Cette thèse vise à contribuer à la compréhension des cycle de vie d’une opération humanitaire (HOLC). Gestion de la chaîne d'approvisionnement humanitaire (HSCM) dans un contexte de mise en perspective et dans l’objectif de proposer un modèle décisionnel qui s'applique aux phases de HOLC lors d’une situation réelle. Cela inclut la mise en oeuvre du modèle proposé pour concevoir et développer un outil d'aide à la décision afin d'améliorer les performances de la logistique humanitaire tant dans les opérations de secours nationaux qu’internationaux.Cette recherche est divisée en trois phases. La première partie vise à présenter le sens de l'étude ; la zone de recherche prise en compte pour la gestion de la chaîne d'approvisionnement (SCM) doit être clairement définie. La première phase consiste à clarifier et définir le HSCM HL, la gestion de la chaîne d'approvisionnement commerciale (CSCM) et le SCM, ainsi que la relation entre ces différents éléments. La gestion du cycle de vie du projet (PLCM) et les différentes approches sont également présentés. La compréhension de la différence entre la gestion du cycle de vie du projet (PLM) et la PLCM est également nécessaire, cela ne peut être abordé dans la phase de cycle de vie de l'opération humanitaire. De plus, les modèles Multiple-Criteria Decision Making (MCDM) et l’aide à la décision concernant le HL sont analysés pour établir le fossé existant en matière de recherche. Les approches MCDM qui mettent en oeuvre le système d'aide à la décision (DSS) et la manière dont le MAS a été utilisé dans le contexte HSCM sont étudiées.La deuxième phase consiste en la proposition d’un modèle décisionnel fondé sur l’approche MCDM à l'appui de la décision du décideur avant qu'il/elle prenne des mesures. Ce modèle prévoit le classement des alternatives concernant l'entrepôt, le fournisseur et le transport au cours des phases de HOLC. Le modèle décisionnel proposé est réalisée en 3 scénarios. I. La décision en 4phases HOLC – opération de secours internationale de la Croix-Rouge Française (CRF). II. La décision en3phases HOLC – opération nationale dela Croix-Rouge thaïlandaise (TRC). III. La décision au niveau de la phase de réponse HOLC – opération internationale du TRC dans quatre pays. Dans cette phase, le scénario I et II sont réalisés étape par étape au travers de calculs numériques et formules mathématiques. Le scénario III sera présenté dans la troisième phase. Pour établir trois scénarios, les données internes recueillies lors des entretiens avec le chef de la logistique de la Croix-Rouge Française, et le vice-président de la fondation de la Coix-Rouge thaïlandaise, seront utilisées. Les données externes proviennent de chercheurs qui sont des experts dans le domaine HL ou le champ du HSCM, de la littérature, et de sources issues des organismes humanitaires (documents d’ateliers, rapports, informations publiées sur leurs sites officiels).Dans la troisième phase, une application Internet multi-critères (decision support system MCDSS WB) mettant en oeuvre le modèle proposé est élaborée. Afin d'atteindre une décision appropriée en temps réel, le WB-MCDSS est développé sur la base d’un protocole client-serveur et est simple à utiliser. Le dernier mais non le moindre ; une application de validation du modèle est réalisée à l'aide de l'approche de l'analyse de sensibilité. / This thesis aims to contribute to the understanding of HOLC in context of the HSCM and to propose a decision model which applies to the phases of HOLC the decision making regarding a real situation . This include the implementation of the proposed model to design and develop a decision support tool in order to improve the performance of humanitarian logistics in both national and international relief operations.This research is divided into three phases; the first phase is to clarify and define HL among HSCM, commercial supply chain management (CSCM) and SCM and their relationship. Project Life Cycle Management (PLCM) approaches are also presented. The difference between project life cycle management (PLM) and PLCM is also required to distinguish a clear understanding which can be addressed in the phase of humanitarian operation life cycle. Additionally, the literature of Multiple-Criteria Decision Making (MCDM) models and existing decision aid system for HL are analyzed to establish the research gap. The MCDM approaches which implement the decision support system (DSS) and lastly how DSS has been used in the HSCM context.The second phase is to propose a decision model based on MCDM approaches to support the decision of the decision maker before he/she takes action. This model provides the ranking alternatives to warehouse, supplier and transportation over the phases of HOLC. The proposed decision model is conducted in 3 scenarios; I. The decision in 4-phase HOLC, international relief operation of French Red Cross (FRC). II. The decision on 3-phase HOLC, national operation by the Thai Red Cross (TRC). III. The decision on response phase HOLC, international operation by the FRC in four countries. In this phase, the scenario I and II are performed step by step though numerical calculation and mathematical formulas. The scenario III will be presented in the third phase.In the third phase, an application of web-based multi-criteria decision support system (WB-MCDSS) which implement the proposed model is developed. The web-based multi-criteria decision support system is developed based on the integration of analytical hierarchy process (AHP) and TOPSIS approaches. In order to achieve an appropriate decision in a real time response, the WB-MCDSS is developed based on server-client protocol and is simple to operate. Last but not least, a validation application of the model is performed using the sensitivity analysis approach.

