我國全民健康保險制度自2004年1月1日開始使用健保IC卡後，醫療資訊電子化的趨勢，某種意義上來說，已經如凱撒（Gaius Julius Caesar）渡過盧比孔河（Crossing the Ribucon）時所說：「骰子已經投下（the die is cast）」一般，只能前進不能後退了！ 時至今日，電腦、網路連線、憑證簽章已經成為任何一間醫療院所從事醫療行為時的開門七件事之一，民眾用健保IC掛號、醫師用電腦下診斷作病歷、行政人員用健保VPN申報費用等，皆成為醫療實務中的標準模式。而我國衛生署也信心滿滿地希望能於2011年達到全國80%醫院實施電子病歷、60%醫院可為院際交換互動之目標。在此「全民電子病歷」旋將施行之當下，相關隱私權之配套對於病人之保障是否足夠，即成為該政策是否受到國人支持之關鍵所在。 本研究透過整理衛生署自2000年迄今所有與電子病歷相關之專案計畫，以及與電子病歷領域，產、官、學界共9位受訪者進行深度訪談後發現，我國現行電子病歷政策推廣有架構、標準、法制、補助、動機等五大問題，其中關於法制規範及隱私保障不足所造成的民眾疑慮與醫事人員躊躇，已成為電子病歷發展上的一大阻礙，而其中計畫推行的電子病歷索引交互中心，更可能對於病人資訊隱私權產生重大危害與影響。另一方面，若回頭省視司法院大法官釋字第603號解釋，大法官們其實已對涵蓋電子病歷等個人資料之資訊隱私權，有過相當明確的闡釋。其所強調「個人自主控制其個人資料之資訊隱私權」，若能配合2010年5月26日修正通過但尚未施行之個人資料保護法，並非不能為電子病歷提供一個基本、框架式的法律基礎。 在此前提之下，本文提出「電子病歷自主控制機制」之概念，主張在現行憲法資訊隱私權之精神下，應該讓病人在充分瞭解到其權益後，得以選擇「是否將病歷電子化」、「電子病歷儲存場所」、「是否放於交換區」、「是否留存索引紀錄」、「是否允目的外利用」，並能透過管道隨時查詢其「電子病歷使用紀錄」。本文並認為，藉由「推力理論（Nudge）」中「自動加入（Opt-in）」與「主動加入（Opt-out）」等「預設值（Default）」概念之運用，資訊科技中「隱私偏好選項（Privacy Preference）」與「電子病歷使用紀錄明細」等系統之設立與使用，以及國際相關隱私及安全規範之借鏡，與我國健保IC卡推行之在地經驗，或許能夠解決論者對於電子病歷自主控制機制，在參與度、決定能力、行政成本、法規及技術架構、多元價值上的各項疑慮與爭論，並進而證明該構想之初步可行性。 / After implementation of the National Health Insurance (NHI) IC Card on January 1, 2004, the trend of e-health, including enforcing a national electronic medical record (EMR) system in Taiwan, is reminiscent of Julius Caesar’s words when he crossed the Rubicon, “The die is cast.” The return point has been passed; there is no return. Nowadays in Taiwan it has become routine in hospitals and clinics for medical practitioners to use a digital authentication or signature transmitted via a computer scan of an NHI IC card to register patients for diagnosis and treatment, and for administrtive staff using Virtual Private Network (VPN) to file fee claims. Furthermore, the Taiwan Department of Health has announced its implementation of the EMR system and has pledged that, in 2011, 80 percent of hospitals and clinics will start to use a more comprehensive EMR system and 60 percent of hospitals will be able to exchange EMRs. However, while Taiwan’s government is very proud and eager to enforce the EMR system, an increasing number of people doubt that adequate regulations have been put in place to protect against the violation of patients’ information privacy rights. This paper first reviews all former DOH projects related to EMRs, and interviews nine industry, government, and academic professionals who have EMR experience. It next argues that the current laws and regulations in Taiwan cannot provide sufficient protection of patients’ privacy rights, especially with regard to information privacy and autonomy. This is a cause for concern for patients and practitioners who are leery of further EMR implementation or development. This paper proposes a controlling mechanism for patients’ autonomy that will empower patients to determine if they want to electronize their medical records, where they will store their EMRs, and if it is in their best interests to set up an index and allow the transmission of additional EMRs. Moreover, patients will have unrestricted access to a log of all users and uses made of their EMRs and be able to set up their own privacy preferences with opt-in and opt-out choices. This paper concludes that the controlling mechanism for patients’ autonomy will solve the current concerns about the implemenation of a national EMR system and improve patients’ ability to enforce their information privacy and information autonomy rights.

