This thesis proposes a multidirectional methodological framework for a comprehensive ergonomic analysis and modelling of workflow for multi-modal vascular image-guided procedures (IGPs). Two approaches are employed to analyse the workflow: Discrete Event Simulation (DES) and purpose-oriented physical models. In contrast to previous studies, the proposed methodology looks in detail the actions carried out within the intervention rooms and the clinical experience during the procedures with three main objectives: to provide a deeper understanding of vascular procedures, to predict the impact of protocol modifications and to offer a framework to develop new image-guided protocols for the alternative use of Magnetic Resonance (MR) imaging in comparison with X-Ray Digital Subtraction Angiography (DSA). The methodological framework includes an assessment of commercial simulation software packages to evaluate their fitness to the specific requirements of this research. The novel methodology is applied to several cases studies of common vascular IGPs. In addition, a case of MR – guided focused ultrasound intervention demonstrates how it is possible to extend the framework to study non-vascular IGPs. The multi-disciplinary methodological framework described opens a new way to understand IGPs that could be used in prospective applications such as medical education and medical devices regulations.

abstract: The analysis of clinical workflow offers many challenges to clinical stakeholders and researchers, especially in environments characterized by dynamic and concurrent processes. Workflow analysis in such environments is essential for monitoring performance and finding bottlenecks and sources of error. Clinical workflow analysis has been enhanced with the inclusion of modern technologies. One such intervention is automated location tracking which is a system that detects the movement of clinicians and equipment. Utilizing the data produced from automated location tracking technologies can lead to the development of novel workflow analytics that can be used to complement more traditional approaches such as ethnography and grounded-theory based qualitative methods. The goals of this research are to: (i) develop a series of analytic techniques to derive deeper workflow-related insight in an emergency department setting, (ii) overlay data from disparate sources (quantitative and qualitative) to develop strategies that facilitate workflow redesign, and (iii) incorporate visual analytics methods to improve the targeted visual feedback received by providers based on the findings. The overarching purpose is to create a framework to demonstrate the utility of automated location tracking data used in conjunction with clinical data like EHR logs and its vital role in the future of clinical workflow analysis/analytics. This document is categorized based on two primary aims of the research. The first aim deals with the use of automated location tracking data to develop a novel methodological/exploratory framework for clinical workflow. The second aim is to overlay the quantitative data generated from the previous aim on data from qualitative observation and shadowing studies (mixed methods) to develop a deeper view of clinical workflow that can be used to facilitate workflow redesign. The final sections of the document speculate on the direction of this work where the potential of this research in the creation of fully integrated clinical environments i.e. environments with state-of-the-art location tracking and other data collection mechanisms, is discussed. The main purpose of this research is to demonstrate ways by which clinical processes can be continuously monitored allowing for proactive adaptations in the face of technological and process changes to minimize any negative impact on the quality of patient care and provider satisfaction. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2018

Tese de mestrado integrado. Engenharia Informátca e Computação. Faculdade de Engenharia. Universidade do Porto. 2008

Dissertação de mestrado. Mestrado em Ciência da Informação. Faculdade de Engenharia. Universidade do Porto. 2012

In-hospital onset strokes represent 4% to 20% of all reported strokes in the United States. The variability of treatment protocols and workflows as well as the complex etiology and multiple comorbidities of the in-hospital stroke subpopulation often result in unfavorable outcomes and higher mortality rates compared to those who experience strokes outside of the hospital setting. The purpose of this project was to conduct a systematic review to identify and summarize effective strategies and practices for prompt recognition and treatment of in-hospital strokes. The results of the literature review with leading-edge guidelines for stroke care were corelated to formulate recommendations at an organizational level for improving care delivery and workflow. Peer-reviewed publications and literature not controlled by publishers were analyzed. An appraisal of 24 articles was conducted, using the guide for classification of level of evidence by Fineout-Overholt, Melnyk, Stillwell, and Williamson. The results of this systematic review revealed that the most effective strategies and practices for prompt recognition and treatment of in-hospital strokes included: staff education, creating a dedicated responder team, analysis and improvement of internal processes to shorten the time from discovery to diagnosis, and offering appropriate evidence-based treatments according to acute stroke guidelines. Creating organizational protocols and quality metrics to promote timely and evidence-based care for in-hospital strokes may result in a positive social change by eliminating the existing care disparities between community and in-hospital strokes and improving the health outcomes of this subpopulation of strokes.