La prise en charge des flux des patients, en particulier les flux récurrents et consécutifs à des crises sanitaires (grippes, canicules, situations exceptionnelles) est l'un des problèmes les plus importants auquel les services des urgences (SU) doivent faire face. Pour gérer cet afflux de patients, les services des urgences nécessitent des ressources humaines et matérielles importantes, ainsi qu'un degré élevé de coordination entre ces ressources. Dans ces conditions, le personnel médical se voit confronté très fréquemment à des situations de tension qui compliquent très fortement sa tâche. L‘objet de cette thèse est de contribuer à l’amélioration de la gestion des situations de tension se produisant dans un service d’urgence en proposant un système d’aide à la décision, SAGEST (Système d’Aide à la décision pour la GEstion des Situations de Tensions), permettant i) le pilotage proactif du SU : prévision à court et/ou moyen terme de l'apparition de situations de tension et l'évolution du flux patients et la proposition d'actions de correction afin d'éviter l’occurrence de ces situations et ii) le pilotage réactif dans le cas où l'occurrence de la situation de tension n'a pas été détectée. Une architecture fonctionnelle du système SAGEST, s'appuyant sur le processus décisionnel du responsable du service d'urgence, est proposée. Les méthodologies et les modèles utilisés dans la construction des principales fonctions et de la base de connaissances sont décrits. Enfin, les résultats d’application des différents modèles du système SAGEST pour le service d’urgence pédiatrique (SUP) du centre hospitalier régional universitaire du Lille sont présentés et discutés. / The management of patient flow, especially the flow resulting from health (flu, heat waves and exceptional circumstances) is one of the most important problems to manage in the emergency department (ED). To handle the influx of patients, emergency departments require significant human and material resources, and a high degree of coordination between these resources. Under these conditions, the medical and the paramedical staffs are often confronted with strain situations which greatly complicate their task. The main purpose of this thesis is to contribute to improving the management of situations of tension occurring in the emergency department by providing a decision support system, SAGEST. This DSS allows i) a proactive control of the ED: predicting at short and/or medium-term the occurrence of potential strain situations and proposing corrective actions to prevent the occurrence of these situations, ii) a reactive control in the case of no-detection of the strain situation occurrence. A functional architecture of the SAGEST system, based on the manager’s decision making process is proposed. Used methodologies and models embedded in the main functions and the knowledge base of the SAGEST system are described. Finally, experiments and results of different models of SAGEST system applied to the paediatric emergency department (PED) of the Regional University Hospital of Lille are presented and discussed.