A two-step model order reduction method is investigated in order to overcome problems of certain one-step methods. Not only optimal combinations of one-step reductions are considered but also the selection of a suitable intermediate dimension (ID) is described. Several automated selection methods are presented and their application tested on a gear box model. The implementation is realized using a Matlab-based Software MORPACK. Several recommendations are given towards the selection of a suitable ID, and problems in Model Order Reduction (MOR) combinations are pointed out. A pseudo two-step is suggested to reduce the full system without any modal information. A new node selection approach is proposed to enhance the SEREP approximation of the system’s response for small reduced representations. / Mehrschrittverfahren der Modellreduktion werden untersucht, um spezielle Probleme konventioneller Einschrittverfahren zu lösen. Eine optimale Kombination von strukturmechanischen Reduktionsverfahren und die Auswahl einer geeigneten Zwischendimension wird untersucht. Dafür werden automatische Verfahren in Matlab implementiert, in die Software MORPACK integriert und anhand des Finite Elemente Modells eines Getriebegehäuses ausgewertet. Zur Auswahl der Zwischendimension werden Empfehlungen genannt und auf Probleme bei der Kombinationen bestimmter Reduktionsverfahren hingewiesen. Ein Pseudo- Zweischrittverfahren wird vorgestellt, welches eine Reduktion ohne Kenntnis der modalen Größen bei ähnlicher Genauigkeit im Vergleich zu modalen Unterraumverfahren durchführt. Für kleine Reduktionsdimensionen wird ein Knotenauswahlverfahren vorgeschlagen, um die Approximation des Frequenzganges durch die System Equivalent Reduction Expansion Process (SEREP)-Reduktion zu verbessern.

A two-step model order reduction method is investigated in order to overcome problems of certain one-step methods. Not only optimal combinations of one-step reductions are considered but also the selection of a suitable intermediate dimension (ID) is described. Several automated selection methods are presented and their application tested on a gear box model. The implementation is realized using a Matlab-based Software MORPACK. Several recommendations are given towards the selection of a suitable ID, and problems in Model Order Reduction (MOR) combinations are pointed out. A pseudo two-step is suggested to reduce the full system without any modal information. A new node selection approach is proposed to enhance the SEREP approximation of the system’s response for small reduced representations.:Contents Kurzfassung..........................................................................................iv Abstract.................................................................................................iv Nomenclature........................................................................................ix 1 Introduction........................................................................................1 1.1 Motivation........................................................................................1 1.2 Objectives........................................................................................1 1.3 Outline of the Thesis........................................................................2 2 Theoretical Background.......................................................................3 2.1 Finite Element Method......................................................................3 2.1.1 Modal Analysis...............................................................................4 2.1.2 Frequency Response Function.......................................................4 2.2 Model Order Reduction.....................................................................5 2.3 Physical Subspace Reduction Methods.............................................7 2.3.1 Guyan Reduction...........................................................................7 2.3.2 Improved Reduced System Method...............................................8 2.4 Modal Subspace Reduction Methods...............................................10 2.4.1 Modal Reduction...........................................................................11 2.4.2 Exact Modal Reduction..................................................................11 2.4.3 System Equivalent Reduction Expansion Process.........................13 2.5 Krylov Subspace Reduction Methods...............................................14 2.6 Hybrid Subspace Reduction Methods..............................................15 2.6.1 Component Mode Synthesis........................................................16 2.6.2 Hybrid Exact Modal Reduction......................................................19 2.7 Model Correlation Methods.............................................................21 2.7.1 Normalized Relative Frequency Difference...................................21 2.7.2 Modified Modal Assurance Criterion.............................................22 2.7.3 Pseudo-Orthogonality Check.......................................................22 2.7.4 Comparison of Frequency Response Function.............................23 3 Selection of Active Degrees of Freedom............................................25 3.1 Non-Iterative