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- QUESTION
Reflection only
- Introduction
Dynamic simulation modelling is the process of creating and analysing simplified representations of real-world situations using computer models. In this module, we will explore the three paradigms of simulation modelling, the types of problems they are suited to and how they have been applied in health. We’ll also consider the rationale and procedure for participatory approaches and you’ll be provided with additional resources if you’d like to have a go at developing different types of simulation models.
2. Dynamic simulation modelling and its application in health
Complex public health problems, such as harmful alcohol use, overweight and obesity and suicide prevention, have many interrelated causes and it can be unclear how these factors interact. Despite decades of effort to effectively respond to these issues, solutions to these complex problems remain elusive. There is often a broad range of possible interventions to respond to complex health problems, however, traditional analytic tools are limited in their ability to help decision-makers determine which suite of interventions are likely to be the most effective, cost-effective and acceptable to the community (Atkinson et al. 2015). Additional challenges faced by decision-makers are gaps in research evidence, political considerations, industry lobbying and the implications for the health system over the short and long term.
Dynamic simulation modelling provides an effective tool to aid decision making, and “can answer important questions, such as which risk factors are the most important when in people’s lives we should target interventions, and which combinations of interventions work best, are most equitable and most cost-effective” (The Australian Prevention Partnership Centre 2015, p. 1).
Dynamic simulation modelling is the process of creating and analysing simplified representations of real-world situations using computer models. Simulation models have been used successfully in engineering, ecology, defence and business since the 1950s, and more recently in health. Bringing together a variety of evidence sources such as research, expert knowledge, practice experience and data, simulation modelling allows complex problems to be mapped. From this, a dynamic model can be used to simulate a variety of scenarios and predict outcomes over time.
The uptake of dynamic simulation modelling in the health sector has been limited, which Atkinson et al. (2015, p. 4-5) report are likely due to:
• A lack of locally available expertise in systems science modelling methods
• Unfamiliarity among policymakers with what these methods can offer
• Concerns that these modelling methods present similar challenges to other ‘black box’ modelling approaches whereby it can be difficult to establish confidence among stakeholders.
Despite limited uptake, dynamic simulation modelling has been implemented in many important ways in the health sector, which Atkinson et al. (2015, p. 2) report have been to:
• Improve operational aspects of healthcare capacity and delivery, such as patient flows in emergency, disease screening, demand for services and workplace requirements
• Map and understand complex relationships between multilevel risk factors that result in health problems such as childhood obesity, substance abuse, diabetes and heart disease
• Map the components of health systems and prevention systems, explore their interaction and analyse policy options to support the most efficient and effective arrangements of the system.
The Australian Prevention Partnership Centre (2015, p. 1) say “Recent advances in modelling software capability and more user-friendly interfaces have meant that simulation modelling is now more accessible than ever. This has allowed stakeholder engagement, consultation and consensus-building processes to be embedded in the development of sophisticated simulation tools, promising to address some of the challenges of decision making for complex problems”.
3. Types of problems and simulation modelling methods
Modelling is an approach to problem-solving. It provides a low-risk and low-cost way to experiment with possible solutions before they are implemented in the real world. Borshchev & Filippov (2004) describe modelling as a process (see diagram 1), which involves:
• Mapping a problem from the real world to a model in the world of models, which is the process of abstraction
• Model analysis and optimization
• Mapping the solution back to the real world.
The model analysis may be analytical or simulation. For complex problems where time dynamics is important, generally, simulation modelling is a better approach.Discussion Board A.7
Part 1 - A: 250 words for this assignment
Questions?
Reflection only - you can share your thoughts on the
What’s a situation that would be useful or interesting to do a simulation model of from your personal or professional life? What type of method would you use and why? Some examples might include the spread of flu in the workplace, exploration of the most effective strategies to increase physical activity participation in your community, how can patient flows in the emergency department be improved?Part 1 - B: 50 words - develop a relevant question from the assignment and discuss about it.
Part 1 - C: 50 words. Develop another relevant question from the assignment and discuss about it.
Please, ensure that the references are accurate.
Thanks
| Subject | Nursing | Pages | 4 | Style | APA |
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Answer
Simulator for Orthopedic Services
Part 1 A
The situation I find most suitable for simulation is orthopedic services. Professionally, I practice an orthopedic surgeon. In orthopedic surgery, it is very critical to understand the structure and anatomy of bones, joints and muscles. The anatomy is very critical for physiotherapy, and surgical treatment. Simulation based surgical experience training for example is a valuable strategy of improving students’ performance in orthopedics. I perceive it as an essential element needed for establishment of a comprehensive curriculum in orthopedic education and practice. To better understand the essential of the core activity of an operation room, it is important that a simulator be properly understood with regards to the exact operation treatment or therapy to be conducted. Orthopedic is increasing attracting a vast scope of techniques which commands a lot of sub-specialization. With the emergence of sub-specialization areas, effective adaptation of simulators is required. Consequently, I would use dynamic simulation modelling because it help to better understand how bones, joints and muscles interact during injury which causes a damage, during operation, and the healing process. There is increasing need for efficient, effective and accurate diagnosis and treatment of joint, bone and muscle injuries with every increasing sports activity. As a matter of fact, numerous bone, muscle and joint injuries are occurring daily from sporting activities. With proper understanding of the simulators, surgical and therapeutic operation would be conducted faster and accurately so that patients’ flow in the emergency is improved. Accuracy and efficiency are important elements of patients’ traffic flow.
Part 1-B
How can Simulators Improve Diagnosis of Bone, Joint or Muscle Problem?
I think simulators are developed from real life situation. With the previous experiences with bone, joint and muscle injuries, the simulators can be developed so that they can easily be used to map and diagnose, and give prognosis for injuries of joints, bones or muscles. This would help elevate the level of understanding of the problem and best solution
Part 1-B
Can simulators predict the probability and efficiency of Healing?
Simulator can predict the probability and efficiency of healing depending of the level of development invested in it. Simulators as the name suggest are and presentation of knowledge from experience. If therefore a simulator is developed accurately from all types and degrees of injuries which have been managed successfully, they can predict how a treatment given in a similar way would result in efficient healing.