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There are many drug interactions and to know every single interaction is impossible. In Uganda, a country located in East Africa, patients often do not get a patient information leflaet when a physician prescribes drugs because they only get the drugs without packaging and information inside. Even in developed countries many poeple die because of drug interactions.
This work aims at developing a clinical decision support system for different kinds of drug interactions: 1) drug-drug interaction,
2) drug-food interactions,
3) drug-condition
interactions and
4) drug-disease interactions.
This system must be integrated into an
existing hospital information system called electronic Health Management Information System (eHMIS).
In the first part of this thesis different kinds of clinical decision support systems are described to find out which one is the best for eHMIS. The two different types are knowledge-based and non knowledge-based systems. The second part of this thesis, the data base of eHMIS is extended to have a full
knowledge base for the new module which contains drug-drug interactions, drug-food interactions, drug-disease interactions as well as drug-condition interactions. Therefore new tables were created and filled with data of several data bases with drug interactions. The last part is about designing the clinical decision support system for drug interactions
with the knowledge base of eHMIS, including the implementation considering the integration into the existing system. To know how health professionals in Uganda work
with an electronical health system as well as their other work ows was important. The system now runs in a hospital in Kampala, the capital of Uganda and in a health center level three in Mifumi, a village located in the east of the country.
An architectural concept for implementing the socio-technical workflow of Digital Pathology in Chile
(2014)
Virtual Microscopy opens up the possibility to remotely access high quality images at large scales for scientific research, education, and clinical application. For clinical diagnostics, Digital Pathology (DP) presents a novel opportunity to reduce variability [Bauer et al., 2013] due to the reproducible access to Whole Slide Imaging, quantitative parameters (e.g. HER2 stained membrane) [Al-Janabi et al., 2012], second opinion and Quality Assurance [Ho et al., 2013]. Despite of the mentioned advantages, the challenge remains to incorporate DP into the pathologists workflow within a heterogeneous environment of systems and infrastructures [Stathonikos
et al., 2013]. Different issues must be solved in order to optimize the impact of DP in the daily clinical practice [Daniel et al., 2012] [Ho et al., 2006]. The integration needs precise planning and comprehensive evaluation for adopting this technology
[Stathonikos et al., 2013]. This thesis will focus on an organizational development approach based on a Socio-Technical System (STS). The socio-technical approach covers: (i) the technical issue: tissue-scanner, NDP.view, NDP.serve, analysis software, and (ii) the social issue: pathologists, technicians. In order to improve the integration, a joint optimization (of i and ii) is necessary. The developed STS approach will optimize the integration of DP towards improved workflows in clinical environments. The improved workflows will reduce the pathologists turnaround time, improve the certainty of the diagnostics, and provide a more effective patient care within the covered institutions. An overt multi-site Participatory Observation, Questionnaires, and Business Process Modelling Notation will be used to analyse the existing pathological workflows. Based on this, the system will be modelled with the 3lgm2 Toolkit [Winter et al., 2007] under consideration of various technical subsystems that are present in the clinical environment. Afterwards, the interfaces between subsystems and its possible interoperabilities will be evaluated, taking into account the different existing standards and guidelines for image processing and management, as well as business processes in DP. In order to analyse the existing preconditions a questionnaire will be evaluated to establish a robust and valid view. In addition, the overt participatory observation will support this elevation, giving a deeper insight on the social part. This observation also covers the technical side including the whole pathological process. The socio technical model will then reveal measurable potential for optimization with incorporated DP (e.g. higher throughput for slides). The organizational development approach consists of a Socio-Technical System based on overt multi-site participatory observations, questionnaires, business process modelling and 3LGM2, will optimize the use of Digital Pathology in the daily clinical practice and raise the acceptance to incorporate integrate the new technology within the dayly workflow through the user centred process of incorporation.
• Perform and evaluate a questionnaire and a participant observation of pathologists work days in private & public institutions
• Create and evaluate a 3lgm2 model
• Model the current pathological process (viewpoint of pathologist & technical assistant) & perform and evaluate a contextual inquiry to elevate the pathologists requirements & expectations towards the system
• Test the future WF according the model parameters.
This project will detect unsuspected interrelations and interdependencies within the socio- technical workflow with a pathology laboratory. The observation will reveal the action conformity as well as the environment in which the process has to be embedded. Furthermore it will establish an optimized workflow for a specific clinical environment to prepare the implementation of DP. Additionally it will be possible to
quantify digitized images in order to improve decision making and lastly to improve patient care. In the future it will be possible to extend automated image analysis in order to support clinical decision support. Depending on acceptance, this can lead towards an automated clinical decision support for cases with low complexity.
Initial results of an ongoing research in the field of reactive mobile autonomy are presented. The aim is to create a reactive obstacle avoidance method for mobile agent operating in dynamic, unstructured, and unpredictable environment. The method is inspired by the stimulus-response behavior of simple animals. An obstacle avoidance controller is developed that uses raw visual information of the environment. It employs reinforcement learning and is therefore capable of self-developing. This should result with obstacle avoidance behavior that is adaptable and therefore generalizes on various operational modalities. The general assumptions of the agent capabilities, the features of the environment as well as the initial result of the simulation are presented. The plans for improvement and suitable performance evaluation are suggested.