21,880 research outputs found

    Modelling mobile health systems: an application of augmented MDA for the extended healthcare enterprise

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    Mobile health systems can extend the enterprise computing system of the healthcare provider by bringing services to the patient any time and anywhere. We propose a model-driven design and development methodology for the development of the m-health components in such extended enterprise computing systems. The methodology applies a model-driven design and development approach augmented with formal validation and verification to address quality and correctness and to support model transformation. Recent work on modelling applications from the healthcare domain is reported. One objective of this work is to explore and elaborate the proposed methodology. At the University of Twente we are developing m-health systems based on Body Area Networks (BANs). One specialization of the generic BAN is the health BAN, which incorporates a set of devices and associated software components to provide some set of health-related services. A patient will have a personalized instance of the health BAN customized to their current set of needs. A health professional interacts with their\ud patients¿ BANs via a BAN Professional System. The set of deployed BANs are supported by a server. We refer to this distributed system as the BAN System. The BAN system extends the enterprise computing system of the healthcare provider. Development of such systems requires a sound software engineering approach and this is what we explore with the new methodology. The methodology is illustrated with reference to recent modelling activities targeted at real implementations. In the context of the Awareness project BAN implementations will be trialled in a number of clinical settings including epilepsy management and management of chronic pain

    Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 192

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    This bibliography lists 247 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1979

    Automated Injection of Curated Knowledge Into Real-Time Clinical Systems: CDS Architecture for the 21st Century

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    abstract: Clinical Decision Support (CDS) is primarily associated with alerts, reminders, order entry, rule-based invocation, diagnostic aids, and on-demand information retrieval. While valuable, these foci have been in production use for decades, and do not provide a broader, interoperable means of plugging structured clinical knowledge into live electronic health record (EHR) ecosystems for purposes of orchestrating the user experiences of patients and clinicians. To date, the gap between knowledge representation and user-facing EHR integration has been considered an “implementation concern” requiring unscalable manual human efforts and governance coordination. Drafting a questionnaire engineered to meet the specifications of the HL7 CDS Knowledge Artifact specification, for example, carries no reasonable expectation that it may be imported and deployed into a live system without significant burdens. Dramatic reduction of the time and effort gap in the research and application cycle could be revolutionary. Doing so, however, requires both a floor-to-ceiling precoordination of functional boundaries in the knowledge management lifecycle, as well as formalization of the human processes by which this occurs. This research introduces ARTAKA: Architecture for Real-Time Application of Knowledge Artifacts, as a concrete floor-to-ceiling technological blueprint for both provider heath IT (HIT) and vendor organizations to incrementally introduce value into existing systems dynamically. This is made possible by service-ization of curated knowledge artifacts, then injected into a highly scalable backend infrastructure by automated orchestration through public marketplaces. Supplementary examples of client app integration are also provided. Compilation of knowledge into platform-specific form has been left flexible, in so far as implementations comply with ARTAKA’s Context Event Service (CES) communication and Health Services Platform (HSP) Marketplace service packaging standards. Towards the goal of interoperable human processes, ARTAKA’s treatment of knowledge artifacts as a specialized form of software allows knowledge engineers to operate as a type of software engineering practice. Thus, nearly a century of software development processes, tools, policies, and lessons offer immediate benefit: in some cases, with remarkable parity. Analyses of experimentation is provided with guidelines in how choice aspects of software development life cycles (SDLCs) apply to knowledge artifact development in an ARTAKA environment. Portions of this culminating document have been further initiated with Standards Developing Organizations (SDOs) intended to ultimately produce normative standards, as have active relationships with other bodies.Dissertation/ThesisDoctoral Dissertation Biomedical Informatics 201

    An Exploratory Study of Patient Falls

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    Debate continues between the contribution of education level and clinical expertise in the nursing practice environment. Research suggests a link between Baccalaureate of Science in Nursing (BSN) nurses and positive patient outcomes such as lower mortality, decreased falls, and fewer medication errors. Purpose: To examine if there a negative correlation between patient falls and the level of nurse education at an urban hospital located in Midwest Illinois during the years 2010-2014? Methods: A retrospective crosssectional cohort analysis was conducted using data from the National Database of Nursing Quality Indicators (NDNQI) from the years 2010-2014. Sample: Inpatients aged ≥ 18 years who experienced a unintentional sudden descent, with or without injury that resulted in the patient striking the floor or object and occurred on inpatient nursing units. Results: The regression model was constructed with annual patient falls as the dependent variable and formal education and a log transformed variable for percentage of certified nurses as the independent variables. The model overall is a good fit, F (2,22) = 9.014, p = .001, adj. R2 = .40. Conclusion: Annual patient falls will decrease by increasing the number of nurses with baccalaureate degrees and/or certifications from a professional nursing board-governing body

    Data science, analytics and artificial intelligence in e-health : trends, applications and challenges