Methods...................................................................26 3.1.1 Modal Kinetic Energy and Variants..............................................26 3.1.2 Driving Point Residue and Variants..............................................27 3.1.3 Eigenvector Component Product..................................................28 3.2 Iterative Reduction Methods...........................................................29 3.2.1 Effective Independence Distribution.............................................29 3.2.2 Mass-Weighted Effective Independence.......................................32 3.2.3 Variance Based Selection Method.................................................33 3.2.4 Singular Value Decomposition Based Selection Method................34 3.2.5 Stiffness-to-Mass Ratio Selection Method.....................................34 3.3 Iterative Expansion Methods...........................................................35 3.3.1 Modal-Geometrical Selection Criterion...........................................36 3.3.2 Triaxial Effective Independence Expansion...................................36 3.4 Measure of Goodness for Selected Active Set..................................39 3.4.1 Determinant and Rank of the Fisher Information Matrix................39 3.4.2 Condition Number of the Partitioned Modal Matrix........................40 3.4.3 Measured Energy per Mode..........................................................40 3.4.4 Root Mean Square Error of Pseudo-Orthogonality Check.............41 3.4.5 Eigenvalue Comparison................................................................41 4 Two-Step Reduction in MORPACK.......................................................42 4.1 Structure of MORPACK.....................................................................42 4.2 Selection of an Intermediate Dimension.........................................43 4.2.1 Intermediate Dimension Requirements........................................44 4.2.2 Implemented Selection Methods..................................................45 4.2.3 Recommended Selection of an Intermediate Dimension...............48 4.3 Combination of Reduction Methods.................................................49 4.3.1 Overview of All Candidates..........................................................50 4.3.2 Combinations with Modal Information.........................................54 4.3.3 Combinations without Modal Information....................................54 5 Applications........................................................................................57 5.1 Gear Box Model...............................................................................57 5.2 Selection of Additional Active Nodes................................................58 5.3 Optimal Intermediate Dimension......................................................64 5.4 Two-Step Model Order Reduction Results........................................66 5.5 Comparison to One-Step Model Order Reduction Methods..............70 5.6 Comparison to One-Step Hybrid Model Order Reduction Methods...72 5.7 Proposal of a New Approach for Additional Node Selection..............73 6 Summary and Conclusions...................................................................77 7 Zusammenfassung und Ausblick..........................................................79 Bibliography............................................................................................81 List of Tables..........................................................................................86 List of Figures.........................................................................................88 A Appendix.............................................................................................89 A.1 Results of Two-Step Model Order Reduction.....................................89 A.2 Data CD............................................................................................96 / Mehrschrittverfahren der Modellreduktion werden untersucht, um spezielle Probleme konventioneller Einschrittverfahren zu lösen. Eine optimale Kombination von strukturmechanischen Reduktionsverfahren und die Auswahl einer geeigneten Zwischendimension wird untersucht. Dafür werden automatische Verfahren in Matlab implementiert, in die Software MORPACK integriert und anhand des Finite Elemente Modells eines Getriebegehäuses ausgewertet. Zur Auswahl der Zwischendimension werden Empfehlungen genannt und auf Probleme bei der Kombinationen bestimmter Reduktionsverfahren hingewiesen. Ein Pseudo- Zweischrittverfahren wird vorgestellt, welches eine Reduktion ohne Kenntnis der modalen Größen bei ähnlicher Genauigkeit im Vergleich zu modalen Unterraumverfahren durchführt. Für kleine Reduktionsdimensionen wird ein Knotenauswahlverfahren vorgeschlagen, um die Approximation des Frequenzganges durch die System Equivalent Reduction Expansion Process (SEREP)-Reduktion zu verbessern.:Contents Kurzfassung..........................................................................................iv Abstract.................................................................................................iv Nomenclature........................................................................................ix 1 