Digital nudging is a relatively new phenomenon that is increasingly mentioned and demanded in human-computer interaction. The concept originates from behavioral economics and aims to help individuals make better decisions that are beneficial to the individual as well as the society, by making subtle changes to the environment in which the decision is made. Nudging implies to pushing people in the right direction and affecting them in different types of decision making. Digital nudging aims at applying the user interface design element to guide people's decisions in digital environments. This thesis presents a study of digital nudging in the form of the six design principles in the user interface of e-commerce sites through the method cognitive walkthrough. It is based on theories of mainly digital nudging but also persuasive design and user experience with connections to psychological aspects. The conclusion of the study has shown that principles in digital nudging exists in e-stores interfaces. The study aims to develop frameworks for an alternative way of implementing digital nudging and to contribute to more knowledge in the field. / Digital nudging är ett relativt nytt fenomen som blir allt mer omtalat och efterfrågat inom människa-datorinteraktion. Begreppet har sitt ursprung från beteendeekonomi och syftar till att få individer att ta bättre beslut som är gynnsamma för den enskilda individen såväl som samhället, genom att göra subtila ändringar i den miljön där beslutet fattas. Nudging innebär att knuffa individer i rätt riktning och att på så sätt påverka individer i olika beslutsfattanden. Digital nudging avser tillämpning av designelement i användargränssnittet för att påverka människors beslutsfattande i digitala miljöer. Studien presenterar en undersökning av de sex designprinciperna inom digital nudging och hur de påträffas i e-butikers användargränssnitt genom metoden kognitiv genomgång. Undersökningen grundar sig på teorier om digital nudging och relaterad forskning som övertygande design och användarupplevelse med kopplingar till psykologiska aspekter. Slutsatsen av studien har visat att designprinciper inom digital nudging förekommer i e-butikers gränssnitt. Studien syftar till att ta fram ramverk för ett alternativt sätt att implementera digital nudging och för att bidra till mer kunskap inom området.

Abstract Background Cardiovascular disease (CVD) has an enormous impact on the lives and health of New Zealanders. There is substantial epidemiological evidence that supports identifying people at high risk of CVD and treating them with lifestyle and drug-based interventions. If fully implemented, this targeted high risk approach could reduce future CVD events by over 50%. Recent studies have shown that a formal CVD risk assessment to the systematically identify high risk patients is rarely done in routine New Zealand general practice and audits of CVD risk management have shown large evidence-practice gaps. The CVD risk prediction score recommended by New Zealand guidelines for identifying high CVD risk patients was derived from the US Framingham Heart Study using data collected between the 1960s and 1980s. This score has only modest prediction accuracy and there are particular concerns about it’s validity for New Zealand sub-populations such as high risk ethnic groups or people with diabetes. Aims The overall aims of this thesis were to investigate the potential of a computerised decision support system (CDSS) to improve the assessment and management of CVD risk in New Zealand general practice while simultaneously developing a sustainable cohort study that could be used for validating and improving CVD risk prediction scores and related research. Methods An environmental scan of the New Zealand health care setting’s readiness to support a CDSS was conducted .The epidemiological evidence was reviewed to assess the effect of decision support systems on the quality of health care and the types and functionality of systems most likely to be successful. This was followed by a focused systematic review of randomised trials evaluating the impact of CDSS on CVD risk assessment and management practices and patient CVD outcomes in primary care. A web-based CDSS (PREDICT) was collaboratively developed. This rules-based provider-initiated system with audit and feedback and referral functionalities was fully integrated with general practice electronic medical records in a number of primary health organisations (PHOs). The evidence-based content was derived from national CVD and diabetes guidelines. When clinicians used PREDICT at the time of a consultation, treatment recommendations tailored to the patient’s CVD and diabetes risk profile were delivered to support decision-making within seconds. Simultaneously, the patient’s CVD risk profiles were securely stored on a central server. With PHO permission, anonymised patient data were linked via encrypted patient National Health Index numbers to national death and hospitalisation data. Three analytical studies using these data are described in this thesis. The first evaluated changes in GP risk assessment practice following implementation of PREDICT; the second investigated patterns of use of the CDSS by GPs and practice nurses; and the third describes the emerging PREDICT cohort and a preliminary validation of risk prediction scores. Results Given the rapid development of organised primary care since the 1990’s, the high degree of general practice computerisation and the New Zealand policy (health, informatics, privacy) environment, the introduction of a CDSS into the primary care setting was deemed feasible. The evidence for the impact of CDSS in general has been moderately favourable in terms of improving desired practice. Of the randomised trials of CDSS for assessing or managing CVD risk, about two-thirds reported improvements in provider processes and two-fifths reported some improvements in intermediate patient outcomes. No adverse effects were reported. Since 2002, the PREDICT CDSS has been implemented progressively in PHOs within Northland and the three Auckland regional District Health Board catchments, covering a population of 1.5 million. A before-after audit conducted in three large PHOs showed that CVD risk documentation increased four fold after the implementation of PREDICT. To date, the PREDICT dataset includes around 63,000 risk assessments conducted on a cohort of over 48,000 people by over 1000 general practitioners and practice