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    Acknowledgments. This work has been partially supported by the Divina Pastora Seguros company.More than ever, healthcare systems can use data, predictive models, and intelligent algorithms to optimize their operations and the service they provide. This paper reviews the existing literature regarding the use of data science/analytics methods and artificial intelligence algorithms in healthcare. The paper also discusses how healthcare organizations can benefit from these tools to efficiently deal with a myriad of new possibilities and strategies. Examples of real applications are discussed to illustrate the potential of these methods. Finally, the paper highlights the main challenges regarding the use of these methods in healthcare, as well as some open research lines

    A Trial Examining an Advanced Practice Nurse Intervention to Promote Medication Adherence and Symptom Management in Adult Cancer Patients Prescribed Oral Anti-Cancer Agents: Study Protocol

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    Aim: To report a study protocol that refines then examines feasibility, preliminary efficacy, and satisfaction of ADHERE, an intervention using motivational interviewing and brief cognitive behavioral therapy as a mechanism for goal-oriented systematic patient education to promote symptom management and adherence among cancer patients prescribed oral anti-cancer agents. Background: Cancer treatment with oral anti-cancer agents shifts responsibility for managing treatment from clinicians in supervised cancer centers to patients and their caregivers. Thus, a need exists to standardize start-of-care for support patient self-management of care at home. Design: A two-phase quasi-experimental sequential design with repeated measures. Methods: Sixty five adult patients newly prescribed an oral anti-cancer agent will be recruited from three community cancer centers. Phase one will enroll 5 patients to refine the ADHERE intervention prior to testing, using an iterative process. After completion, Phase two will enroll 30 patients who receive usual care to examine symptoms and ahderence. Advanced practice nurses will then be trained. Then 30 patients will be enrolled in the intervention group and provided ADHERE, a 4-week intervention using semi-structured interactions (initial face-to-face session and once a week phone sessions over 3-weeks) and a Toolkit to promote self-management of care. Outcome measures include: oral anti-cancer agents adherence rate, symptom presence and severity, feasibility, and satisfaction with ADHERE. This protocol was approved January 2014 and is registered at ClinicalTrials.gov (Identifier NCT02337296). Discussion: This nurse-led intervention has the potential to standardize the start-of-care training for the patients to self-manage when prescribed oral anti-cancer agents for treatment

    Collaborative Interventions for Circulation and Depression (COINCIDE): study protocol for a cluster randomized controlled trial of collaborative care for depression in people with diabetes and/or coronary heart disease.

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    Published onlineJournal ArticleRandomized Controlled TrialResearch Support, Non-U.S. Gov'tBACKGROUND: Depression is up to two to three times as common in people with long-term conditions. It negatively affects medical management of disease and self-care behaviors, and leads to poorer quality of life and high costs in primary care. Screening and treatment of depression is increasingly prioritized, but despite initiatives to improve access and quality of care, depression remains under-detected and under-treated, especially in people with long-term conditions. Collaborative care is known to positively affect the process and outcome of care for people with depression and long-term conditions, but its effectiveness outside the USA is still relatively unknown. Furthermore, collaborative care has yet to be tested in settings that resemble more naturalistic settings that include patient choice and the usual care providers. The aim of this study was to test the effectiveness of a collaborative-care intervention, for people with depression and diabetes/coronary heart disease in National Health Service (NHS) primary care, in which low-intensity psychological treatment services are delivered by the usual care provider - Increasing Access to Psychological Therapies (IAPT) services. The study also aimed to evaluate the cost-effectiveness of the intervention over 6 months, and to assess qualitatively the extent to which collaborative care was implemented in the intervention general practices. METHODS: This is a cluster randomized controlled trial of 30 general practices allocated to either collaborative care or usual care. Fifteen patients per practice will be recruited after a screening exercise to detect patients with recognized depression (≥10 on the nine-symptom Patient Health Questionnaire; PHQ-9). Patients in the collaborative-care arm with recognized depression will be offered a choice of evidence-based low-intensity psychological treatments based on cognitive and behavioral approaches. Patients will be case managed by psychological well-being practitioners employed by IAPT in partnership with a practice nurse and/or general practitioner. The primary outcome will be change in depressive symptoms at 6 months on the 90-item Symptoms Checklist (SCL-90). Secondary outcomes include change in health status, self-care behaviors, and self-efficacy. A qualitative process evaluation will be undertaken with patients and health practitioners to gauge the extent to which the collaborative-care model is implemented, and to explore sustainability beyond the clinical trial. DISCUSSION: COINCIDE will assess whether collaborative care can improve patient-centered outcomes, and evaluate access to and quality of care of co-morbid depression of varying intensity in people with diabetes/coronary heart disease. Additionally, by working with usual care providers such as IAPT, and by identifying and evaluating interventions that are effective and appropriate for routine use in the NHS, the COINCIDE trial offers opportunities to address translational gaps between research and implementation. TRIAL REGISTRATION NUMBER: ISRCTN80309252 TRIAL STATUS: Open.NIHR Collaboration for Leadership in Applied Health Research and Care for Greater Mancheste
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