The Friendly Health Issue Network to Support Computer-Assisted Education for Clinical Reasoning in Multimorbidity Patients

Clinical reasoning in multimorbidity conditions asks for the ability to anticipate the possible evolutions of the overall health state of a patient and to identify the interactions among the concurrent health issues and their treatments. The HIN (Health Issue Network) approach, as Petri Nets-based formal language, is introduced as capable of providing a novel perspective to facilitate the acquisition of such competencies, graphically representing the network among a set of health issues (HIs) that affect a person throughout their life, and describing how HIs evolve over time. The need to provide a more immediate user-oriented interface has led to the development of f-HIN (friendly HIN), a lighter version based on the same mathematical properties as HIN, from which stems in turn the f-HINe (friendly HIN extracted) model, used to represent networks related to either real patients’ clinical experiences extracted from electronic health records, or from teacher-designed realistic clinical histories. Such models have also been designed to be embedded in a software learning environment that allows drawing a f-HIN diagram, checking for its format correctness, as well as designing clinical exercises for the learners, including their computer-assisted assessment. The present paper aims at introducing and discussing the f-HIN/f-HINe models and their educational use. It also introduces the main features of the software learning environment it was built upon, pointing out its importance to: (i) help medical teachers in designing and representing the context of a learning outcome; and (ii) handle the complex history of a multimorbidity patient, to be conveyed in Case-Based Learning (CBL) exercises

Quality of primary care for children: Autism Spectrum Disorders and Immunization indicators in the EU MOCHA project

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The Invisibility of Children in Data Systems

In order to assess the state of health of Europe’s children, or to appraise the systems and models of healthcare delivery, data about children are essential, with as much precision and accuracy as possible by small group characteristic. Unfortunately, the experience of the Models of Child Health Appraised (MOCHA) project and its scientists shows that this ideal is seldom met, and thus the accuracy of appraisal or planning work is compromised. In the project, we explored the data collected on children by a number of databases used in Europe and globally, to find that although the four quinquennial age bands are common, it is impossible to represent children aged 0–17 years as a legally defined group in statistical analysis. Adolescents, in particular, are the most invisible age group despite this being a time of life when they are rapidly changing and facing increasing challenges. In terms of measurement and monitoring, there is little progress from work of nearly two decades ago that recommended an information system, and no focus on the creation of a policy and ethical framework to allow collaborative analysis of the rich anonymised databases that hold real-world people-based data. In respect of data systems and surveillance, nearly all systems in European society pay lip service to the importance of children, but do not accommodate them in a practical and statistical sense

Heart rate estimation from ballistocardiogram signals processing via low-cost telemedicine architectures: a comparative performance evaluation

Medical devices (MDs) have been designed for monitoring the parameters of patients in many sectors. Nonetheless, despite being high-performing and reliable, they often turn out to be expensive and intrusive. In addition, MDs are almost exclusively used in controlled, hospital-based environments. Paving a path of technological innovation in the clinical field, a very active line of research is currently dealing with the possibility to rely on non-medical-graded low-cost devices, to develop unattended telemedicine (TM) solutions aimed at non-invasively gathering data, signals, and images. In this article, a TM solution is proposed for monitoring the heart rate (HR) of patients during sleep. A remote patient monitoring system (RPMS) featuring a smart belt equipped with pressure sensors for ballistocardiogram (BCG) signals sampling was deployed. A field trial was then conducted over a 2-month period on 24 volunteers, who also agreed to wear a finger pulse oximeter capable of producing a photoplethysmography (PPG) signal as the gold standard, to examine the feasibility of the solution via the estimation of HR values from the collected BCG signals. For this purpose, two of the highest-performing approaches for HR estimation from BCG signals, one algorithmic and the other based on a convolutional neural network (CNN), were retrieved from the literature and updated for a TM-related use case. Finally, HR estimation performances were assessed in terms of patient-wise mean absolute error (MAE). Results retrieved from the literature (controlled environment) outperformed those achieved in the experimentation (TM environment) by 29% (MAE = 4.24 vs. 5.46, algorithmic approach) and 52% (MAE = 2.32 vs. 3.54, CNN-based approach), respectively. Nonetheless, a low packet loss ratio, restrained elaboration time of the collected biomedical big data, low-cost deployment, and positive feedback from the users, demonstrate the robustness, reliability, and applicability of the proposed TM solution. In light of this, further steps will be planned to fulfill new targets, such as evaluation of respiratory rate (RR), and pattern assessment of the movement of the participants overnight

Modelling collaboration of primary and secondary care for children with complex care needs: long-term ventilation as an example.

