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Model driven software engineering (MDSE) is an emerging methodology for software development, targeting productivity, flexibility and reliability of systems; metamodelling is at the core of most MDSE approaches. Due to their complexity and plethora of requirements placed upon them, healthcare systems so far have not been adequately modeled; as a re...
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... In (Rabbi et al., 2014a;Rabbi et al., 2014b), the authors presented an approach where different aspects of a system were coordinated by means of multiple metamodels. The approach is based on the foundation of DPF. ...
Clinical practice guidelines (CPGs) play a fundamental role in modern medical practice since they summarize the vast medical literature and provide distilled recommendations on care based on the current best evidence. However, there are barriers to CPG utilization such as lack of awareness and lack of familiarity of the CPGs by clinicians due to ineffective CPG dissemination and implementation. This calls for research into effective and scalable CPG dissemination strategies that will improve CPG awareness and familiarity. We describe a formal model-driven approach to design and implement a gamified e-learning system for clinical guidelines. We employ gamification to increase user motivation and engagement in the training of guideline content. Our approach involves the use of models for different aspects of the system, an entity model for the clinical domain, a workflow model for the clinical processes and a game model to manage the training sessions. A game engine instantiates a training session by coupling the workflow and entity models to automatically generate questions based on the data in the model instances. Our proposed approach is flexible and adaptive as it allows for easy updates of the guidelines, integration with different device interfaces and representation of any guideline.
... In this context, some works provide closed solutions that can be configured by the final user such as [41]. Other works provide means for application design aiming at alarm identification [28,[42][43][44][45][46] or at the specification of the responses [47,48], which commonly correspond to warning or alarm triggering. For instance, the Millennium Home System [47] allows defining how to select the best mode of interaction with the user, and whether the resident or an external service have to be warned. ...
... For example, the CommonSens system [42] proposes an event language to describe events, and the Necesity project [43] presents a rule-based classifier that determines if a situation is normal or abnormal. Some authors make use of modeling methodologies [50] as they allow representing a system at different abstraction levels, hiding irrelevant technical details [28,44,45]. In this sense, the specification and verification approach in [44] combines UML diagrams and formal methods for establishing time requirements associated to events. ...
... These design approaches have something in common; they focus on software developers. On the contrary, but also based on modeling techniques, there are works that incorporate domain experts in the system design and development as in [45] where physicians define the conditions to trigger the alerts to display in a view, or in [28] where they model the care process and nurses manually initiate the different actions related to an alarm. The CAALYX system [46] proposes a special purpose language for caretakers to define the clinical rules. ...
In developed countries, public health systems are under pressure due to the increasing
percentage of population over 65. In this context, homecare based on ambient intelligence technology
seems to be a suitable solution to allow elderly people to continue to enjoy the comforts of home and
help optimize medical resources. Thus, current technological developments make it possible to build
complex homecare applications that demand, among others, flexibility mechanisms for being able
to evolve as context does (adaptability), as well as avoiding service disruptions in the case of node
failure (availability). The solution proposed in this paper copes with these flexibility requirements
through the whole life-cycle of the target applications: from design phase to runtime. The proposed
domain modeling approach allows medical staff to design customized applications, taking into
account the adaptability needs. It also guides software developers during system implementation.
The application execution is managed by a multi-agent based middleware, making it possible to
meet adaptation requirements, assuring at the same time the availability of the system even for
stateful applications.
Clinical practice guidelines (CPGs) are a cornerstone of modern medical practice since they summarize the vast medical literature and provide care recommendations based on the current best evidence. However, there are barriers to CPG utilization such as lack of awareness and lack of familiarity of the CPGs by clinicians due to ineffective CPG dissemination and implementation. This calls for research into effective and scalable CPG dissemination strategies that will improve CPG awareness and familiarity. We describe a model-driven approach to design and develop a gamified e-learning system for clinical guidelines where the training questions are generated automatically. We also present the prototype developed using this approach. We use models for different aspects of the system, an entity model for the clinical domain, a workflow model for the clinical processes and a game engine to generate and manage the training sessions. We employ gamification to increase user motivation and engagement in the training of guideline content. We conducted a limited formative evaluation of the prototype system and the users agreed that the system would be a useful addition to their training. Our proposed approach is flexible and adaptive as it allows for easy updates of the guidelines, integration with different device interfaces and representation of any guideline.
Due to their complexity and the plethora of requirements placed upon them, healthcare systems so far have not been adequately modeled for the purpose of software development. As a result, the healthcare software suffers from high development costs and lack of flexibility. Model driven software engineering (MDSE) is an emerging methodology for software development, targeting productivity, flexibility and reliability of systems; metamodelling is at the core of most MDSE approaches. In previous work, we proposed a multi metamodelling approach that captures the complexity of these systems by using a metamodelling hierarchy, built from individually defined metamodels, each capturing different aspects of a healthcare domain, namely, user access modelling, health process modelling, process monitoring, user interface modelling and modelling of the data sources. Here, we formalize the co-ordination among metamodels, using a linguistic extension of the metamodelling hierarchy. This linguistic extension is an added metalevel which models the integration of two or more different aspects of the system. We focus on two features essential to the co-ordination of healthcare metamodels, namely the integration of process and data, modelling data-aware processes, and the integration of process and user, modelling both user access as well as inheritance of user access to tasks.
