Rewiring care delivery through Digital Therapeutics (DTx): a machine learning-enhanced assessment and development (M-LEAD) framework.

BACKGROUND: Digital transformation has sparked profound change in the healthcare sector through the development of innovative digital technologies. Digital Therapeutics offer an innovative approach to disease management and treatment. Care delivery is increasingly patient-centered, data-driven, and based on real-time information. These technological innovations can lead to better patient outcomes and support for healthcare professionals, also considering resource scarcity. As these digital technologies continue to evolve, the healthcare field must be ready to integrate them into processes to take advantage of their benefits. This study aims to develop a framework for the development and assessment of Digital Therapeutics. METHODS: The study was conducted relying on a mixed methodology. 338 studies about Digital Therapeutics resulting from a systematic literature review were analyzed using descriptive statistics through RStudio. Machine learning algorithms were applied to analyze variables and find patterns in the data. The results of these analytical analyses were summarized in a framework qualitatively tested and validated through expert opinion elicitation. RESULTS: The research provides M-LEAD, a Machine Learning-Enhanced Assessment and Development framework that recommends best practices for developing and assessing Digital Therapeutics. The framework takes as input Digital Therapeutics characteristics, regulatory aspects, study purpose, and assessment domains. The framework produces as outputs recommendations to design the Digital Therapeutics study characteristics. CONCLUSIONS: The framework constitutes the first step toward standardized guidelines for the development and assessment of Digital Therapeutics. The results may support manufacturers and inform decision-makers of the relevant results of the Digital Therapeutics assessment.

Unveiling the interplay between rational, psychological and functional factors in continuous glucose monitoring early adoption: Novel evidence from the Dexcom ONE case in Italy.

BACKGROUND: The escalating prevalence of diabetes, with its multifaceted complications, poses a pressing challenge for healthcare systems globally. In response, the advent of continuous glucose monitoring (CGM) systems, offering technological solutions for daily diabetes management, presents significant opportunities. However, the widespread adoption faces several barriers, linked both to the technological configuration of the devices and to the psychological dimension of patients. Therefore, this study aims to apply and test a theoretical model that investigates the antecedents of the intention to use Continuous Glucose Monitoring systems. METHODS: The research model was built to unveil the impacts of psychological factors, functional components and rational constructs derived from the Technology Acceptance Model (TAM) on CGM systems sustained adoption. To ensure the comparability of results, we have collected data from people who had used Dexcom ONE Dexcom (San Diego, CA) for the first time for at least one month. Employing Structural Equation Modelling (SEM) techniques, the hypothesized relationships among constructs were assessed. RESULTS: The analyses confirmed the positive correlation of rational factors to the Intention to Use. Subjective Norm, intended as the physicians' influence, is positively correlated with the Perceived Usefulness. Trend Arrows, albeit being negatively correlated with Perceived Usefulness, have a positive correlation on Perceived Ease Of Use, reinforcing its mediating effect towards Perceived Usefulness. Among psychological factors, Trust in the CGM technology positively correlates with Intention to Use. Health Literacy is negatively correlated to the Intention to Use. CONCLUSIONS: These findings contribute to theoretical and managerial understanding, providing recommendations to enhance the adoption of CGM systems like Dexcom ONE.

High-energy devices in different surgical settings: lessons learnt from a full health technology assessment report developed by SICE (Società Italiana di Chirurgia Endoscopica).

