51,944 research outputs found

    Clinical Data Entry & Protocol Tracking System

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    CLINICAL DATA ENTRY & PROTOCOL TRACKING SYSTEM (CDEPT) is a software framework designed to provide the tools necessary to rapidly develop web based data entry and data management systems for clinical trails and medical research studies. A software framework defines a model, approach, procedures and tools for creating new protocols for clinical studies. As a framework this software is able to gain efficiency by providing standard approaches and tools for commonly needed capabilities such as construction of data entry routines, validation of data, audit trails and monitoring the completeness and timeliness of data collection. However, as a framework this software provides far greater flexibility, expandability and customization than is typical in a turnkey or off the shelf application. CDEPT is designed around a three-tiered software development model widely used on Internet. This model consists of browsers, web server and database servers. This software is mostly designed to run on two major browsers Internet Explorer and Netscape

    Examining adherence to activity monitoring devices to improve physical activity in adults with cardiovascular disease: A systematic review

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    Background Activity monitoring devices are currently being used to facilitate and monitor physical activity. No prior review has examined adherence to the use of activity monitoring devices amongst adults with cardiovascular disease. Methods Literature from June 2012 to October 2017 was evaluated to examine the extent of adherence to any activity monitoring device used to collect objective physical activity data. Randomized control trials comparing usual care against the use of an activity monitoring device, in a community intervention for adults from any cardiovascular diagnostic group, were included. A systematic search of databases and clinical trials registers was conducted using Joanna Briggs Institute methodology. Results Of 10 eligible studies, two studies reported pedometer use and eight accelerometer use. Six studies addressed the primary outcome. Mean adherence was 59.1% (range 39.6% to 85.7%) at last follow-up. Studies lacked equal representation by gender (28.6% female) and age (range 42 to 82 years). Conclusion This review indicates that current research on activity monitoring devices may be overstated due to the variability in adherence. Results showed that physical activity tracking in women and in young adults have been understudied

    Eliminating Central Line Infections and Spreading Success at High-Performing Hospitals

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    Synthesizes lessons in preventing central line-associated bloodstream infections, including the importance of evidence-based protocols, dedicated teams to oversee central line insertions, participation in collaboratives, and monitoring of infection rates

    Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

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    Health-related data analysis plays an important role in self-knowledge, disease prevention, diagnosis, and quality of life assessment. With the advent of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices (wearables, home-medical sensors, etc) facilitates data collection and provide cloud storage with a central administration. More recently, blockchain and other distributed ledgers became available as alternative storage options based on decentralised organisation systems. We bring attention to the human data bleeding problem and argue that neither centralised nor decentralised system organisations are a magic bullet for data-driven innovation if individual, community and societal values are ignored. The motivation for this position paper is to elaborate on strategies to protect privacy as well as to encourage data sharing and support open data without requiring a complex access protocol for researchers. Our main contribution is to outline the design of a self-regulated Open Health Archive (OHA) system with focus on quality of life (QoL) data.Comment: DSS 2018: Data-Driven Self-Regulating System

    Health-related preferences of older patients with multimorbidity: the protocol for an evidence map

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    Introduction: Interaction of conditions and treatments, complicated care needs and substantial treatment burden make patient–physician encounters involving multimorbid older patients highly complex. To optimally integrate patients’ preferences, define and prioritise realistic treatment goals and individualise care, a patient-centred approach is recommended. However, the preferences of older patients, who are especially vulnerable and frequently multimorbid, have not been systematically investigated with regard to their health status. The purpose of this evidence map is to explore current research addressing health-related preferences of older patients with multimorbidity, and to identify the knowledge clusters and research gaps. Methods and analysis: To identify relevant research, we will conduct searches in the electronic databases MEDLINE, EMBASE, PsycINFO, PSYNDEX, CINAHL, Social Science Citation Index, Social Science Citation Index Expanded and the Cochrane library from their inception. We will check reference lists of relevant articles and carry out cited reference research (forward citation tracking). Two independent reviewers will screen titles and abstracts, check full texts for eligibility and extract the data. Any disagreement will be resolved and consensus reached with the help of a third reviewer. We will include both qualitative and quantitative studies, and address preferences from the patients’ perspectives in a multimorbid population of 60 years or older. There will be no restrictions on the publication language. Data extraction tables will present study and patient characteristics, aim of study, methods used to identify preferences and outcomes (ie, type of preferences). We will summarise the data using tables and figures (ie, bubble plot) to present the research landscape and to describe clusters and gaps. Ethics and dissemination: Due to the nature of the proposed evidence map, ethics approval will not be required. Results from our research will be disseminated by means of specifically prepared materials for patients, at relevant (inter)national conferences and via publication in peer-reviewed journals
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