Children dependent on long-term ventilation need the planning, provision and monitoring of complex services generally provided at home by professionals belonging to different care settings. The collaboration among professionals improves the efficiency and the continuity of care especially when treating children with complex care needs. In this paper, the Unified Modelling Language (UML) has been adopted to detect the variety of the patterns of collaboration as well as to represent and compare the different processes of care across the 30 EU/EEA countries of the MOCHA project.Conclusion: Half of the analysed countries have a multidisciplinary team with different degrees of team composition, influencing organisational features such as the development of the personalised plan as well as the provision of preventive and curative services. This approach provides indications on the efficiency in performing and organising the delivery of care in terms of family involvement, interactions among professionals and availability of ICT. What is known: • Children with CCNs require a coordination of efforts before and after discharge in a continuum of care delivery dependent on the level of integrated care solutions adopted at country level. What is new: •The adoption of a business process method contributes to perform a cross-country analysis highlighting the variability of team composition and its influence on the delivery of care. • This approach provides indications on the efficiency in performing and organising the delivery of care in terms of family involvement, interactions among professionals and availability of ICT

Comparative evaluation of vital parameters in Hares and Rabbits in response to trans-nasal heavy sedation

In wild animals, such as hares, injectable anesthesia is often necessary to conduct clinical as well as management manipulations1. Trans-nasal (TN) administration of some analgesics, sedatives, and anesthetics is an effective and rapid route in rabbits2. Aim of this study was to compare the effects over some physiological variables of TN administration of a mixture of dexmedetomidine (D), midazolam (M) and butorphanol (B) in rabbits and hares. A mixture of 0.1 mg/kg D, 0.4 mg/kg B and 2 mg/kg M was administered TN to 15 healthy NZW Rabbits (Oryctolagus cuniculus) and 15 adult captive hares (Lepus europaeus) through a feeding tube. Physiological parameters were continuously monitored for 45 min and they included heart and respiratory rate (Hr, Rr), rectal temperature (T°C), pulse-oximetry (SPO2), capnometry (EtCO2), systolic, diastolic and mean arterial pressure (SAP, DAP, MAP). Since such parameters resulted significantly different between the two species before sedation (data not shown), absolute values were transformed in scores (i.e., the difference between the second and the first time point, and so on). Data were processed by using a MANOVA for repeated measures. Significance was set at P???0.05. The trend of all the variables studied resulted very similar over time and no significant differences were recorded, but for Hr that significantly decreased in hares at T40 (P=0.0237) and T45 (P<0.0001). The onset time resulted rapid in all subjects (.... sec/min) and no side effects nor mortality was recorded in this experimental group. TN DBM delivery in awake rabbits and hares was easily achieved. TN administration of the DBM mixture proved to be an effective and safe technique in lagomorphs allowing diagnostic or minor surgical procedures and might be proposed as a simple tool for chemical restraint in these species. The choose of scoring absolute data for statistic analysis allowed the comparison between two species, which demonstrated different basal physiological parameters, but did not have a different response to the DBM treatment. 1 Vesce G. et al. 2011 VII International Symposium on Wild Fauna Prooc., Edinburgh, UK, p. 291. 2 West G. et al. Zoo Animal & Wildlife: Immobilization and Anesthesia, Blackwell Publ 200

A night at the opera: A conceptual framework for an integrated distributed sensor network-based system to figure out safety protocols for animals under risk of fire †

Large scale wildfire events that occurred around the world involved a massive loss of animal lives, with a consequent economic impact on agricultural holdings and damages to ecosystems. Preparing animals for a wildfire evacuation requires an extra level of planning, preparedness and coordination, which is missing in the current practice. This paper describes a conceptual framework of an ICT system implemented to support the activities of the Regional Veterinary referral Center for non-epidemic emergencies (CeRVEnE) in the Campania Region for the twofold objectives. On the one hand, it realizes the monitoring of the wooded areas under risk of fire in the so-called “Mount Vesuvius’ red zone”. On the other hand, it determines the Optimal Evacuation Route for Animals (OPERA) in case of fire, for each of the reported animal species living in the mentioned red zone. The main innovation of the proposed system lies in its software architecture that aims at integrating a Distributed Sensor Network (DSN), an ad-hoc software to generate timely simulations for fire risk modeling, and a GIS (Geographic Information System) for both the activities of web mapping and OPERA definition. This paper shows some effective preliminary results of the system implementation. The importance of the system mainly lies in its accordance with the so-called “Foresight approach” perspective, that provides models and tools to guarantee the prevention of systematic failure in disaster risk management, and becomes moreover critical in the case of Mount Vesuvius, which hosts a unique combination of both animal and anthropic elements within a delicate natural ecosystem