BACKGROUND: The present paper aims at evaluating the potential benefits of high-energy devices (HEDs) in the Italian surgical practice, defining the comparative efficacy and safety profiles, as well as the potential economic and organizational advantages for hospitals and patients, with respect to standard monopolar or bipolar devices. METHODS: A Health Technology Assessment was conducted in 2021 assuming the hospital perspective, comparing HEDs and standard monopolar/bipolar devices, within eleven surgical settings: appendectomy, hepatic resections, colorectal resections, cholecystectomy, splenectomy, hemorrhoidectomy, thyroidectomy, esophago-gastrectomy, breast surgery, adrenalectomy, and pancreatectomy. The nine EUnetHTA Core Model dimensions were deployed considering a multi-methods approach. Both qualitative and quantitative methods were used: (1) a systematic literature review for the definition of the comparative efficacy and safety data; (2) administration of qualitative questionnaires, completed by 23 healthcare professionals (according to 7-item Likert scale, ranging from - 3 to + 3); and (3) health-economics tools, useful for the economic evaluation of the clinical pathway and budget impact analysis, and for the definition of the organizational and accessibility advantages, in terms of time or procedures' savings. RESULTS: The literature declared a decrease in operating time and length of stay in using HEDs in most surgical settings. While HEDs would lead to a marginal investment for the conduction of 178,619 surgeries on annual basis, their routinely implementation would generate significant organizational savings. A decrease equal to - 5.25/-9.02% of operating room time and to - 5.03/-30.73% of length of stay emerged. An advantage in accessibility to surgery could be hypothesized in a 9% of increase, due to the gaining in operatory slots. Professionals' perceptions crystallized and confirmed literature evidence, declaring a better safety and effectiveness profile. An improvement in both patients and caregivers' quality-of-life emerged. CONCLUSIONS: The results have demonstrated the strategic relevance related to HEDs introduction, their economic sustainability, and feasibility, as well as the potentialities in process improvement.

What drives patients' acceptance of Digital Therapeutics? Establishing a new framework to measure the interplay between rational and institutional factors.

BACKGROUND: The rising incidence of chronic diseases among the population, further exacerbated by the phenomenon of aging, is a primary concern and a serious challenge for the healthcare systems worldwide. Among the wide realm of health digital technologies, the rise of Digital Therapeutics (DTx), which are medical devices able to deliver evidence-based treatments to manage and treat diseases, opens new opportunities. However, their diffusion and usage are still fragmented among countries. As the diffusion results from the adoption of technology from a social system and individual acceptance, this study aims to design and test a theoretical model that investigates the intention to use DTx, with a particular focus on the treatment of obesity, as a widespread and burdensome chronic condition. METHODS: This research is built on 336 answers coming from a survey to test the proposed model, which consists of a combination of organizational mechanisms, derived from Institutional Theory, and rational factors, derived from the Technology Acceptance Model (TAM). The survey has been delivered to patients and former patients of Istituto Auxologico Italiano, a hospital with several locations in northern Italy, recognized as a center of excellence for the treatment of obesity. RESULTS: The analyses of the answers, performed through the Structural Equation Modelling (SEM) technique, confirmed the influence of the Perceived Usefulness on Intention To Use, and of the Perceived Ease Of Use on the Perceived Usefulness, confirming the validity of the assumptions derived from the TAM. On the other hand, institutional factors were introduced as antecedents of the Perceived Usefulness, and the Perceived Ease Of Use. Results show that the Regulative Pillar influences both the TAM constructs, the Normative Pillar (peer influence) has a positive effect only on the Perceived Usefulness, and finally, the Cultural Pillar impacts the Perceived Ease Of Use. CONCLUSION: This study allows filling the knowledge gap regarding the usage of the Institutional as a means to predict individuals' intentions. Moreover, managerial contributions are available as the results have been operationalized into practical advice to managers and healthcare professionals to foster the adoption, and thus the diffusion, of Digital Therapeutics.

Glucometer Usability for 65+ Type 2 Diabetes Patients: Insights on Physical and Cognitive Issues.

Background: Self-monitoring of blood glucose (SMBG) is of paramount relevance for type 2 diabetes mellitus (T2DM) patients. However, past evidence shows that there are physical and cognitive issues that might limit the usage of glucometers by T2DM patients aged 65 years and over. Objective: Our aim was to investigate the physical and cognitive issues related to the usage of glucometers by T2DM patients aged 65 years and over. Materials and Methods: The extant literature was analysed to define an original framework showing the logical nexus between physical and cognitive issues and quality of life. Then we collected evidence addressing the specific case of the Accu-Chek® Instant glucometer produced by Roche Diabetes Care GmbH, which implements new features claiming to improve usability. We conducted 30 interviews with T2DM patients aged 65 years and over, three interviews with senior nurses, and a focus group with three senior physicians and three senior nurses. Results: From the interviews, both patients and nurses declared that they were generally satisfied with the Accu-Chek® Instant glucometer's characteristics. In the focus group, the results were commented on and, in the light of some diverging answers, improvements have been set up for future implementation. Conclusions: Our study produces evidence and future suggestions about the usage of glucometers by type 2 diabetes patients aged 65 years and over.