Introduction........................................................................................1 1.1 Motivation........................................................................................1 1.2 Objectives........................................................................................1 1.3 Outline of the Thesis........................................................................2 2 Theoretical Background.......................................................................3 2.1 Finite Element Method......................................................................3 2.1.1 Modal Analysis...............................................................................4 2.1.2 Frequency Response Function.......................................................4 2.2 Model Order Reduction.....................................................................5 2.3 Physical Subspace Reduction Methods.............................................7 2.3.1 Guyan Reduction...........................................................................7 2.3.2 Improved Reduced System Method...............................................8 2.4 Modal Subspace Reduction Methods...............................................10 2.4.1 Modal Reduction...........................................................................11 2.4.2 Exact Modal Reduction..................................................................11 2.4.3 System Equivalent Reduction Expansion Process.........................13 2.5 Krylov Subspace Reduction Methods...............................................14 2.6 Hybrid Subspace Reduction Methods..............................................15 2.6.1 Component Mode Synthesis........................................................16 2.6.2 Hybrid Exact Modal Reduction......................................................19 2.7 Model Correlation Methods.............................................................21 2.7.1 Normalized Relative Frequency Difference...................................21 2.7.2 Modified Modal Assurance Criterion.............................................22 2.7.3 Pseudo-Orthogonality Check.......................................................22 2.7.4 Comparison of Frequency Response Function.............................23 3 Selection of Active Degrees of Freedom............................................25 3.1 Non-Iterative Methods...................................................................26 3.1.1 Modal Kinetic Energy and Variants..............................................26 3.1.2 Driving Point Residue and Variants..............................................27 3.1.3 Eigenvector Component Product..................................................28 3.2 Iterative Reduction Methods...........................................................29 3.2.1 Effective Independence Distribution.............................................29 3.2.2 Mass-Weighted Effective Independence.......................................32 3.2.3 Variance Based Selection Method.................................................33 3.2.4 Singular Value Decomposition Based Selection Method................34 3.2.5 Stiffness-to-Mass Ratio Selection Method.....................................34 3.3 Iterative Expansion Methods...........................................................35 3.3.1 Modal-Geometrical Selection Criterion...........................................36 3.3.2 Triaxial Effective Independence Expansion...................................36 3.4 Measure of Goodness for Selected Active Set..................................39 3.4.1 Determinant and Rank of the Fisher Information Matrix................39 3.4.2 Condition Number of the Partitioned Modal Matrix........................40 3.4.3 Measured Energy per Mode..........................................................40 3.4.4 Root Mean Square Error of Pseudo-Orthogonality Check.............41 3.4.5 Eigenvalue Comparison................................................................41 4 Two-Step Reduction in MORPACK.......................................................42 4.1 Structure of MORPACK.....................................................................42 4.2 Selection of an Intermediate Dimension.........................................43 4.2.1 Intermediate Dimension Requirements........................................44 4.2.2 Implemented Selection Methods..................................................45 4.2.3 Recommended Selection of an Intermediate Dimension...............48 4.3 Combination of Reduction Methods.................................................49 4.3.1 Overview of All Candidates..........................................................50 4.3.2 Combinations with Modal Information.........................................54 4.3.3 Combinations without Modal Information....................................54 5 Applications........................................................................................57 5.1 Gear Box Model...............................................................................57 5.2 Selection of Additional Active Nodes................................................58 5.3 Optimal Intermediate Dimension......................................................64 5.4 Two-Step Model Order Reduction Results........................................66 