4 research outputs found

    Software Architectures for Smart Applications in the Management of Chronic Diseases: A Study of Reversibility of Diabetes 2

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    The paper proposes a software architecture for applications which use the reasoning upon SWRL enabled OWL ontologies and SQL like retrievals as core computational models. The application assists patients affected by diabetes 2, to personalize the reversibility of the condition through the diet and life style changes. The novelty is in (a) the deployment of SWRL enabled OWL ontologies in the management of data related to the personalisation of reversibility of diabetes 2 and in (b) the proposed software architecture, which contains and manipulates the SWRL enabled OWL ontology and SQL databases at the same time and transparently. The application, which has been implemented within the Java environment and NetBeans, is reusable in any other problem domain when the personalization of healthcare delivery is required. The proposed architecture also generates applications within Android environments without changing its style and the computational models

    Exploiting Semantic Web Technologies to Develop OWL-Based Clinical Practice Guideline Execution Engines

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    Doctor of Philosophy

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    dissertationExchanging patient specific information across heterogeneous information systems is a critical but increasingly complex and expensive challenge. Lacking a universal unique identifier for healthcare, patient records must be linked using combinations of identity attributes such as name, date of birth, and sex. A state's birth certificate registry contains demographic information that is potentially very valuable for identity resolution, but its use for that purpose presents numerous problems. The objectives of this research were to: (1) assess the frequency, extent, reasons, and types of changes on birth certificates; (2) develop and evaluate an ontology describing information used in identity resolution; and (3) use a logical framework to model identity transactions and assess the impact of policy decisions in a cross jurisdictional master person index. To understand birth certificate changes, we obtained de identifified datasets from the Utah birth certifificate registry, including history and reasons for changes from 2000 to 2012. We conducted cohort analyses, examining the number, reason, and extent of changes over time, and cross sectional analyses to assess patterns of changes. We evaluated an ontological approach to overcome heterogeneity between systems exchanging identity information and demonstrated the use of two existing ontologies, the Simple Event Model (SEM) and the Clinical Element Model (CEM), to capture an individual's identity history. We used Discrete Event Calculus to model identity events iv across domains and over time. Models were used to develop contextual rules for releasing minimal information from birth certificate registries for sensitive cases such as adoptions. Our findings demonstrate that the mutability of birth certificates makes them a valuable resource for identity resolution, provided that changes can be captured and modeled in a usable form. An ontology can effectively model identity attributes and the events that cause them to change over time, as well as to overcome syntactic and semantic heterogeneity. Finally, we show that dynamic, contextual rules can be used to govern the flow of identity information between systems, allowing entities to link records in the most difficult cases, avoid costly human review, and avoid the threats to privacy that come from such review

    Front-Line Physicians' Satisfaction with Information Systems in Hospitals

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    Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe
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