Adoption of novel biomarker test parameters with machine learning-based algorithms for the early detection of sepsis in hospital practice.

AIMS: We aim (i) to redesign sepsis's clinical pathway and fit the organizational requirements of a novel machine-learning algorithm incorporating a novel biomarker test and (ii) to assess adoption drivers of the new combined technology. BACKGROUND: There is an urgent need to achieve sepsis' early detection and diagnostic excellence. METHODS: A qualitative study based on semi-structured interviews conducted at the target site and across other Italian hospitals. A content analysis was undertaken, emergent themes were selected and categorized, and interviews were conducted until saturation was reached. RESULTS: Sixteen nurses (10 at the target site and six across other hospitals) and nine non-nursing professionals (seven at the target site and two across other hospitals) were interviewed. An organizational redesign was identified as the primary adoption driver. Even though nurses perceived workload increase related to the machine-learning component, technology acceptability was relatively high, as the standardization of tasks was perceived as crucial to improving professional satisfaction. CONCLUSIONS: A novel business-oriented solution based on machine learning requires interprofessional integration, new professional roles, infrastructure improvement, and data integration to be effectively implemented. IMPLICATIONS FOR NURSING MANAGEMENT: Lessons learned from this study suggest the need to involve nurses in the early stages of the design of new machine-learning technologies and the importance of training nurses on sepsis management through the support of disruptive technological innovation.

Individuals' adoption of smart technologies for preventive health care: a structural equation modeling approach.

Healthcare is moving towards new patterns and models, with an increasing attention paid to prevention. Smart technologies for mobile health care are emerging as new instruments to monitor the state of essential parameters in citizens. A very debated subject in literature is the critical role played by citizens' acceptance and willingness to pay for mobile health technologies, especially whereas the services provided are preventive rather than curative. The adoption of such technologies is, indeed, a necessary condition for the success of mobile personalized health care. In this view, a conceptual framework, grounded on Technology Acceptance Model, is developed to explore the determinants of users' willingness to adopt and pay for a mobile health care application for cardiovascular prevention. Empirical data are collected from a sample of 212 non-hypertensive Italian individuals and analyzed through Structural Equation Modeling. Results confirm that usefulness and ease of use determine both intention to accept and willingness to pay for mobile health smart technologies. Results show also the significant role played by social influence as well the role as antecedents played by technology promptness, innovativeness and prevention awareness. This study offers novel insights to design and promote smart application to improve mobile health care, with implications for researchers and practitioners in health care, research & development, and marketing.

Data mining application to healthcare fraud detection: a two-step unsupervised clustering method for outlier detection with administrative databases.

BACKGROUND: The healthcare sector is an interesting target for fraudsters. The availability of a great amount of data makes it possible to tackle this issue with the adoption of data mining techniques, making the auditing process more efficient and effective. This research has the objective of developing a novel data mining model devoted to fraud detection among hospitals using Hospital Discharge Charts (HDC) in Administrative Databases. In particular, it is focused on the DRG upcoding practice, i.e., the tendency of registering codes for provided services and inpatients health status so to make the hospitalization fall within a more remunerative DRG class. METHODS: We propose a two-step algorithm: the first step entails kmeans clustering of providers to identify locally consistent and locally similar groups of hospitals, according to their characteristics and behavior treating a specific disease, in order to spot outliers within this groups of peers. An initial grid search for the best number of features to be selected (through Principal Feature Analysis) and the best number of local groups makes the algorithm extremely flexible. In the second step, we propose a human-decision support system that helps auditors cross-validating the identified outliers, analyzing them w.r.t. fraud-related variables, and the complexity of patients' casemix they treated. The proposed algorithm was tested on a database relative to HDC collected by Regione Lombardia (Italy) in a time period of three years (2013-2015), focusing on the treatment of Heart Failure. RESULTS: The model identified 6 clusters of hospitals and 10 outliers among the 183 units. Out of those providers, we report the in depth the application of Step Two on three Hospitals (two private and one public). Cross-validating with the patients' population and the hospitals' characteristics, the public hospital seemed justified in its outlierness, while the two private providers were deemed interesting for a further investigation by auditors. CONCLUSIONS: The proposed model is promising in identifying anomalous DRG coding behavior and it is easily transferrable to all diseases and contexts of interest. Our proposal contributes to the limited literature regarding behavioral models for fraud detection, identifying the most 'cautious' fraudsters. The results of the first and the second Steps together represent a valuable set of information for auditors in their preliminary investigation.

