Glycosaminoglycans and contrast agents: The role of hyaluronic acid as MRI contrast enhancer

A comprehensive understanding of the behaviour of Glycosaminoglycans (GAGs) combined with imaging or therapeutic agents can be a key factor for the rational design of drug delivery and diagnostic systems. In this work, physical and thermodynamic phenomena arising from the complex interplay between GAGs and contrast agents for Magnetic Resonance Imaging (MRI) have been explored. Being an excellent candidate for drug delivery and diagnostic systems, Hyaluronic acid (HA) (0.1 to 0.7%w/v) has been chosen as a GAG model, and Gd-DTPA (0.01 to 0.2 mM) as a relevant MRI contrast agent. HA samples crosslinked with divinyl sulfone (DVS) have also been investigated. Water Diffusion and Isothermal Titration Calorimetry studies demonstrated that the interaction between HA and Gd-DTPA can form hydrogen bonds and coordinate water molecules, which plays a leading role in determining both the polymer conformation and the relaxometric properties of the contrast agent. This interaction can be modulated by changing the GAG/contrast agent molar ratio and by acting on the organization of the polymer network. The fine control over the combination of GAGs and imaging agents could represent an enormous advantage in formulating novel multifunctional diagnostic probes paving the way for precision nanomedicine tools

An Innovative Business Model for a Multi-echelon Supply Chain Inventory Management Pattern

Nowadays, companies are experimenting novel organizational solutions to efficiently operate in uncertain and highly dynamic scenarios. As a potential solution, this paper proposes a new business model for a multi-echelon Supply Chain inventory management pattern. Specifically, an inventory model with proactive lateral transshipments was developed and subsequently tested carrying out 288 experiments with the aim of assessing transshipments impact on the performance of a two-echelon Supply Chain. The final goal was to investigate the potential reduction of the overall cost of the enterprise and, conversely, whether this approach could promote significant improvements in the level of service, achievable through a more efficient management of resources. The analyses and simulations indicate the use of large batches and/or low-cost products did not demand the necessity of transshipment events. These preliminary findings could be potentially validated and tested in the future considering more complex networks or multiple products

A Hybrid Analytic Hierarchy Process and Likert Scale Approach for the Quality Assessment of Medical Education Programs

The quality assessment of training courses is of utmost importance in the medical education field to improve the quality of the training. This work proposes a hybrid multicriteria decision-making approach based on two methodologies, a Likert scale (LS) and the analytic hierarchy process (AHP), for the quality assessment of medical education programs. On one hand, the qualitative LS method was adopted to estimate the degree of consensus on specific topics; on the other hand, the quantitative AHP technique was employed to prioritize parameters involved in complex decision-making problems. The approach was validated in a real scenario for evaluating healthcare training activities carried out at the Centre of Biotechnology of the National Hospital A.O.R.N. “A. Cardarelli” of Naples (Italy). The rational combination of the two methodologies proved to be a promising decision-making tool for decision makers to identify those aspects of a medical education program characterized by a lower user satisfaction degree (revealed by the LS) and a higher priority degree (revealed by the AHP), potentially suggesting strategies to increase the quality of the service provided and to reduce the waste of resources. The results show how this hybrid approach can provide decision makers with helpful information to select the most important characteristics of the delivered education program and to possibly improve the weakest ones, thus enhancing the whole quality of the training courses

Implementation and validation of a new method to model voluntary departures from emergency departments

In the literature, several organizational solutions have been proposed for determining the probability of voluntary patient discharge from the emergency department. Here, the issue of self-discharge is analyzed by Markov theory-based modeling, an innovative approach diffusely applied in the healthcare field in recent years. The aim of this work is to propose a new method for calculating the rate of voluntary discharge by defining a generic model to describe the process of first aid using a “behavioral” Markov chain model, a new approach that takes into account the satisfaction of the patient. The proposed model is then implemented in MATLAB and validated with a real case study from the hospital “A. Cardarelli” of Naples. It is found that most of the risk of self-discharge occurs during the wait time before the patient is seen and during the wait time for the final report; usually, once the analysis is requested, the patient, although not very satisfied, is willing to wait longer for the results. The model allows the description of the first aid process from the perspective of the patient. The presented model is generic and can be adapted to each hospital facility by changing only the transition probabilities between states

A six sigma DMAIC methodology as a support tool for health technology assessment of two antibiotics

Health Technology Assessment (HTA) and Six Sigma (SS) have largely proved their reliability in the healthcare context. The former focuses on the assessment of health technologies to be introduced in a healthcare system. The latter deals with the improvement of the quality of services, reducing errors and variability in the healthcare processes. Both the approaches demand a detailed analysis, evidence-based decisions, and efficient control plans. In this paper, the SS is applied as a support tool for HTA of two antibiotics with the final aim of assessing their clinical and organizational impact in terms of postoperative Length Of Stay (LOS) for patients undergoing tongue cancer surgery. More specifically, the SS has been implemented through its main tool, namely the DMAIC (Define, Measure, Analyse, Improve, Control) cycle. Moreover, within the DMAIC cycle, a modelling approach based on a multiple linear regression analysis technique is introduced, in the Control phase, to add complementary information and confirm the results obtained by the statistical analysis performed within the other phases of the SS DMAIC. The obtained results show that the proposed methodology is effective to determine the clinical and organizational impact of each of the examined antibiotics, when LOS is taken as a measure of performance, and guide the decision-making process. Furthermore, our study provides a systematic procedure which, properly combining different and well-assessed tools available in the literature, demonstrated to be a useful guidance for choosing the right treatment based on the available data in the specific circumstance

Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease

The impact of neurodegenerative disorders is twofold; they affect both quality of life and healthcare expenditure. In the case of Parkinson’s disease, several strategies have been attempted to support the pharmacological treatment with rehabilitation protocols aimed at restoring motor function. In this scenario, the study of upper limb control mechanisms is particularly relevant due to the complexity of the joints involved in the movement of the arm. For these reasons, it is difficult to define proper indicators of the rehabilitation outcome. In this work, we propose a methodology to analyze and extract an ensemble of kinematic parameters from signals acquired during a complex upper limb reaching task. The methodology is tested in both healthy subjects and Parkinson’s disease patients (N = 12), and a statistical analysis is carried out to establish the value of the extracted kinematic features in distinguishing between the two groups under study. The parameters with the greatest number of significances across the submovements are duration, mean velocity, maximum velocity, maximum acceleration, and smoothness. Results allowed the identification of a subset of significant kinematic parameters that could serve as a proof-of-concept for a future definition of potential indicators of the rehabilitation outcome in Parkinson’s disease

Agile six sigma in healthcare: Case study at santobono pediatric hospital

Healthcare is one of the most complex systems to manage. In recent years, the control of processes and the modelling of public administrations have been considered some of the main areas of interest in management. In particular, one of the most problematic issues is the management of waiting lists and the consequent absenteeism of patients. Patient no-shows imply a loss of time and resources, and in this paper, the strategy of overbooking is analysed as a solution. Here, a real waiting list process is simulated with discrete event simulation (DES) software, and the activities performed by hospital staff are reproduced. The methodology employed combines agile manufacturing and Six Sigma, focusing on a paediatric public hospital pavilion. Different scenarios show that the overbooking strategy is effective in ensuring fairness of access to services. Indeed, all patients respect the times dictated by the waiting list, without “favouritism”, which is guaranteed by the logic of replacement. In a comparison between a real sample of bookings and a simulated sample designed to improve no-shows, no statistically significant difference is found. This model will allow health managers to provide patients with faster service and to better manage their resources. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

Exploring Biosignals for Quantitative Pain Assessment in Cancer Patients: A Proof of Concept

Perception and expression of pain in cancer patients are influenced by distress levels, tumor type and progression, and the underlying pathophysiology of pain. Relying on traditional pain assessment tools can present limitations due to the highly subjective and multifaceted nature of the symptoms. In this scenario, objective pain assessment is an open research challenge. This work introduces a framework for automatic pain assessment. The proposed method is based on a wearable biosignal platform to extract quantitative indicators of the patient pain experience, evaluated through a self-assessment report. Two preliminary case studies focused on the simultaneous acquisition of electrocardiography (ECG), electrodermal activity (EDA), and accelerometer signals are illustrated and discussed. The results demonstrate the feasibility of the approach, highlighting the potential of EDA in capturing skin conductance responses (SCR) related to pain events in chronic cancer pain. A weak correlation (R = 0.2) is found between SCR parameters and the standard deviation of the interbeat interval series (SDRR), selected as the Heart Rate Variability index. A statistically significant (p < 0.001) increase in both EDA signal and SDRR is detected in movement with respect to rest conditions (assessed by means of the accelerometer signals) in the case of motion-associated cancer pain, thus reflecting the relationship between motor dynamics, which trigger painful responses, and the subsequent activation of the autonomous nervous system. With the objective of integrating parameters obtained from biosignals to establish pain signatures within different clinical scenarios, the proposed framework proves to be a promising research approach to define pain signatures in different clinical contexts

Healthcare professional and manager perceptions on drivers, benefits, and challenges of telemedicine: results from a cross-sectional survey in the Italian NHS

Background: The Covid-19 pandemic provided new challenges and opportunities for patients and healthcare providers while accelerating the trend of digital healthcare transformation. This study explores the perspectives of healthcare professionals and managers on (i) drivers to the implementation of telemedicine services and (ii) perceived benefits and challenges related to the use of telemedicine across the Italian National Health Service. Methods: An online cross-sectional survey was distributed to professionals working within 308 healthcare organisations in different Italian regions. Quantitative and qualitative data were collected through a self-administered questionnaire (June-September 2021). Responses were analysed using summary statistics and thematic analysis. Results: Key factors driving the adoption of telemedicine have been grouped into (i) organisational drivers (reduce the virus spread-80%; enhance care quality and efficiency-61%), (ii) technological drivers (ease of use-82%; efficacy and reliability-64%; compliance with data governance regulations-64%) and (iii) regulatory drivers (regulations’ semplification-84%). Nearly all respondents perceive telemedicine as useful in improving patient care (96%). The main benefits reported by respondents are shorter waiting lists, reduced Emergency Department attendance, decreased patient and clinician travel, and more frequent patient-doctor interactions. However, only 7% of respondents believe that telemedicine services are more effective than traditional care and 66% of the healthcare professionals believe that telemedicine can’t completely substitute in-person visits due to challenges with physical examination and patient-doctor relationships. Other reported challenges include poor quality and interoperability of telemedicine platforms and scarce integration of telemedicine with traditional care services. Moreover, healthcare professionals believe that some groups of patients experience difficulties in accessing and using the technologies due to socio-cultural factors, technological and linguistic challenges and the absence of caregivers. Conclusions: Respondents believe that telemedicine can be useful to complement and augment traditional care. However, many challenges still need to be overcome to fully consider telemedicine a standard of care. Strategies that could help address these challenges include additional regulations on data governance and reimbursements, evidence-based guidelines for the use of telemedicine, greater integration of tools and processes, patient-centred training for clinicians, patient-facing material to assist patients in navigating virtual sessions, different language options, and greater involvement of caregivers in the care process