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Background: Stroke rehabilitation is a complex process that requires collaboration between stroke patients
and various health professionals. One important component of the rehabilitation is to set goals collaboratively with health professionals. The goal setting process can be time-consuming. In many cases, it is complicated for the patient and difficult to track for the health professionals. A simple user interface that supports patients, their family members and health professionals can help both sides to make the goal setting and attainment process easier.
Objectives: The aim is to design and develop a software for the goal attainment process of stroke patients with milder disabilities that facilitates goal setting process and the traceability of the goal progress for patients and health professionals.
Methods: Based on previous evaluated results, the web interface was developed and improved. Using this knowledge, a goal setting interface was added. To analyze the the goal setting process, goal attainment scaling (GAS) was included as well as parts of the International Classification of Functioning, Disability and Health (ICF) core set for stroke. The results were discussed afterwards in focus groups and evaluated based on two stroke patients, one family member and health professionals.
Results: We developed an interactive prototype, that can aid the rehabilitation at home by inserting
problems with ICF codes and different kinds of goals, creating new activities and tracing goal progress by reviewing the different goals. With the help of the GAS the outcome of the patient’s goals are visualized by a line chart presenting the positive or negative outcomes of the stroke rehabilitation.
Conclusion: The interactive prototype showed that it can support stroke patients during their rehabilitation
at home. A usability test indicated that the goal setting and attainment process was perceived as useful for patients and their family members. Small improvements have to be made to simplify use and error handling. For health professionals, the prototype could also simplify the documentation process by using ICF in the prototype, and also improving collaboration when using the tool for coordination.
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.
The e-commerce turnover has a constant growth rate of about 10%. An additional increase
in complexity and traffic spikes clarify the need for a scalable software architecture to prevent
a potential technical debt, higher financial cost, longer maintenance, or a reduced reliability.
Due to the fact, that existing approaches like the Palladio Approach require a high modelling
overhead and the importance of dropping this overhead was identified this master thesis is
focused on the modelling and simulation of e-commerce web application architectures using
a high-level approach to provide a faster, but possibly more inaccurate prediction of the
scalability.
This is done by the usage of the Design Science Research Process as a frame, a scientific
literature review for use of the existing knowledge base and the Conical Methodology for the
artefact creation. The artefact is a graphical model which is evaluated using a simulation
developed with Python and its framework SimPy. For model creation and evaluation a total
of twelve papers investigating the scalability of e-commerce web application architectures is
split into a test and train group. The training group and parts of the scientific research are
used to identify the components load balancer, application server, web tier, ERP system,
legacy system and database as well as some general characteristics that need to be considered.
The components with the most modelling variables are the application server and web
tier with a total of thirteen, while the ERP and legacy system only required five.
The model is evaluated using a total of three papers from the test group, where an average
throughput error of 5.78% and a response time error of 46.55% or 26.46% was identified. An
additional evaluation based on two non-e-commerce architectures shows the usability of the
model for other types of architectures. Even though the average error gives the impression,
that the model is not providing a good estimation, the graphical results show, that the model
and its simulation can be used to provide a faster scalability prediction. The model is least
accurate for the prediction of the situation, where the response time increases exponentially,
as this is the point, where variables, only accountable for some percentage and thus ignored
for the model, have the highest influence.
Future research can be found in the extension of the model by either adding or investigating
additional components, adding features ignored within this work or applying it to other
types of web application architectures. Additionally, both the low-level and the high-level
approaches can be brought together to combine the advantages from both approaches.