Multi-level models for heart failure patients' 30-day mortality and readmission rates: the relation between patient and hospital factors in administrative data.

BACKGROUND: This study aims at gathering evidence about the relation between 30-day mortality and 30-day unplanned readmission and patient and hospital factors. By definition, we refer to 30-day mortality and 30-day unplanned readmission as the number of deaths and non-programmed hospitalizations for any cause within 30 days after the incident heart failure (HF). In particular, the focus is on the role played by hospital-level factors. METHODS: A multi-level logistic model that combines patient- and hospital-level covariates has been developed to better disentangle the role played by the two groups of covariates. Later on, hospital outliers in term of better-than-expected/worst-than-expected performers have been identified by comparing expected cases vs. observed cases. Hospitals performance in terms of 30-day mortality and 30-day unplanned readmission rates have been visualized through the creation of funnel plots. Covariates have been selected coherently to past literature. Data comes from the hospital discharge forms for Heart Failure patients in the Lombardy Region (Northern Italy). Considering incident cases for HF in the timespan 2010-2012, 78,907 records for adult patients from 117 hospitals have been collected after quality checks. RESULTS: Our results show that 30-day mortality and 30-day unplanned readmissions are explained by hospital-level covariates, paving the way for the design and implementation of evidence-based improvement strategies. While the percentage of surgical DRG (OR = 1.001; CI (1.000-1.002)) and the hospital type of structure (Research hospitals vs. non-research public hospitals (OR = 0.62; CI (0.48-0.80)) and Non-research private hospitals vs. non-research hospitals OR = 0.75; CI (0.63-0.90)) are significant for mortality, the mean length of stay (OR = 0.96; CI (0.95-0.98)) is significant for unplanned readmission, showing that mortality and readmission rates might be improved through different strategies. CONCLUSION: Our results confirm that hospital-level covariates do affect quality of care, and that 30-day mortality and 30-day unplanned readmission are affected by different managerial choices. This confirms that hospitals should be accountable for their "added value" to quality of care.

Big Data in Adolescent Psychiatry: Do Patients Share Their Psychiatric Symptoms on Social Networking Sites?

BACKGROUND: Fascinating developments in big data technologies and unprecedented diffusion of social networking sites (SNSs) generate unseen opportunities for scientific fields, including psychiatry. This study focuses on the use of SNSs by adolescent psychiatric patients and the potential use of SNS-generated data to help medical practitioners diagnose and treat patients' mental health. Our objective is to understand and measure the psychiatric and individual conditions in which symptom-sharing occurs on SNSs and the frequency of these conditions. Based on literature, we hypothesized that the perceived value of social network sites positively affects adolescents' sharing of symptoms on these sites. SUBJECTS AND METHODS: An empirical test of this hypothesis was conducted with a survey of 224 adolescents admitted to a psychiatry clinic in Turkey. The hypothesis was tested using a hierarchical multiple regression analysis. RESULTS: The perceived value of SNSs explained an additional 37.8% of variation in symptom sharing on SNSs above and beyond the control variables, which are gender, age, type of disorder, and amount of internet and SNS use. The findings suggested that adolescents share symptoms on SNSs only if they attribute value to the SNSs that they use. We also found that 72% of adolescents in our sample shared their symptoms on SNSs. CONCLUSIONS: There is an attractive opportunity for information technology companies to develop, together with health professionals; data analytics that are able to detect symptoms to support psychiatric diagnoses and pave the way for big-data enabled personalized medicine.

TECHNOLOGY ASSESSMENT IN HOSPITALS: LESSONS LEARNED FROM AN EMPIRICAL EXPERIMENT.