nurses. This cohort has been followed from baseline for a median of 2.12 years. During that time 2655 people died or were hospitalised with a CVD event. Analyses showed that the original Framingham risk score was reasonably well calibrated overall but underestimated risk in high risk ethnic groups. Discrimination was only modest (AUC 0.701). An adjusted Framingham score, recommended by the New Zealand Guideline Group (NZGG) overestimated 5-year event rates by around 4-7%, in effect lowering the threshold for drug therapy to about 10% 5-year predicted CVD risk. The NZGG adjusted score (AUC 0.676) was less discriminating than the Framingham score and over-adjusted for high risk ethnic groups. For the cohort aged 30-74 years, the NZGG-recommended CVD risk management strategy identified almost half of the population as eligible for lifestyle management +/- drug therapy and this group generated 82% of all CVD events. In contrast the original Framingham score classified less than one-third of the cohort as eligible for individualised management and this group generated 71% of the events that occurred during follow-up. Implications This research project has demonstrated that a CDSS tool can be successfully implemented on a large scale in New Zealand general practice. It has assisted practitioners to improve the assessment and management of CVD at the time of patient consultation. Simultaneously, PREDICT has cost-effectively generated one of the largest cohorts of Māori and non-Māori ever assembled in New Zealand. As the cohort grows, new CVD risk prediction scores will be able to be developed for many New Zealand sub-populations. It will also provide clinicians and policy makers with the information needed to determine the trade-offs between the resources required to manage increasing proportions of the populations and the likely impact of management on preventing CVD events.

Den ökade globaliseringen och senaste finanskrisen ställer höga krav på uppföljning och medvetenhet av ett företags prestation. Business Intelligence (BI) är ett område vars syfte är att förbättra en organisations prestation genom analys av historisk data. BI är ett komplext område som inte bara handlar om tekniska lösningar, även om det är en förutsättning. För närvarande investeras det mycket i olika BI-lösningar och företagen behöver veta vad resurserna bör läggas på. I dagsläget finns det ingen modell som bedömer ett företags arbete med Business Intelligence utifrån ett flertal dimensioner. Syftet med den här studien var att utveckla en mognadsmodell för Business Intelligence och sedan jämföra de undersökta företagen Axfood, Scania och Systembolagets mognad. För att uppnå studiens syfte avsåg vi att besvara följande frågeställningar, ”Hur skulle en modell för att bedöma ett företags mognad inom Business Intelligence kunna se ut?” samt ”Vilka förutsättningar påverkar ett företags mognad inom Business Intelligence”. Mognadsmodellen (BIOMA) kom att bestå av fyra hörnstenar som i sin tur delades in i en eller flera underkategorier. Varje delkategori ger poäng som sedan infogas i ett koordinatsystem där axlarna motsvarar hörnstenarna och poängen utgår från origo. Att mäta ett företags mognad inom BI är komplext, då ett antal aspekter såsom organisationsstruktur, användarmedverkan samt klyftan mellan IT-avdelning och verksamhet kan påverka. Den teoretiska modellen är empiriskt testad. Respondenterna på respektive företag har bedömt hur långt de kommit inom varje hörnsten samt ge synpunkter på modellens utformning. Modellen har sedan förädlats utifrån det empiriska materialet. Vi anser att BIOMA har ett stort värde då det saknas en modell som visuellt och relativt enkelt beskriver ett företags mognad inom Business Intelligence. Modellen kan användas i olika syften, såsom benchmarking mellan processer och företag, säljstöd för konsulter samt vid förstudie för att klargöra ett företags nuläge. / The increased globalization and the recent financial crisis have put high demands on the monitoring and awareness of an organization's performance. Business Intelligence (BI) is an area which aims to improve this performance through analysis of historical data. BI is a complex question for organization’s because it involves more than just technical solutions for maximum performance. Organizations are currently investing in different BI solutions and a list of priorities has to be made to ensure balanced resource allocation within a BI-implementation. To this day no single business intelligence model exists that can adequately measure a company’s work from several perspectives. The purpose of this study was to develop a maturity model for BI and use it in a case study of three different well-known Swedish companies; Axfood, Scania and Systembolaget, to measure their BI-maturity. To achieve the purpose of the study, three distinct research questions arose; "What would a model for measuring a company’s Business Intelligence maturity look like? How would this model be constructed? And finally “What conditions could potentially affect an organization’s maturity in Business Intelligence?". The Maturity Model BIOMA (Business Intelligence Organizational Maturity Analysis) is made up of four categories, which in turn are divided into one or more sub-categories. A subcategory consists of several statements. Each statement carries a certain number of points. When the points are combined, the summarized amount is inserted into a coordinate system. Within this, the axies correspond to the pillars and the score is based on the origo-point. Measuring a company's BI-maturity is a complex research question, where a number of aspects such as organizational structure, end-user involvement, and the gap between IT department and business can be of great importance. BIOMA was empirically tested in the case study. The responders in each company judged their company based on the statements in each subcategory. Following this they made suggestions on ways to change the model. By applying these suggestions to the original material, the model was then redeveloped to create a final version. The model can be used for various purposes, such as processes within organizations or in benchmarking. It can also be used by consultants in Sales support as a pilot study for clarifying a company’s present BI-maturity. In this absence of a model that could visually describe a company’s BI maturity multidimensionally, we believe that BIOMA has substantial and existing business potential.