Workflow issues related to adoption of the electronic health record (EHR) has led to unsafe workarounds, decreased productivity, inefficient clinical documentation and slow rates of EHR adoption. The problem addressed in this quality improvement project was nurses' lack of knowledge about workflow changes due to EHR adoption. The purpose of this project was to identify changes in workflow and to develop an educational module to communicate the changes. This project was guided by both the ADDIE model (analysis, design, development, implementation, and evaluation) and the diffusion of innovations theory. Five stages were involved: process mapping, cognitive walkthrough, eLearning module development, pilot study, and evaluation. The process maps and cognitive walkthrough revealed significant workflow changes particularly in clinical practice guidelines, emergency department treatment plan, and the interdisciplinary care plan. The eLearning module was developed to describe workflow changes using gamification, scenario-based learning, and EHR simulation. The 14-item course evaluation included a 6-point Likert scale and closed- and open-ended questions. A purposive sample of nurses (N = 30) from the emergency department and inpatient care areas were invited to complete the eLearning module and course evaluation. Data were collected until saturation was achieved (n = 15). Descriptive statistics revealed the participants' positive learning experience. This quality improvement project is expected to contribute to positive social change by facilitating the effective use of the new EHR which can improve the quality of patient care, promote patient safety, reduce healthcare costs, and improve patient outcomes.

This thesis investigates an innovative framework and process coordination technologies for peer-to-peer based decentralised workflow systems. The aim of this work is to address some of the unsolved problems in the contemporary workflow research rudimentally from an architectural viewpoint. The problems addressed in this thesis, i.e., bad performance, vulnerability to failures, poor scalability, user restrictions, unsatisfactory system openness, and lack of support for incompletely specified processes, have become major obstacles for wide deployment of workflow in real-world. After an in-depth analysis of the above problems, this thesis reveals that most of these problems are mainly caused by the mismatch between application nature, i.e., distributed, and system design, i.e., centralised management. Thus, the old-fashioned client-server paradigm which is conventionally used in most of today�s workflow systems should be replaced with a peer-to-peer based, open,collaborative and decentralised framework which can reflect workflow�s distributed feature more naturally. Combining workflow technology and peer-to-peer computing technology, SwinDeW which is a genuinely decentralised workflow approach is proposed in this thesis. The distinguished design of SwinDeW removes both the centralised data repository and the centralised workflow engine from the system. Hence, workflow participants are facilitated by automated peers which are able to communicate and collaborate with one another directly to fulfil both build-time and run-time workflow functions. To achieve this goal, an innovative data storage approach, known as �know what you should know�, is proposed, which divides a process model into individual task partitions and distributes each partition to relevant peers properly according to the capability match. Based on such a data storage approach, the novel mechanisms for decentralised process instantiation, instance execution and execution monitoring are explored. Moreover, SwinDeW is further extended to support incompletely-specified processes in the decentralised environment. New technologies for handling incompletely-specified processes at run-time are presented. The major contributions of this research are an innovative, decentralised workflow system framework and corresponding process coordination technologies for system functionality. Issues regarding system performance, reliability, scalability,user support, system openness, and incompletely-specified process support are discussed deeply. Moreover, this thesis also contributes the SwinDeW prototype which implements and demonstrates this design and functionality for proof-of concept purposes. With these outcomes, performance bottlenecks in workflow systems are likely to be eliminated whilst increased resilience to failure, enhanced scalability, better user support and improved system openness are likely to be achieved with support for both completely- and incompletely-specified processes. As a consequence, workflow systems will be expected to be widely deployable to real world applications to support processes, which was infeasible before.