OBJECTIVES: Hospital Based Health Technology Assessment (HBHTA) practices, to inform decision making at the hospital level, emerged as urgent priority for policy makers, hospital managers, and professionals. The present study crystallized the results achieved by the testing of an original framework for HBHTA, developed within Lombardy Region: the IMPlementation of A Quick hospital-based HTA (IMPAQHTA). The study tested: (i) the HBHTA framework efficiency, (ii) feasibility, (iii) the tool utility and completeness, considering dimensions and sub-dimensions. METHODS: The IMPAQHTA framework deployed the Regional HTA program, activated in 2008 in Lombardy, at the hospital level. The relevance and feasibility of the framework were tested over a 3-year period through a large-scale empirical experiment, involving seventy-four healthcare professionals organized in different HBHTA teams for assessing thirty-two different technologies within twenty-two different hospitals. Semi-structured interviews and self-reported questionnaires were used to collect data regarding the relevance and feasibility of the IMPAQHTA framework. RESULTS: The proposed HBHTA framework proved to be suitable for application at the hospital level, in the Italian context, permitting a quick assessment (11 working days) and providing hospital decision makers with relevant and quantitative information. Performances in terms of feasibility, utility, completeness, and easiness proved to be satisfactory. CONCLUSIONS: The IMPAQHTA was considered to be a complete and feasible HBHTA framework, as well as being replicable to different technologies within any hospital settings, thus demonstrating the capability of a hospital to develop a complete HTA, if supported by adequate and well defined tools and quantitative metrics.

Empowering patients through eHealth: a case report of a pan-European project.

BACKGROUND: This paper crystallises the experience developed by the pan-European PALANTE Consortium in dealing with the generation of relevant evidence from heterogeneous eHealth services for patient empowerment in nine European Regions. The European Commission (EC) recently funded a number of pan-European eHealth projects aimed at empowering European patients/citizens thus transforming the traditional patient/citizen role in the management of their health (e.g., PALANTE, SUSTAIN, CARRE, HeartCycle, Empower). However, the heterogeneity of the healthcare systems, of the implemented services and of the target patients, the use of ad-hoc definitions of the salient concepts and the development of small-size experiences have prevented the dissemination of "global" results and the development of cumulative knowledge. The main challenge has been the generation of large-scale evidence from heterogeneous small-size experiences. DISCUSSION: Three lessons have been collectively learnt during the development of the PALANTE project, which involves 9 sites that have implemented different eHealth services for empowering different typologies of patients. These lessons have been refined progressively through project meetings, reviews with the EC Project Officer and Reviewers. The paper illustrates the ten steps followed to develop the three lessons. The first lesson learnt is about how EC-funded projects should develop cumulative knowledge by avoiding self-crafted measures of outcome and by adopting literature-grounded definitions and scales. The second lesson learnt is about how EC-funded projects should identify ambitious, cross-pilot policy and research questions that allow pooling of data from across heterogeneous experiences even if a multi-centre study design was not agreed before. The third lesson learnt is about how EC-funded projects should open their collections of data and make them freely-accessible to the scientific community shortly after the conclusion of the project in order to guarantee the replicability of results and conclusions. SUMMARY: The three lessons might provide original elements for fuelling the ongoing debate about the capability of the EC to develop evidence-based policies by pooling evidence from heterogeneous, local experiences.

Clinical competence in the surgery of rectal cancer: the Italian Consensus Conference.

BACKGROUND AND AIM: The literature continues to emphasize the advantages of treating patients in "high volume" units by "expert" surgeons, but there is no agreed definition of what is meant by either term. In September 2012, a Consensus Conference on Clinical Competence was organized in Rome as part of the meeting of the National Congress of Italian Surgery (I Congresso Nazionale della Chirurgia Italiana: Unità e valore della chirurgia italiana). The aims were to provide a definition of "expert surgeon" and "high-volume facility" in rectal cancer surgery and to assess their influence on patient outcome. METHOD: An Organizing Committee (OC), a Scientific Committee (SC), a Group of Experts (E) and a Panel/Jury (P) were set up for the conduct of the Consensus Conference. Review of the literature focused on three main questions including training, "measuring" of quality and to what extent hospital and surgeon volume affects sphincter-preserving procedures, local recurrence, 30-day morbidity and mortality, survival, function, choice of laparoscopic approach and the choice of transanal endoscopic microsurgery (TEM). RESULTS AND CONCLUSION: The difficulties encountered in defining competence in rectal surgery arise from the great heterogeneity of the parameters described in the literature to quantify it. Acquisition of data is difficult as many articles were published many years ago. Even with a focus on surgeon and hospital volume, it is difficult to define their role owing to the variability and the quality of the relevant studies.

