as a useful tool, since it can ease the patients’ burden on the management of nutrition and pharmacological treatment, and can improve the connection with the physicians. In this paper, we present NutriA, a new responsive web application for the management of IBD patients in Italy, created to assist patients with diet, medications and symptoms monitoring, optimizing the follow-ups frequency and providing direct assistance by the doctors. Besides being useful to improve the patients’ well-being, NutriA is also designed to be used in a new clinical study on the effects of malnutrition on IBD treatment.

Abstract Statistics on medical errors and their consequences has astonished, during the previous years, both healthcare professionals and ordinary people. Mass‐media are becoming more and more sensitive to medical malpractices. This paper elaborates on the well‐known resistance of the medical world to disclose actions and processes that could have caused some damages; it illustrates the possible causes of medical errors and, for some of them, it suggests solutions based on information and communication technology. In particular, careflow management systems and process mining techniques are proposed as a means to improve the healthcare delivery process: the former by facilitating task assignments and resource management, the latter by discovering not only individuals' errors, but also the chains of responsibilities concurring to produce errors in a complex patient's pathway. Both supervised and unsupervised process mining will be addressed. The former compares real processes with a known process model (e.g., a clinical practice guideline or a medical protocol), whereas the latter mines processes from raw data, without imposing any model. The potentiality of these techniques is illustrated by means of examples from stroke patient management. Copyright © 2010 John Wiley & Sons, Ltd.

Recent studies suggest that the quality of recovery after a stroke can be increased by early and more intensive rehabilitation. Portable unobtrusive devices are promising candidates for the realization of stroke-rehabilitation systems that complement care in the post-acute rehabilitation phase, both in the clinic and at home. The proposed system allows patients to increase the amount of motor exercise they can perform in autonomy, providing them with a real-time feedback based on wearable sensors embedded in the garment's tissue across the upper limb and trunk. A dynamic time warping algorithm allows for the recognition of correct and incorrect motor exercises. After the feedback phase, data are stored in a central location for review and statistics. Workstations can be installed either at home or at the hospital to support patients, independent of their location. The performance of the system on healthy subjects was quantified for seven types of motor exercises for upper limb's rehabilitation. Finally, we present the preliminary results of a pilot clinical study to test the system's acceptability and usability by post-stroke patients, and physicians in a clinical setting.

OBJECTIVES: Many groups are developing computer-interpretable clinical guidelines (CIGs) for use during clinical encounters. CIGs use "Task-Network Models" for representation but differ in their approaches to addressing particular modeling challenges. We have studied similarities and differences between CIGs in order to identify issues that must be resolved before a consensus on a set of common components can be developed. DESIGN: We compared six models: Asbru, EON, GLIF, GUIDE, PRODIGY, and PROforma. Collaborators from groups that created these models represented, in their own formalisms, portions of two guidelines: American College of Chest Physicians cough guidelines [correction] and the Sixth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. MEASUREMENTS: We compared the models according to eight components that capture the structure of CIGs. The components enable modelers to encode guidelines as plans that organize decision and action tasks in networks. They also enable the encoded guidelines to be linked with patient data-a key requirement for enabling patient-specific decision support. RESULTS: We found consensus on many components, including plan organization, expression language, conceptual medical record model, medical concept model, and data abstractions. Differences were most apparent in underlying decision models, goal representation, use of scenarios, and structured medical actions. CONCLUSION: We identified guideline components that the CIG community could adopt as standards. Some of the participants are pursuing standardization of these components under the auspices of HL7.

The authors describe GAMEES II (Graphical Modeling Environment for Expert Systems II), a computer system built to manage arrays of Bayesian belief networks (BBNs). With regard to biomedical applications, the system makes it possible to represent probabilistic knowledge both for the individual patient and for population, enlarging the class of problems actually represented through BBNs. In addition, mathematical models can be represented through the BBN formalism. These characteristics were exploited to perform model-based patient monitoring and population pharmacokinetic/pharmacodynamic studies. BBNs are built within GAMEES II through a graphical interface which is provided with some statistical knowledge, in order to facilitate the construction of sound statistical models. Probabilistic inference is performed by stochastic simulation algorithms that do not give rise to computational problems when dealing with complex networks.>