Alcuni abstract di articoli che trattano argomenti relativi all'eHealth

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What Training, Support, and Resourcing Do Health Professionals Need to Support People Using a Closed-Loop System? A Qualitative Interview Study with Health Professionals Involved in the Closed Loop from Onset in Type 1 Diabetes (CLOuD) Trial.

Background: We explored health professionals' views about the training, support, and resourcing needed to support people using closed-loop technology in routine clinical care to help inform the development of formal guidance. Methods: Interviews were conducted with health professionals (n = 22) delivering the Closed Loop from Onset in Type 1 Diabetes (CLOuD) trial after they had ≥6 months' experience of supporting participants using a closed-loop system. Data were analyzed descriptively. Results: Interviewees described how, compared with other insulin regimens, teaching and supporting individuals to use a closed-loop system could be initially more time-consuming. However, they also noted that after an initial adjustment period, users had less need for initiating contact with the clinical team compared with people using pumps or multiple daily injections. Interviewees highlighted how a lessened need for ad hoc clinical input could result in new challenges; specifically, they had fewer opportunities to reinforce users' diabetes knowledge and skills and detect potential psychosocial problems. They also observed heightened anxiety among some parents due to the constant availability of data and unrealistic expectations about the system's capabilities. Interviewees noted that all local diabetes teams should be empowered to deliver closed-loop system care, but stressed that health professionals supporting closed-loop users in routine care will need comprehensive technology training and standardized clinical guidance. Conclusion: These findings constitute an important starting point for the development of formal guidance to support the rollout of closed-loop technology. Our recommendations, if actioned, will help limit the potential additional burden of introducing closed-loop systems in routine clinical care and help inform appropriate user education and support.NIHR Wellcome Trust Strategic Award (100574/Z/12/Z

Designing an educational interactive eBook for newly diagnosed children with type 1 diabetes: Mapping a new design space

peer-reviewedIn this paper, we report on a project investigating the role of Interactive Technologies (IT) and participatory design methods in supporting self-care practices in paediatric Type 1 Diabetes Mellitus (T1DM). In particular, we discuss the design of an educational interactive eBook to support newly diagnosed children and their families in learning about effective management outside the clinical–medical consultation. We use our design as an illustration of a potential new design space for type 1 diabetes learning resources. We map this space by identifying a series of oppositions that helps us to explore new design assumptions that could better support the education of newly diagnosed children and families: learning alone vs learning together, medical vs patient perspective, prescriptive language vs narratives and social stories, and static vs interactive educational contents. Through a discussion of these shifting of points of focus in the design of educational products in T1DM, we hope to open up new opportunities to rethink the design of tools to support the education of paediatric diabetes (and possibly of other chronic diseases and conditions)

Towards an Artificial Pancreas: Software Architectural Model and Implementation for Personalized Insulin Administration

Research on an Artificial Pancreas has gained its momentum and focused on the processing of clinical data for continuous insulin administration. However, the overall research is rather sketchy, fragmented and not very well coordinated. In this paper, we propose an architectural model for creating software intensive environments, which address deficiencies of current solutions for insulin infusion. A new way of defining which data should be collected and which types of computations should be performed with the data is important if we wish to come close to the functioning of a natural pancreas. An excerpt of the proposed software architecture has been deployed using Watson Analytics and performed upon a selection of data collected from sensors, individual patient’s input and persistent patient records

Consensus Recommendations for the Use of Automated Insulin Delivery (AID) Technologies in Clinical Practice

International audienceThe significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past six years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage

Applications of the Internet of Medical Things to Type 1 Diabetes Mellitus

Type 1 Diabetes Mellitus (DM1) is a condition of the metabolism typified by persistent hyperglycemia as a result of insufficient pancreatic insulin synthesis. This requires patients to be aware of their blood glucose level oscillations every day to deduce a pattern and anticipate future glycemia, and hence, decide the amount of insulin that must be exogenously injected to maintain glycemia within the target range. This approach often suffers from a relatively high imprecision, which can be dangerous. Nevertheless, current developments in Information and Communication Technologies (ICT) and innovative sensors for biological signals that might enable a continuous, complete assessment of the patient’s health provide a fresh viewpoint on treating DM1. With this, we observe that current biomonitoring devices and Continuous Glucose Monitoring (CGM) units can easily obtain data that allow us to know at all times the state of glycemia and other variables that influence its oscillations. A complete review has been made of the variables that influence glycemia in a T1DM patient and that can be measured by the above means. The communications systems necessary to transfer the information collected to a more powerful computational environment, which can adequately handle the amounts of data collected, have also been described. From this point, intelligent data analysis extracts knowledge from the data and allows predictions to be made in order to anticipate risk situations. With all of the above, it is necessary to build a holistic proposal that allows the complete and smart management of T1DM. This approach evaluates a potential shortage of such suggestions and the obstacles that future intelligent IoMT-DM1 management systems must surmount. Lastly, we provide an outline of a comprehensive IoMT-based proposal for DM1 management that aims to address the limits of prior studies while also using the disruptive technologies highlighted beforePartial funding for open access charge: Universidad de Málag