5.5 Comparison to One-Step Model Order Reduction Methods..............70 5.6 Comparison to One-Step Hybrid Model Order Reduction Methods...72 5.7 Proposal of a New Approach for Additional Node Selection..............73 6 Summary and Conclusions...................................................................77 7 Zusammenfassung und Ausblick..........................................................79 Bibliography............................................................................................81 List of Tables..........................................................................................86 List of Figures.........................................................................................88 A Appendix.............................................................................................89 A.1 Results of Two-Step Model Order Reduction.....................................89 A.2 Data CD............................................................................................96

<p>Information technology (IT) has been applied in every aspect in common everyday experience. Most industries have changed from paper based to digitally supported processes. The implementation of IT has resulted in lower costs, faster operations, and faster response to consumer demands, thus achieving economies of scale and major advancements in the quality of products introduced to the consumer.</p> <p>In healthcare, IT has led to extensive advances in many different aspects of medicine. IT has enhanced diagnostic equipment, laboratory result accuracy, research methodologies and analysis advancements, and has resulted in more effective prescription of medications. These advances have increased the overall quality of life for patients.</p> <p>Despite the fact that the adoption rate of Electronic Medical Record systems (EMRs) in European countries has reached more than 90%, the adoption of EMRs by primary care physicians in Canada lags far behind at a rate closer to 30%. Much of this low adoption rate can be attributed to barriers due to resistance to change. Many adoption projects in IT fail, even after change has occurred. These failures have occurred in many different industries, including healthcare. EMR adoption in primary care requires a focus on change management and sustainability for primary care physicians, the target audience of change.</p> <p>This thesis research investigates the reasons for the low rate of adoption of EMRs in the primary care environment in Canada. A change management model dedicated to the Canadian primary healthcare environment for the management and sustainability of change is created and discussed in detail. This study is based on a thorough literature review of change management models; a qualitative analysis of interviews with industry leaders from different backgrounds such as consultancy, government, and vendors; and a quantitative analysis of data through an online primary care physician questionnaire.</p> / Master of Science (MSc)

No description available.

This thesis explores the field of context-aware information systems (CAIS). We present an approach called Compose, Learn, and Discover (CLD) to incorporate CAIS into the user daily workflow. The CLD approach is self-adjusting. It enables users to personalise the information views for different situations. The CAIS learns about the usage of the information views and recalls the right view in the right situation. We illustrate the CLD approach through an application in the health care field using the Clinical Document Architecture (CDA). In order to realise the CLD approach, we introduce Semantic Composition as a new paradigm to personalise information views. Semantic Composition leverages the type information in the domain model to simplify the user-interface composition process. We also introduce a pattern discovery mechanism that leverages data-mining algorithms to discover correlations between user information needs and different situations.

The implementation of electronic medical record (EMR) systems is a complex process that is receiving more focus in developing countries to support understaffed and overcrowded health facilities deal with the HIV/AIDS epidemic. This thesis research uses exploratory-grounded theory to study clinician perceived benefits of EMRs in antiretroviral therapy (ART) clinics at four hospitals in Ethiopia. The study is designed to understand the process, technology, social and organizational challenges associated with EMR implementation in resource-limited areas. The research found the attitude of ART clinicians towards the implementation of EMR systems to be overwhelmingly positive. The data showed that perceived benefits of EMRs are improved continuity of care, timely access to complete medical record, patient care efficiency, reduced medication errors, improved patient confidentiality, improved communication among clinicians, integration of various HIV programs, timely decision support and overall job motivation. Conversely, drawbacks to EMR implementation include productivity loss and negative impact on the interaction and relationship between clinicians and their patients. The study proposes a conceptual framework classifying key components for successful EMR implementation in Ethiopia.