Implementation of EUnetHTA core Model® in Lombardia: the VTS framework.

OBJECTIVES: This study describes the health technology assessment (HTA) framework introduced by Regione Lombardia to regulate the introduction of new technologies. The study outlines the process and dimensions adopted to prioritize, assess and appraise the requests of new technologies. METHODS: The HTA framework incorporates and adapts elements from the EUnetHTA Core Model and the EVIDEM framework. It includes dimensions, topics, and issues provided by EUnetHTA Core Model to collect data and process the assessment. Decision making is instead supported by the criteria and Multi-Criteria Decision Analysis technique from the EVIDEM consortium. RESULTS: The HTA framework moves along three process stages: (i) prioritization of requests, (ii) assessment of prioritized technology, (iii) appraisal of technology in support of decision making. Requests received by Regione Lombardia are first prioritized according to their relevance along eight dimensions (e.g., costs, efficiency and efficacy, organizational impact, safety). Evidence about the impacts of the prioritized technologies is then collected following the issues and topics provided by EUnetHTA Core Model. Finally, the Multi-Criteria Decision Analysis technique is used to appraise the novel technology and support Regione Lombardia decision making. CONCLUSIONS: The VTS (Valutazione delle Tecnologie Sanitarie) framework has been successfully implemented at the end of 2011. From its inception, twenty-six technologies have been processed.

Therapies go digital. What drives physicians' acceptance?

National healthcare systems face multiple challenges, including the increasing demand for care and decreasing availability of healthcare professionals. Digital health technologies represent opportunities that offer improved efficiency, accessibility, and patient care. In this scenario, Digital Therapeutics are technological advancements to treat or alleviate a disease and deliver a medical intervention with evidence-based therapeutic impacts and regulatory approval. Digital Therapeutics are a paradigm shift for physicians, who exercise caution in terms of trust and wide usage. Digital Therapeutics represents an opportunity and a challenge in healthcare system integration. The research investigates the factors explaining physicians' acceptance of Digital Therapeutics. A research model that combines organizational mechanisms derived from Institutional Theory and rational factors derived from the Technology Acceptance model was developed. The model was tested through 107 responses from a survey distributed to the members of the leading Italian scientific society in Diabetology. Literature-based hypotheses were empirically tested through Structural Equation Modelling. The analysis confirmed the influence of Perceived Ease of Use on Perceived Usefulness and Perceived Usefulness on the Intention To Use Digital Therapeutics. Rules and norms impact Perceived Usefulness when considering the influence of the scientific society. Culture and mindset towards innovation within the hospital positively affect Perceived Ease of Use. The readiness of hospital facilities enhances the extent to which physicians perceive the ease of employing Digital Therapeutics in their daily practice. Instead, esteemed colleagues' opinions and guidelines from the scientific society reveal to physicians the value of Digital Therapeutics in patients' care pathways. Institutions should prioritize cultural, normative, and regulative aspects to accelerate physicians' endorsement of Digital Therapeutics. Findings advance the theoretical knowledge around clinicians' adoption of innovative digital health technologies, unveiling the interaction between rational and institutional factors. The results highlight practical implications for healthcare institutions and Digital Therapeutics manufacturers willing to promote their adoption.

Mixed Reality and Artificial Intelligence: A Holistic Approach to Multimodal Visualization and Extended Interaction in Knee Osteotomy.

