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.

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.

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.

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.

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.

Development and validation of Medical Device Key Evidence Tool ('MeDKET'): An evidence-based framework to explain success in selected European and US companies.

Innovating in Medical Device (MD) industry is challenging. This study aims to develop and validate an evidence-based framework that helps innovators of small and large enterprises (SEs and LEs) assess their readiness for successful MD development and deployment. We conducted a key-informant process (stage 1) where 25 international experts identified a list of emergent Health Technology Assessment (HTA) themes they believed were essential to company success. A sample of 22 European and US selected companies (13 SEs and 9 LEs) then reached a consensus on a list of key themes through a robust Delphi process (stage 2). Finally, we constructed (stage 3) and validated (stage 4) the checklist for SEs and LEs. The checklist for SEs and LEs included 21 and 15 items (i.e., fundamental Yes/No questions) with nine overlapping criteria for both SEs and LEs. In both groups, MD success was driven by three major item categories: (i) R&D assessment strategy; (ii) device-outcome measures; (iii) company profiling. Alongside the retrospective validation study, we collected 40 case studies on MDs (23 successes and 17 failures) across the selected enterprises. The retrospective validation provided the proportion of successful and failed case studies that met the 'MeDKET' criteria. We discovered that early HTA plays a pivotal role in MD industry success with different implications based on enterprise size. This study is the first of its kind to provide a holistic picture of the perceived role of early-stage HTA in MD industry success.

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.

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.

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.

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.

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.

Development and psychometric testing of a new measure of the determinants that influence the adoption of WhatsApp in hospitals.

BACKGROUND: Healthcare contexts are witnessing a growing use of applications to support clinical processes and to communicate between peers and with patients. An increasing number of hospital professionals use instant-messaging applications such as WhatsApp in their daily work. Previous research has mainly focused on the advantages and risks of WhatsApp usage in different clinical settings, but limited evidence is available about whether and how individual and organizational determinants can influence the use of WhatsApp in hospitals. Moreover, instruments to explore this phenomenon are lacking. A theoretical four-factor model based on the 'Technology Acceptance Model' and the Institutional Theory, guided the development of a new measure of the individual and institutional determinants of WhatsApp usage in hospitals. AIM: To develop and psychometrically test the questionnaire 'Digital Innovation Adoption in Hospitals'. METHOD: A panel of researchers and clinical experts generated an initial pool of 35 items by identifying and adapting items from existing measures. These items were assessed for content and face validity by fourteen experts. The final 28-item 'Digital Innovation Adoption in Hospitals' questionnaire comprising four sections (Perceived risks, Perceived usefulness, Regulative factors and Normative factors) was administered online to nurses and physicians. Construct validity was tested through confirmatory factor analysis. RESULTS: The sample included 326 hospital nurses and physicians. The theoretical four-factors model was confirmed and the confirmatory factor analysis yielded acceptable fit indexes. The correlations between the factors were significant and ranged from -0.284 to 0.543 (p < .01). Reliability in terms of internal consistency was satisfactory with Cronbach's alpha coefficient ranging from 0.918-0.973. CONCLUSION: This study is the first to provide a validated tool to evaluate the use of WhatsApp in hospitals. The new instrument shows reasonable psychometric properties and is a promising and widely applicable measure of factors that influence the use of WhatsApp in hospitals.

Stability over time of the "hospital effect" on 30-day unplanned readmissions: Evidence from administrative data.

Past studies showed that hospital characteristics affect hospital performance in terms of 30-day unplanned readmissions, proving the existence of a "hospital effect". However, the stability over time of this effect has been under-investigated. This study offers new evidence about the stability over time of the hospital effect on 30-day unplanned readmissions. Using 78,907 heart failure (HF) records collected from 116 hospitals in the Lombardy Region (Northern Italy) over three years (2010-2012), this study analysed hospital performance in terms of 30-day unplanned readmissions. Hospitals with unusually high and low readmission rates were identified through multi-level regression that combined both patient and hospital covariates in each year. Our results confirm that although hospital covariates - and the connected managerial choices - affect the 30-day unplanned readmissions of a specific year, their effect is not stable in the short-term (3 years). This has important implications for pay-for-performance schemes and quality improvement initiatives.

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.

Composite Outcomes of Mortality and Readmission in Patients with Heart Failure: Retrospective Review of Administrative Datasets.

BACKGROUND: Controlling the quality of care through readmissions and mortality for patients with heart failure (HF) is a national priority for healthcare regulators in developed countries. In this longitudinal cohort study, using administrative data such as hospital discharge forms (HDFs), emergency departments (EDs) accesses, and vital statistics, we test new covariates for predicting mortality and readmissions of patients hospitalized for HF and discuss the use of combined outcome as an alternative. METHODS: Logistic models, with a stepwise selection method, were estimated on 70% of the sample and validated on the remaining 30% to evaluate 30-day mortality, 30-day readmissions, and the combined outcome. We followed an extraction method for any-cause mortality and unplanned readmission within 30 days after incident HF hospitalization. Data on patient admission and previous history were extracted by HDFs and ED dataset. RESULTS: Our principal findings demonstrate that the model's discriminant ability is consistent with literature both for mortality (AUC=0.738, CI (0.729-0.748)) and readmissions (AUC=0.578, CI (0.562-0.594)). Additionally, the discriminant ability of the composite outcome model is satisfactory (AUC=0.675, CI (0.666-0.684)). CONCLUSION: Hospitalization characteristics and patient history introduced in the logistic models do not improve their discriminant ability. The composite outcome prediction is led more by mortality than readmission, without improvements for the comprehension of the readmission phenomenon.