Der Einsatz numerischer Simulationen zur Bearbeitung klinischer Fragestellungen ist eine innovative Vorgehensweise. Im Rahmen der vorliegenden Arbeit wurde eine Methode zur Auswertung von Ergebnissen einer Finite-Elemente-Analyse zum Stentgraftverhalten konzipiert, implementiert und im Rahmen einer deutschlandweiten Benutzerstudie getestet. Für einen Vergleich unterschiedlicher Stentgraftkonfigurationen im Kontext mit dem patientenspezifischen Gefäß wurden Stentgraftbewertungsgrößen eingeführt. Hierzu gehören die Fixierungskraft und der Kontaktstatus zwischen Stentringen und Blutgefäßbestandteilen. Für eine Bereitstellung der Ergebnisgrößen im gefäßmedizinischen Arbeitsumfeld wurde eine graphische Mensch-Maschine-Schnittstelle entwickelt. Diese ermöglicht eine quantitative und qualitative Auswertung von Stentgraftbewertungsgrößen. Hierfür wurden Module zur automatisierten Auswertung von Fixierungskräften sowie zur 2D- und 3D- Ergebnisvisualisierung implementiert. Im Rahmen der Benutzerstudie wurde die Anwendung der entwickelten Methode für die Ermittlung des Einsatzpotenzials numerischer Simulationen zur Unterstützung der Stentgraftauswahl demonstriert. Im Ergebnis wurde als wesentliches Einsatzpotenzial die Festlegung eines Mindestmaßes an Überdimensionierung, die Optimierung der Schenkellänge sowie der Ver- gleich unterschiedlicher Stentgraftdesigns ermittelt. Weiterhin konnten grundlegende Anforderungen an ein System zur Generierung und Bewertung von Stentgraftkonfigurationen im klinischen Alltag definiert werden. Zu den wesentlichen Funktionen, die der Implanteur für einen Vergleich von Stentgrafts benötigt, zählen eine Übersichtskarte zu farbkodiertem Migrationsrisiko pro Stentgraft und Landungszone, die Visualisierung des Abdichtungszustandes der Stentkomponenten sowie die Darstellung von Stentgraft- und Gefäßdeformationen im 3D-Modell.

