After finishing this course, the student can apply theories, models and methodologies to a design of eHealth technology for short- and/or long-term remote care and synthesize his/her findings in a scientifically well-structured report.|
Specifically the student can:
- Define clinically relevant parameters to detect changes in the health status of patients and illustrate this by creating and presenting a user persona and a scenario (1. Requirements) (1. Requirements)
- Assess existing sensors/applications for wearable, environmental, and self-reported short- (e.g. vital signs after surgery) and long-term (e.g. diagnosis, behaviour change) monitoring and choose the best fit with the requirements. (1. Requirements)
- Create a detailed description of a eHealth technology including its functional and technical specifications (1. Requirements)
- Collect, analyse and visualize multi-modal monitoring data adequately using sensors (2. Data monitoring and analysis)
- Analyse both prospective and retrospective data to detect and/or predict relevant changes in health conditions. (3. Decision support)
- Create decision support algorithms from using knowledge retrieved from state of the art decision support strategies to support clinical decision making (3. Decision support)
- From the decision support outcomes and practice-based examples of decision making, Create different coaching strategies for the design of the telemedicine system to enable behaviour change and engagement based on the literature and state of the art examples (4. Feedback and coaching)
- Formulate an evaluation methodology for the monitoring system including future methodologies for higher TRL levels. (5. Evaluation and implementation)
- Develop and execute a research protocol for monitoring in a daily life environment. (5. Evaluation and implementation)
- Create a prototype of a telemedicine system that entails the 4 telemedicine building blocks
In eHealth we study theories, approaches and systems that focus on treating and assisting people in managing chronic health conditions or lifestyle changes in their own daily environment thereby supported by health care professionals when needed . To understand these systems, analyse them and to design them, we need to understand the health issues and problems that have to be addressed by the eHealth technology and we need to understand what the suitable building blocks and architectures are to design these . Furthermore, we need to be able to evaluate the eHealth technology and understand how they can be implemented in everyday care practice.|
Both elderly and people with chronic diseases are more viable to become victim of all kind of complaints with the consequence of having problems with finding a balance between work and private life. Not only the number of patients seeking help for their health problems is increasing, but the health problems they report are also more complex. The number of people with chronic diseases is growing and almost half of them have multiple complex chronic conditions (multimorbidity). Complex chronic conditions pose a challenge for healthcare as it heavily impacts a person’s quality of life physically, mentally and socially. Also, it consequently imposes a high burden on the healthcare system in terms of the complexity of treatment and care delivery, manpower and costs, because of the need of receiving complex and long-term care from multiple healthcare professionals. Since health, work and well-being are closely and powerfully linked, they need to be addressed together. Consequently, in many cases the conventional ‘one size fits all’ treatment approach is no longer sufficient, and a more personalized approach is needed.
Current disease management and monitoring of patients with a complex (chronic) condition(s) now relies heavily on information acquired during time-based scheduled visits when patients are usually stable, whereas the actual symptoms and changes during common daily life triggers are not quantified. Follow-up of relevant physiological parameters at home (remote patient monitoring) can provide important quantitative insights into the severity and dynamics of a chronic disease. Next, the data will be analysed and interpreted to create targeted treatment via e.g. clinical decision-support systems. Benefits are expected to arise from earlier initiation of appropriate treatment resulting in less severe complications, accelerated recovery, and reduced healthcare utilization. Additionally, eHealth technology can be valuable for short-term monitoring, such as in the peri- or postoperative phase. Studies have shown that performing certain surgeries in day care with subsequent remote patient monitoring at home of vital signs is a safe and feasible alternative for people at low risk of complications.
Also, eHealth technologies can assist patients in their self-care behaviour and can be used to develop personalized coaching and feedback for the individual person. Especially supporting people in having a healthy lifestyle is important as for example a sedentary lifestyle is one of the main risk factors for all kind of health problems such as cardiovascular diseases, COPD, diabetes and musculoskeletal problems and because of the existing evidence that being active contributes positively to feeling healthy and quality of life. Although people do recognize the need for a more healthy lifestyle, they often find it difficult to get started and/or to stay motivated. Technology-supported lifestyle applications, focusing at physical activity, stress and nutrition, are expected to help people to continue contributing to society, the marketplace and the economy.
As such there is an ongoing development of patient monitoring and treatment outside the hospital using telemonitoring and telemedicine technology, using analysis and interpretation of data from existing and novel sensing methods in the wider clinical and daily life context. Such an eHealth technology can be decomposed into four main functional building blocks
- Monitoring – this part of the system takes care of sensing relevant (health-related) parameters and whenever needed environmental parameters. It will often include some data processing so as to remove measurement artifacts or to extract basic features from the sensor data. Monitoring may also include the transfer of data to some local or remote data-store facility, and it may include presentation of the (raw) data.
- Data Analysis – this part of the system takes care of analysing and interpreting the data with respect to biomedical or clinical metrics, or to estimate the state (either physical or mental) of the data.
- Decision Support – In decision support the outcomes of the analysis are used to make decisions on whether or not action should be undertaken and which action. The question here is how we can derive and construct decision models and how should these be used.
- Feedback and Coaching – Once a decision has been made, proper feedback and coaching to the user is needed in order to effectuate the action and/or move the user into the desired direction.
This course is about the design and development of an end-to-end telemedicine system for remote monitoring and coaching by addressing these four different building blocks, to enable personalized intervention of the complex chronic condition, focusing on long-term care and healthy lifestyle (nutrition, physical activity).
The aim of this course is to design and develop an end-to-end telemedicine system for long-term care and healthy lifestyle in the context of a chronic condition. We do this by addressing 5 main themes:
- Requirements Analysis
- Data monitoring and analysis
- Decision support and decision making
- Feedback and Coaching
- Evaluation and implementation
In this course you will all work on developing an eHealth technology for a use case of your choice (including, but not limited to asthma, COPD, oncology), resulting in different eHealth technologies. The course will have a theoretical roadmap in which the student learns the theories and tools for designing and developing such a system. In addition, the course has a practical roadmap in which the students gain more in-depth information about the themes and learn how to apply the theory in practice (by assignments, tutorials, presentations / discussions). Here technologies are being acquired that help in designing and implementing a monitoring and analysis system as part of an eHealth application consisting a decision support strategy and a feedback strategy. In a project team, the student collaborates in multidisciplinary teams with fellow students to design and develop such an eHealth technology for their specific use case, which they present and demo at the end of the course. The course will be assessed with a written report (grade).
|Master Technical Medicine|
|Master Biomedical Engineering||Required materials-Recommended materials|
|Wordt via Canvas beschikbaar gesteld.|