Delay to antibiotic treatment of community-acquired pneumonia (CAP) greater than 4 hours following hospital admission is associated with a 15% increase in mortality. Paper-based guidelines have been widely introduced to improve CAP care, but these interventions have under-performed due to poor compliance in complex clinical workflows. Unlike passive paper-based guidelines, alerting systems based on computer-based decision support systems (CDSS) have the capacity to actively draw attention to delayed clinical processes. Formal consideration of local workflow is key to the design and successful implementation of CDSS. I used workflow analysis techniques to develop an evidence-based alerting system designed to reduce the delay to treatment of CAP in the emergency department (ED) of an Australian tertiary hospital. A sample of 6 CAP patients were observed during October 2001 to derive a structural process flow model, which was refined via stakeholder interview. A deterministic process flow model was then developed using an existing retrospectively compiled CAP database, consisting of 246 patients admitted June-December 1998 and 146 patients admitted May-December 2000. A stratified control sample presenting with respiratory symptoms (n=74, January-December 2003) was collected for the assessment of diagnosis and chest x-ray (CXR) accuracy. Treatment delay greater than 4 hours was associated with failure to diagnose CAP in the ED, the absence of CXR evidence, low triage score, delayed CXR, and failure to treat in the ED. ED physicians only identified 54-57% of those discharged with CAP. Radiologists only reported CAP features in 47% - 67% of initial CXRs for these patients. I hypothesised that a CDSS-based alerting system, composed of a CAP early diagnosis model (EDM) and a simple risk model (CRB-65), would identify enough CAP patients to reduce the percentage treated after 4 hours. I constructed an evidence-based naïve Bayesian EDM (sensitivity = 36%, specificity = 93%). It was able to identify 24% of CAP patients that died in hospital, 38% of those with antibiotics delayed greater than 4 hours, and 26% of those with CXR delayed greater than 4 hours. CAP-specific risk models were equivalent to the Australasian Triage Score (ATS) in predicting mortality. I simulated alerting policy by combining the CDSS with the deterministic process flow model. Alerting for treatment at triage or initial physician assessment, when the EDM was positive, approximately halved the median treatment time of 5.53 hours, and decreased the number treated after 4 hours (62%) by 1/3. Treating EDM-positive patients as ATS category 2 produced a similar effect. Current triage practices, embodied mainly by the disease-independent, sign and symptom based ATS are too coarse to deal with conditions such as CAP, where there is high diagnostic uncertainty and delays in diagnosis and treatment are critical determinants of outcomes. Better outcomes may be achieved with quicker diagnostic and treatment workflows via: analysis of current diagnosis and treatment workflows, analysis and correlation of a comprehensive set of patient symptoms, signs and risk factors for the specific disease, and improving triaging and subsequent workflow through a disease-specific CDSS based on early diagnostic models derived from the previous analyses. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1374804 / Thesis (Ph.D.) - University of Adelaide, School of Medicine, 2009

L'approche "services Web" étend le rôle du Web d'un simple support d'information vers un intergiciel d'applications B2B. Un des concepts intéressants qu'offre cette technologie est la possibilité de définir un nouveau service par composition de services Web existants. Dans cette thèse nous nous intéressons à assurer des compositions fiables de services Web. Pour ce faire, nous proposons un modèle qui (i) enrichit la description des services Web pour mieux exprimer leurs propriétés transactionnelles et qui (ii) étend et fusionne les systèmes de workflow et les modèles transactionnels avancés (MTA).<br />Nous proposons trois approches, basées sur ce modèle, pour assurer des compositions fiables. Contrairement aux MTA, la première approche part des spécifications des concepteurs pour déterminer les mécanismes transactionnels permettant d'assurer des exécutions correctes.<br />La deuxième approche procède par ré-ingénierie du service composé (SC). Elle permet d'améliorer les mécanismes de recouvrement d'un SC après analyse de ses traces d'exécutions.<br />La troisième approche repose sur le concept de "patron transactionnel", un nouveau concept que nous introduisons. Un "patron transactionnel"est un patron qui combine la flexibilité des workflows et la fiabilité des MTA. Nous définissons un SC en connectant des patrons transactionnels.<br />Nous utilisons un ensemble de règles de cohérence pour assurer que le SC défini est fiable. La contribution majeure de notre proposition est qu'elle a pu fusionner la flexibilité des systèmes de workflow et la fiabilité des MTA. Ainsi elle permet d'assurer des exécutions correctes<br />selon les critères spécifiés par les concepteurs.

Les travaux développés dans ce mémoire se situent à l'intersection des domaines du Génie Logiciel et de l'Intelligence Artificielle Distribuée : l'objectif est de spécifier un système d‘aide à la gestion d'information au sein d'une organisation de type administrative complexe sous la forme d'un système multi-agent. Le modèle holonique a été choisi, suite à une étude générale sur les organisations humaines et sur les organisations multi-agent, afin de structurer un système d'aide distribué en adéquation avec notre problématique, à savoir l'apport d'une aide au niveau de chaque acteur de l'organisation et la gestion de la cohérence de son fonctionnement global. Le choix d'une méthode d'analyse et de modélisation de système administratif complexe a nécessité la confrontation, à l'aide d'un benchmark, d'un ensemble de méthodes issues du Génie Logiciel et couramment utilisées. Aucune des méthodes comparées ne répondant totalement aux critères établis, la méthode MAMOSACO, conçue par adaptation et intégration des éléments les plus pertinents des méthodes comparées, est proposée. Cette méthode permet de spécifier un Système Orienté Holon pour l'aide au Travail COopératif (SOHTCO) d'un ensemble des acteurs impliqués dans une procédure donnée. La méthode MAMOSACO a été appliquée, au travers de son atelier de modélisation, sur un ensemble de cas réels de procédures administratives complexes. Et, finalement, sur base du cas d'application développé, un ensemble de perspectives de recherches, tant en ce qui concerne la modélisation qu'en ce qui concerne le système multi-agent holonique, est proposé.