OBJECTIVE: Recent advancements in augmented reality led to planning and navigation systems for orthopedic surgery. However little is known about mixed reality (MR) in orthopedics. Furthermore, artificial intelligence (AI) has the potential to boost the capabilities of MR by enabling automation and personalization. The purpose of this work is to assess Holoknee prototype, based on AI and MR for multimodal data visualization and surgical planning in knee osteotomy, developed to run on the HoloLens 2 headset. METHODS: Two preclinical test sessions were performed with 11 participants (eight surgeons, two residents, and one medical student) executing three times six tasks, corresponding to a number of holographic data interactions and preoperative planning steps. At the end of each session, participants answered a questionnaire on user perception and usability. RESULTS: During the second trial, the participants were faster in all tasks than in the first one, while in the third one, the time of execution decreased only for two tasks ("Patient selection" and "Scrolling through radiograph") with respect to the second attempt, but without statistically significant difference (respectively [Formula: see text] = 0.14 and [Formula: see text] = 0.13, [Formula: see text]). All subjects strongly agreed that MR can be used effectively for surgical training, whereas 10 (90.9%) strongly agreed that it can be used effectively for preoperative planning. Six (54.5%) agreed and two of them (18.2%) strongly agreed that it can be used effectively for intraoperative guidance. DISCUSSION/CONCLUSION: In this work, we presented Holoknee, the first holistic application of AI and MR for surgical planning for knee osteotomy. It reported promising results on its potential translation to surgical training, preoperative planning, and surgical guidance. Clinical and Translational Impact Statement - Holoknee can be helpful to support surgeons in the preoperative planning of knee osteotomy. It has the potential to impact positively the training of the future generation of residents and aid surgeons in the intraoperative stage.

A retrospective multidimensional comparison of microprocessor and mechanical knee users: Analysis of quality of life and satisfaction with the prosthesis.

BACKGROUND: Despite the demonstrated greater efficacy of microprocessor knees (MPK) over mechanical knees (MK), the latter is still widely used by persons with transfemoral amputation. Besides motivations related to local insurance policies, quality of life (QoL) and satisfaction with the prosthesis play a key role in user preference. OBJECTIVE: The aim of this study is to compare QoL and satisfaction in a large sample of MPK and MK users and to assess how these outcomes are explained by clinical and demographic characteristics. STUDY DESIGN: Retrospective study. METHODS: The study was conducted on 75 MPK and 60 MK users. Quality of life was assessed using the EuroQoL Five Dimensions and the EuroQoL Visual Analog Scale questionnaires. Satisfaction was assessed with the Satisfaction with Prosthesis questionnaire. All 3 instruments were self-administered. Univariate and multivariate regression analyses were conducted thereafter. RESULTS: The difference in satisfaction between MPK and MK users was not statistically significant. Significant differences were observed instead for QoL. From the univariate regression analysis, 6 factors were significant predictors of QoL and satisfaction. On multivariate analysis, the number of significant factors was reduced to 3, namely knee type, age at the first prosthesis, and experience with prosthesis. Type of knee and age at the first prosthesis significantly predicted QoL scores, explaining 12% of EuroQoL Five Dimensions and 25% of EuroQoL Visual Analog Scale variances. Age at the first prosthesis and experience with prosthesis predicted Satisfaction with Prosthesis scores in the multivariate model, explaining 25% of the variance. CONCLUSIONS: MPK affects QoL but not satisfaction, which is positively driven by patients' experience with prosthesis and negatively affected by the age at the time of the first prosthesis.

The freedom to run: developing an autonomous robot matching the needs of visually impaired citizens to technology opportunities.

Purpose: Visual impairment poses significant challenges in daily life, especially when navigating unfamiliar environments, resulting in inequalities and reduced quality of life. This study aimed to gain an in-depth understanding of the needs and perspectives of visually impaired people in sports-related contexts through surveys and focus groups, and to understand whether their needs are being met by current technological solutions.Materials and methods: To accomplish this, opinions gathered from focus groups and interviews were compared to the technological solutions found in the literature. Since many unmet needs were identified, participants from associations and organizations were asked to identify key characteristics for the development of a robot guide. The results underscored the paramount importance of an easy-to-use guide that offers accurate and personalized assistance. Participants expressed a strong desire for advanced features such as object recognition and navigation in complex environments, as well as adaptability to the user's speed while providing the necessary safety features to ensure a high level of autonomy.Results: This research serves as a bridge between technological advances and the needs of the visually impaired, contributing to a more accessible and inclusive society. By addressing the unique challenges faced by the visually impaired individuals and tailoring technology to meet their needs, this study takes a significant step toward reducing disparities and improving the independence and quality of life for this community.Conclusions: As technology continues to advance, it has the potential to be a powerful tool in breaking down barriers and fostering a world where everyone, regardless of their visual ability, can navigate the world with confidence and ease.