La compréhension de la dynamique spatiale et temporelle des peuplements benthiques qu’elle soit naturelle et induite par des forçages anthropiques, nécessite de nouvelles méthodes d'observation du benthos avec des besoins affichés de haute résolution temporelle et de longues périodes de mesures. L'enregistrement et l’analyse des sons produits dans l’environnement marin donnent accès au paysage acoustique, et notamment à l’une de ses composantes biologiques la biophonie benthique. Observer les variabilités spatio-temporelles de cette biophonie benthique, afin de contribuer à l'évaluation de la structure, du fonctionnement, de l’état et des évolutions du compartiment benthique, constitue l'objectif principal de la thèse. Pour ce faire nous avons développé deux outils permettant d'évaluer la variabilité spatiale de ces émissions avec un ou plusieurs capteurs. Le premier est un descripteur de la forme des spectres des impulsions du benthos permettant de mieux caractériser la diversité de la biophonie benthique. Le second est une méthode de localisation tridimensionnelle des sources sonores benthiques et de cartographie de cette biophonie pour des échelles spatiales allant de 500 mètres jusqu’à 5 mètres. En utilisant ces deux outils, nous avons démontré la faisabilité de l'observation du benthos au travers de sa biophonie sur des sites spécifiques. Dans une partie applicative, nous nous sommes intéressés aux projets de site de production d’énergies marines renouvelables et à la compréhension et à l’observation de leurs impacts sur la faune marine. Sur un site atelier de géométrie similaire à celle d’une ferme d’éoliennes offshores, nous avons défini, réalisé et analysé une preuve de concept pour l’observabilité d’un effet de type binaire : présence ou absence de faune fixée dans une surface sentinelle de quelques mètres carré. Les travaux de thèse ont été conclus par une étude mesurant le niveau sonore rayonné par une hydrolienne en phase de production d’énergie (Paimpol-Bréhat) puis évaluant les impacts acoustiques sur trois compartiments biologiques : les mammifères marins, les poissons et les invertébrés. / Understanding the spatial and temporal dynamics of benthic populations, both natural and induced by anthropogenic pressures, requires new observation methods with high temporal resolution and long periods of measurement. The recording and analysis of sounds produced in the marine environment give access to the soundscape, and in particular to one of its biological components, the benthic biophony. Observing the spatiotemporal variability of this benthic biophony, in order to contribute to the evaluation of the structure, functioning, state and evolution of the benthic compartment, is the main objective of the thesis. To do this we have developed two tools to evaluate the spatial variability of these emissions with one sensor or more. The first is a descriptor of the shape of the spectra of the benthic snaps allowing to better characterize the diversity of benthic biophony. The second is a method of three-dimensional localization of the benthic sound sources and mapping of this biophony for spatial scales ranging from 500 meters to 5 meters. Using these two tools, we have demonstrated the feasibility of benthos monitoring through its biophony at specific sites. In an applicative part, we were interested in sites of production of marine renewable energies and the understanding and observation of their impacts on the marine fauna. On a workshop site of geometry similar to that of an offshore wind farm, we defined, realized and analyzed a proof of concept for the observability of a binary impact: presence or absence of fixed benthic fauna in a sentinel area of a few square meters. The thesis work was concluded by a study measuring the sound level radiated by a tidal current turbine in the energy production phase (Paimpol-Bréhat) and then evaluating the acoustic impacts on three biological compartments: marine mammals, fish and invertebrates.

Many of the technological and social systems our society has come to depend on can be classified as complex adaptive systems (CAS). These systems are made of many individual parts that self-organize to respond and adapt to changing outside and inside influences affecting the system and its actors. These CAS can be placed on a spectrum ranging from loosely- to tightly-coupled, depending on the degree of interrelatedness and interdependence between system components. This research has explored how the process of collaboration occurs in both a loosely- and tightly-coupled setting using one exemplar of each system. The loosely-coupled exemplar related to disaster risk reduction in two Canadian communities while the tightly-coupled one involved the implementation of a surgical information management system in a Canadian hospital. A list of core elements of collaboration that should be considered essential to the success of all collaborative endeavours was developed as a result: Engagement, Communication, Leadership, Role Clarity, Awareness, Time, and Technical Skills and Knowledge. Based on observing how the core elements of collaboration interacted with one another within each of these example systems, two models were created to represent their relationships. A list of considerations that collaborative tool designers should consider was also developed and the implications of these considerations were discussed. As businesses and other organizations increasingly incorporate team-based work models, they will come to depend more heavily on technology-based solutions to support collaboration. By incorporating collaborative technologies that properly support the activity of these teams—based on the specific type of complex adaptive system in which their organization exists—organizations can avoid wasting time and resources developing tools that hinder collaboration.

No description available.