Η πληροφοριακή υπερφόρτωση των χρηστών αποτελεί βασικό πρόβλημα ενός οργανισμού. Η συσσώρευση μεγάλου όγκου πληροφορίας στα πληροφοριακά συστήματα, προκαλεί στους χρήστες άγχος και υπερένταση, με αποτέλεσμα να δυσχεραίνει την ικανότητά τους για λήψη αποφάσεων. Λόγω αυτού, η επίδραση της πληροφοριακής υπερφόρτωσης στους οργανισμούς είναι καταστροφική και απαιτείται η αντιμετώπισή της. Υπάρχουν διάφοροι τρόποι αντιμετώπισης της πληροφοριακής υπερφόρτωσης όπως τα συστήματα υποστήριξης λήψης αποφάσεων, τα συστήματα φιλτραρίσματος πληροφορίας, οι αποθήκες δεδομένων και άλλες τεχνικές της εξόρυξης δεδομένων και της τεχνητής νοημοσύνης, όπως είναι οι ευφυείς πράκτορες. Οι ευφυείς πράκτορες αποτελούν εφαρμογές που εφάπτονται της τεχνικής νοημοσύνης, οι οποίες έχουν την ικανότητα να δρουν αυτόνομα, συλλέγοντας πληροφορίες, εκπαιδεύοντας τον εαυτό τους και επικοινωνώντας με τον χρήστη και μεταξύ τους. Συχνά, υλοποιούνται πολυπρακτορικά συστήματα προκει-μένου να επιλυθεί ένα πρόβλημα του οργανισμού. Στόχος τους είναι να διευκολύνουν τη λήψη αποφάσεων των χρηστών, προτείνοντας πληροφορίες βάσει των προτιμήσεών τους. Ο σκοπός της παρούσας διπλωματικής εργασίας είναι να αναλύσει σε βάθος τους ευφυείς πράκτορες, σαν μία αποτελεσματική μέθοδο αντιμετώπισης της πληροφοριακής υπερφόρτωσης, να προτείνει πειραματικούς πράκτορες προτά-σεων και να εξετάσει επιτυχημένες υλοποιήσεις. Συγκεκριμένα, παρουσιάζεται ένα ευφυές σύστημα διδασκαλίας για την ενίσχυση του e-Learning/e-Teaching, προτείνεται ένα σύστημα πρακτόρων για τον οργανισμό Flickr, ενώ εξετάζεται το σύστημα προτάσεων του Last.fm και ο αλγόριθμος προτάσεων του Amazon. Τέλος, αναλύεται μια πειραματική έρευνα ενός ευφυούς πράκτορα προτάσεων, ο οποίος αντιμετώπισε με επιτυχία την αντιληπτή πληροφοριακή υπερφόρτωση των χρηστών ενός θεωρητικού ηλεκτρονικού καταστήματος. Τα αποτελέσματα του πειράματος παρουσίασαν την επίδραση της αντιληπτής πληροφοριακής υπερφόρτωσης και του φορτίου πληροφορίας στην ποιότητα επιλογής, στην εμπιστοσύνη επιλογής και στην αντιληπτή αλληλεπίδραση μεταξύ ηλεκτρονικού καταστήματος και χρήστη, ενώ παρατηρήθηκε η καθοριστική συμβολή της χρήσης των ευφυών πρακτόρων στην αντιμετώπιση της πληροφοριακής υπερφόρτωσης. / -

No description available.

The application of environmental performance indicators (EPIs) has received increasing attention by both governments and international organisations as a tool for assessing complex environmental scenarios in national and local decision making processes. However, at the regional scale there is a gap in the application of EPIs, as this has not been well understood and defined due to a limited theoretical foundation and often insufficient data from all participant countries. The regional scale is important because it can incorporate natural ecosystems which often transcend national boundaries. A case study is developed for the Lower Mekong Subregion (LMS), where four riparian Southeast Asian countries (Lao PDR, Thailand, Cambodia, and Viet Nam) share the Lower Mekong River. The research proposes a conceptual framework to identify approaches for developing criteria for acceptable and appropriate EPIs which can be used to support and implement decision making processes by relevant organisations at the regional level. This research evaluates the application of environmental performance indicators using methodologies that assess cross-national quantitative and qualitative data and existing decision support systems. In addition, global and national indicators are examined for application and relation to the regional context. The research finds that the application of EPIs varies according to spatial scale, and is diverse among the four countries. Data availability is also identified as a major problem encountered during the development and selection of EPIs. The study finds that the governance of the existing regional body is ineffective due to differing agendas pursued by each participating country. This is because the current regional body is structured only to facilitate information exchange and cooperation in a limited manner, focusing so far only on water management issues. LMS regional goals need to be set in order to guide the stakeholders in identifying an appropriate set of EPIs. Most importantly, the research is intended to be a catalyst for encouraging the participants to integrate methods and other species of EPIs proposed in this research in their environmental assessment policies.