Inclusive design: Recognizing the importance of incorporating the unique requirements and perspectives of visually impaired individuals can guide the development of rehabilitation technology and services, ensuring they effectively support daily activities and active participation in sports and physical pursuits.Tailored-assistive technology: Understanding the specific needs of visually impaired individuals with regards to assistive technology, such as dependable robotic guides and essential features, can inform the design and customization of rehabilitation aids to enhance mobility and independence.Promising technologies: Exploring promising technologies like Aira, Be My Eyes, RoboCart, and Wayband can inspire the integration of these innovations into rehabilitation programs, facilitating better orientation, mobility, and accessibility for individuals with visual impairments.Continued research and development: Emphasizing the necessity for ongoing research and development efforts underscores the importance of advancing rehabilitation solutions that effectively address the distinct needs of visually impaired individuals, particularly in navigating unfamiliar environments.

Systematic application of SICA-PED protocol for central venous catheterization in neonates: A prospective clinical study on 104 cases.

BACKGROUND: Catheterization of central vessels can be associated with early and late, potentially fatal complications. A proactive approach is imperative to reduce the frequency and magnitude of adverse events. Recently, the GAVeCeLT has proposed a protocol called SICA-PED (i.e. Safe Insertion of Central Access in Pediatric patients) and includes seven evidence-based strategies. METHODS: Through a single-center prospective observational study, the authors wanted to consolidate the efficacy and safety of these protocol in newborns. In a series of 104 newborns, the seven steps of the protocol were applied (1) pre-procedural ultrasound study of the RaCeVA veins, (2) correct aseptic technique, (3) ultrasound-guided venipuncture, (4) intraprocedural localization of the tip of the catheter with TTE (ECHO TIP) and (iECG) intracavitary electrocardiogram, (5) reasoned choice of the implant exit site with the RAVESTO Tunneling technique, (6) anchoring without stitches, and (7) exit point protection with the use of glue and transparent semipermeable membrane. The authors have included a further precaution in point (6) the subcutaneous anchoring system has added the counter-fixation of the catheter wings that we will call 6Plus Point. RESULTS: All infants requiring implantation of elective us-guided central venous access were enrolled in the study. None of the 104 implanted central venous catheters experienced early complications (accidental arterial puncture, PNX, primary malposition); rare late complications such as ecchymosis, CRBSI, exit site infection or dislodgement were observed, No catheter-related thrombotic phenomena were observed. The CRBSI catheter-related infection rate was 2.47 × 1000 days catheter cases. CONCLUSION: The results of this prospective study strengthen the feasibility and efficacy of the SICA-Ped Protocol. Demonstrating that the systematic application of the evidence-based seven-step implantation strategy increases the success rate, minimizes early and late complications, which result in increased patient safety.

Assessing the Social and Environmental Impact of Healthcare Technologies: Towards an Extended Social Return on Investment.

Stroke is the third leading cause of death and disability overall worldwide. Upper limb impairment is a common consequence for stroke survivors, having negative impact on their quality of life. Robotic rehabilitation, through repetitive and monitored movements, can improve their status. Developed by a team of researchers at Politecnico di Milano, AGREE is an exoskeleton for upper limb rehabilitation at the stage gate between translational research and clinical validation. Since the cost of this device is particularly high, the present study aimed to provide a framework for assessing its value. The Social Return on Investment (SROI) method, able to grasp the economic, social and environmental impact of an activity, was applied, using expert opinions of a pool of clinical engineers and healthcare professionals from different Italian hospitals to obtain information. Environmental impacts were estimated through Life Cycle Assessment in terms of CO2 emissions and incorporated in the analysis. Considering a 5-year period, the SROI for a single exoskeleton was 3.75:1, and the SROI for the number of exoskeletons projected to be sold was 2.868:1, thus resulting largely in value for money. This study provides a model for combining economic, social and environmental outcomes that, besides contributing to theory, could be useful for decision-making.