A personalised and adaptive insulin dosing decision support system for type 1 diabetes

People with type 1 diabetes (T1D) rely on exogenous insulin to maintain stable glucose levels. Despite the advent of diabetes technologies such as continuous glucose monitors and insulin infusion pumps, the majority of people with T1D do not manage to bring back glucose levels into a healthy target after meals. In addition to patient compliance, this is due to the complexity of the decision-making on how much insulin is required. Commercial insulin bolus calculators exist that help with the calculation of insulin for meals but these lack fine-tuning and adaptability. This thesis presents a novel insulin dosing decision support system for people with T1D that is able to provide individualised insulin dosing advice. The proposed research utilises Case-Based Reasoning (CBR), an artificial intelligence methodology, that is able to learn over time based on the behaviour of the patient and optimises the insulin therapy for various diabetes scenarios. The decision support system has been implemented into a user-friendly smartphone-based patient platform and communicates with a clinical platform for remote supervision. In-silico studies are presented demonstrating the overall performance of CBR as well as metrics used to adapt the insulin therapy. Safety and feasibility of the developed system have been assessed incrementally in clinical trials; initially during an eight-hour study in hospital settings followed by a six-week study in the home environment of the user. Human factors play an important role in the clinical adoption of technologies such as the one proposed. System usability and acceptability were evaluated during the second study phase based on feedback obtained from study participants. Results from in-silico tests show the potential of the proposed research to safely automate the process of optimising the insulin therapy for people with T1D. In the six-week study, the system demonstrated safety in maintaining glycemic control with a trend suggesting improvement in postprandial glucose outcomes. Feedback from participants showed favourable outcomes when assessing device satisfaction and usability. A six-month large-scale randomised controlled study to evaluate the efficacy of the system is currently ongoing.Open Acces

DoR Communicator - January 2014

The January 2014 issue of the Division of Research newsletter.https://digitalcommons.fiu.edu/research_newsletter/1007/thumbnail.jp

ORED Communicator - February 2015

The February 2015 issue of the Office of Research and Economic Development newsletter.https://digitalcommons.fiu.edu/research_newsletter/1006/thumbnail.jp

Program and Proceedings: The Nebraska Academy of Sciences 1880-2012

PROGRAM FRIDAY, APRIL 20, 2012 REGISTRATION FOR ACADEMY, Lobby of Lecture wing, Olin Hall Aeronautics and Space Science, Session A, Olin 249 Aeronautics and Space Science, Session B, Olin 224 Collegiate Academy, Biology Session A, Olin B Chemistry and Physics, Section A, Chemistry, Olin A Applied Science and Technology, Olin 325 Biological and Medical Sciences, Session A, Olin 112 Biological and Medical Sciences, Session B, Smith Callen Conference Center Junior Academy, Judges Check-In, Olin 219 Junior Academy, Senior High REGISTRATION, Olin Hall Lobby Chemistry and Physics, Section B, Physics, Planetarium Collegiate Academy, Chemistry and Physics, Session A, Olin 324 Junior Academy, Senior High Competition, Olin 124, Olin 131 Aeronautics and Space Science, Poster Session, Olin 249 NWU Health and Sciences Graduate School Fair, Olin and Smith Curtiss Halls Aeronautics and Space Science, Poster Session, Olin 249 MAIBEN MEMORIAL LECTURE, OLIN B Buffalo Bruce McIntosh, Research Ecologist with Western Nebraska Resources Council, The Status of Nebraska\u27s Native Aspen LUNCH, PATIO ROOM, STORY STUDENT CENTER (pay and carry tray through cafeteria line, or pay at NAS registration desk) Aeronautics Group, Conestoga Room Anthropology, Olin 111 Biological and Medical Sciences, Session C, Olin 112 Biological and Medical Sciences, Session D, Smith Callen Conference Center Chemistry and Physics, Section A, Chemistry, Olin A Chemistry and Physics, Section B, Physics, Planetarium Collegiate Academy, Biology Session A, Olin B Collegiate Academy, Biology Session B, Olin 249 Collegiate Academy, Chemistry and Physics, Session B, Olin 324 Earth Science, Olin 224 History/Philosophy of Science, Olin 325 Junior Academy, Judges Check-In, Olin 219 Junior Academy, Junior High REGISTRATION, Olin Hall Lobby Junior Academy, Senior High Competition, (Final), Olin 110 Teaching of Science and Math, Olin 325 Junior Academy, Junior High Competition, Olin 124, Olin 131 NJAS Board/Teacher Meeting, Olin 219 BUSINESS MEETING, OLIN B AWARDS RECEPTION for NJAS, Scholarships, Members, Spouses, and Guests First United Methodist Church, 2723 N 50th Street, Lincoln, N