Medical Teamwork: A Case Study

Since technology revolution has taken place in many areas of our life, quality of services in healthcare has become one of the most important objectives that concerning both private and public organizations. Because of the relation between work performance and patient care, according to [Aiken et al.,2002] there are many hospitals have poor services quality which has impact on patient treatment as a result of frustration of teamwork. Also, they concluded that a key of improving services in health environment is cope and solve nurses’ job dissatisfaction. So, management of team work plays a significant role in improving in solving this problem. For instance, workers should have a balance of tasks based on their experience and skills which would

therefore, these difficulties were addressed by many studies that investigated different perspectives of team work environment., For example, [Femke, et al., 2016] built an algorithm in order to provide a satisfied tool of teamwork management tasks, they point out that

Team work management

Collaborative tools for team work.

Aim and objectives of your project

Impact for medical team

Literature Review / related works:

Algorithm of Task assignment:

This section will address previous studies and contributions to management teamwork.

In 2010, a study was done by Bachouch, R.B et al. which aims to create a model for optimizing and assigning tasks of home healthcare (HHC) in France. Microsoft Excel and LINGO were used to conduct the objectives of research where entering data send to LINGO solver to optimize the tasks. The authors take into account set of variables such as availability of worker, skills, traveling time of nurses and realizing tasks before end of day. As a result, they conclude that the tool was successfully resolve workload among nurses with some

system can assign tasks with less 5 second while it manages maximally 60 caregivers. By contrast, limitations of study illustrated that the present tool does not assign prioritise to tasks which might be acknowledge in future research also, there is a significant demand to add ability of customising the system to fit different departments in healthcare such as change algorithm’s weights. Analogously, Wilk, S. et. al applied technique of semantic rule solver due to extend MET4 system with dynamic assignment tasks which designed to capture changing in workflows context of healthcare. By Establishing set of behavioural rules that describe lively medical team workflow in order to assign tasks to team member under specific context. Furthermore, these rules take into account the relation and concepts of patients to healthcare workflow. thus, the system implementation based on multi-agent platform and Z3 solver. However, the result shows that the system able to present scalable strategies of team management that provided by behavioural rules. Also, a team leader can easily assign tasks to diversely team members that addressed by structure of interdisciplinary healthcare team ontogeny.