Electronic Medical Records implementation in hospital: An empirical investigation of individual and organizational determinants.

The implementation of hospital-wide Electronic Medical Records (EMRs) is still an unsolved quest for many hospital managers. EMRs have long been considered a key factor for improving healthcare quality and safety, reducing adverse events for patients, decreasing costs, optimizing processes, improving clinical research and obtaining best clinical performances. However, hospitals continue to experience resistance from professionals to accepting EMRs. This study combines institutional and individual factors to explain which determinants can trigger or inhibit the EMRs implementation in hospitals, and which variables managers can exploit to guide professionals' behaviours. Data have been collected through a survey administered to physicians and nurses in an Italian University Hospital in Rome. A total of 114 high-quality responses had been received. Results show that both, physicians and nurses, expect many benefits from the use of EMRs. In particular, it is believed that the EMRs will have a positive impact on quality, efficiency and effectiveness of care; handover communication between healthcare workers; teaching, tutoring and research activities; greater control of your own business. Moreover, data show an interplay between individual and institutional determinants: normative factors directly affect perceived usefulness (C = 0.30 **), perceived ease of use (C = 0.26 **) and intention to use EMRs (C = 0.33 **), regulative factors affect the intention to use EMRs (C = -0.21 **), and perceived usefulness directly affect the intention to use EMRs (C = 0.33 **). The analysis carried out shows that the key determinants of the intention to use EMRs are the normative ones (peer influence) and the individual ones (perceived usefulness), and that perceived usefulness works also as a mediator between normative factors and intention to use EMRs. Therefore, Management can leverage on power users to motivate, generate and manage change.

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.

What drives hospital wards' ambidexterity: Insights on the determinants of exploration and exploitation.

OBJECTIVES: Hospital wards are required to exploit current knowledge and explore for new knowledge. Ambidexterity (i.e., the capability to combine both exploitation and exploration) is a major issue in healthcare as result of the growing expectations that hospitals wards have the capability to manage the trade-off between high-quality delivery of care and cost-containment. This study sheds novel light on the determinants of ambidextrous behaviours in hospital wards. METHODS: A theoretical framework has been built on the extant literature. The main determinants of ambidexterity are opening/closing leadership, organisational support, organisational creativity and environmental dynamism. The model has been tested empirically through data collected via survey administered to head physicians in charge of hospital wards. After the quality check, 80 questionnaires were available for the statistical analysis based on a hierarchical sequential linear regression model (with enter methodology). RESULTS: Results showed that opening (ß = 0.389;p < 0.001) and closing (ß = 0.288;p < 0.01) leadership, as well as organisational creativity (ß = 0.499 p < 0.001) are necessary to materialize ambidextrous behaviours (Adj.R²â€¯= 0.529). Environmental dynamism does not moderate these relationships. While opening leadership (ß = 0.375;p < 0.01), organisational creativity (ß = 0.270;p < 0.05) and environmental dynamism (ß = 0.224;p < 0.1) are determinants of exploration, closing leadership (ß = 0.506;p < 0.001) and organisational creativity (ß = 0.529;p < 0.001) are determinants of exploitation. CONCLUSIONS: Head physicians' leadership style as well as organizational creativity play a pivotal role in materializing ambidextrous behaviours in wards.

Use of Health Apps and Wearable Devices: Survey Among Italian Associations for Patient Advocacy.

BACKGROUND: Technological tools such as Web-based social networks, telemedicine, apps, or wearable devices are becoming more widespread in health care like elsewhere. Although patients are the main users, for example, to monitor symptoms and clinical parameters or to communicate with the doctor, their perspective is seldom analyzed, and to the best of our knowledge, no one has focused on the patients' health care advocacy associations' point of view. OBJECTIVE: The objective of this study was to assess patients' health care advocacy associations' opinions about the use, usefulness, obstacles, negative aspects, and impact of health apps and wearable devices through a Web-based survey. METHODS: We conducted a Web-based survey through SurveyMonkey over nearly 3 months. Participants were contacted via an email explaining the aims of the survey and providing a link to complete the Web-based questionnaire. All the 20 items were mandatory, and the anonymized data were collected automatically into a database. Only fully completed questionnaires were considered for analysis. RESULTS: We contacted 1998 patients' health care advocacy associations; a total of 258 questionnaires were received back (response rate 12.91%), and 227 of the received questionnaires were fully completed (completion rate 88.0%). Informative apps, hospital apps for viewing medical reports or booking visits, and those for monitoring physical activity are the most used. They are considered especially useful to improve patients' engagement and compliance with treatment. Wearable devices to check physical activity and glycemia are the most widespread considering, again, their benefits in increasing patients' involvement and treatment compliance. For health apps and wearable devices, the main obstacles to their use are personal and technical reasons; the risk of overmedicalization is considered the most negative aspect of their constant use, while privacy and confidentiality of data are not rated a limitation. No statistical difference was found on stratifying the answers by responders' technological level (P=.30), age (P=.10), and the composition of the association's advisory board (P=.15). CONCLUSIONS: According to responders, health apps and wearable devices are sufficiently known and used and are considered potential supports for greater involvement in health management. However, there are still obstacles to their adoption, and the developers need to work to make them more accessible and more useful. The involvement of patients and their associations in planning services and products based on these technologies (as well as others) would be desirable to overcome these barriers and boost awareness about privacy and the confidentiality of data.