Abstract Background Cardiovascular disease (CVD) has an enormous impact on the lives and health of New Zealanders. There is substantial epidemiological evidence that supports identifying people at high risk of CVD and treating them with lifestyle and drug-based interventions. If fully implemented, this targeted high risk approach could reduce future CVD events by over 50%. Recent studies have shown that a formal CVD risk assessment to the systematically identify high risk patients is rarely done in routine New Zealand general practice and audits of CVD risk management have shown large evidence-practice gaps. The CVD risk prediction score recommended by New Zealand guidelines for identifying high CVD risk patients was derived from the US Framingham Heart Study using data collected between the 1960s and 1980s. This score has only modest prediction accuracy and there are particular concerns about it’s validity for New Zealand sub-populations such as high risk ethnic groups or people with diabetes. Aims The overall aims of this thesis were to investigate the potential of a computerised decision support system (CDSS) to improve the assessment and management of CVD risk in New Zealand general practice while simultaneously developing a sustainable cohort study that could be used for validating and improving CVD risk prediction scores and related research. Methods An environmental scan of the New Zealand health care setting’s readiness to support a CDSS was conducted .The epidemiological evidence was reviewed to assess the effect of decision support systems on the quality of health care and the types and functionality of systems most likely to be successful. This was followed by a focused systematic review of randomised trials evaluating the impact of CDSS on CVD risk assessment and management practices and patient CVD outcomes in primary care. A web-based CDSS (PREDICT) was collaboratively developed. This rules-based provider-initiated system with audit and feedback and referral functionalities was fully integrated with general practice electronic medical records in a number of primary health organisations (PHOs). The evidence-based content was derived from national CVD and diabetes guidelines. When clinicians used PREDICT at the time of a consultation, treatment recommendations tailored to the patient’s CVD and diabetes risk profile were delivered to support decision-making within seconds. Simultaneously, the patient’s CVD risk profiles were securely stored on a central server. With PHO permission, anonymised patient data were linked via encrypted patient National Health Index numbers to national death and hospitalisation data. Three analytical studies using these data are described in this thesis. The first evaluated changes in GP risk assessment practice following implementation of PREDICT; the second investigated patterns of use of the CDSS by GPs and practice nurses; and the third describes the emerging PREDICT cohort and a preliminary validation of risk prediction scores. Results Given the rapid development of organised primary care since the 1990’s, the high degree of general practice computerisation and the New Zealand policy (health, informatics, privacy) environment, the introduction of a CDSS into the primary care setting was deemed feasible. The evidence for the impact of CDSS in general has been moderately favourable in terms of improving desired practice. Of the randomised trials of CDSS for assessing or managing CVD risk, about two-thirds reported improvements in provider processes and two-fifths reported some improvements in intermediate patient outcomes. No adverse effects were reported. Since 2002, the PREDICT CDSS has been implemented progressively in PHOs within Northland and the three Auckland regional District Health Board catchments, covering a population of 1.5 million. A before-after audit conducted in three large PHOs showed that CVD risk documentation increased four fold after the implementation of PREDICT. To date, the PREDICT dataset includes around 63,000 risk assessments conducted on a cohort of over 48,000 people by over 1000 general practitioners and practice nurses. This cohort has been followed from baseline for a median of 2.12 years. During that time 2655 people died or were hospitalised with a CVD event. Analyses showed that the original Framingham risk score was reasonably well calibrated overall but underestimated risk in high risk ethnic groups. Discrimination was only modest (AUC 0.701). An adjusted Framingham score, recommended by the New Zealand Guideline Group (NZGG) overestimated 5-year event rates by around 4-7%, in effect lowering the threshold for drug therapy to about 10% 5-year predicted CVD risk. The NZGG adjusted score (AUC 0.676) was less discriminating than the Framingham score and over-adjusted for high risk ethnic groups. For the cohort aged 30-74 years, the NZGG-recommended CVD risk management strategy identified almost half of the population as eligible for lifestyle management +/- drug therapy and this group generated 82% of all CVD events. In contrast the original Framingham score classified less than one-third of the cohort as eligible for individualised management and this group generated 71% of the events that occurred during follow-up. Implications This research project has demonstrated that a CDSS tool can be successfully implemented on a large scale in New Zealand general practice. It has assisted practitioners to improve the assessment and management of CVD at the time of patient consultation. Simultaneously, PREDICT has cost-effectively generated one of the largest cohorts of Māori and non-Māori ever assembled in New Zealand. As the cohort grows, new CVD risk prediction scores will be able to be developed for many New Zealand sub-populations. It will also provide clinicians and policy makers with the information needed to determine the trade-offs between the resources required to manage increasing proportions of the populations and the likely impact of management on preventing CVD events.