Walden University Week 9 Healthcare Environment Discussion Replies

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Ask a probing      question, substantiated with additional background information, evidence,      or research.

Share an insight from      having read your colleagues’ postings, synthesizing the information to      provide new perspectives.

Offer and support an      alternative perspective, using readings from the classroom or from your      own research in the Walden Library.

Validate an idea with      your own experience and additional research.

Make a suggestion      based on additional evidence drawn from readings or after synthesizing      multiple postings.

  • Expand on your      colleagues’ postings by providing additional insights or contrasting      perspectives based on readings and evidence.

DISCUSSION 1-

  • Discussion: Simulation for Performance Improvement

Globally, several developments in the clinical sector are being analyzed and monitored. Despite the fact that prospects for innovation have arisen, the development has seen severe hurdles. The increased frequency of study, rising knowledge, breakthroughs, and technological development have all contributed to an increase in life expectancy. Furthermore, rising difficulties such as infectious and chronic illnesses, demographic shifts, and personnel shortages, among others, need action in order to achieve the desired solution (Lamé & Dixon-Woods, 2020). The complexities of such difficulties need the use of computer-based process optimization methods like simulation. The use of simulation necessitates the inclusion of precisely identified probability distributions derived from research data. Furthermore, simulation optimization is used to investigate various aspects while keeping track of other parameters such as expenses and revenues. As a result, the simulation procedure considers the event’s tracks and includes all time-related data to report.

  • It may take many different forms in healthcare. For example, they provide a secure setting for learning, enabling researchers and medical personnel to examine clinical procedures and improve personal and remedial abilities before working with patients. Dummy patients with symptoms that react to simulated therapy are used in various simulations (Lamé & Dixon-Woods, 2020). Simulations are also used in skill training, which is done in a dedicated facility, in technology-based environments, in virtual reality, and in task trainers. Such modalities are used to increase quality. In-situ simulation is expressly seen as closely mimicking the complicated healthcare system that medical practitioners deal with on a daily basis. Simulation allows providers to rehearse a complicated procedure or event that may occur in “real life without the desired repercussions if a mistake happens” (Broussard, 2008). Such a scenario may be evaluated, extensively scrutinized, and all practitioners debriefed to adapt changes and remove any damages.

References:

  • Broussard, L. (2008). Simulation?based learning: how simulators help nurses improve their clinical skills and preserve. Nursing for women’s health, 12(6), 521-524.

Lamé, G., & Dixon-Woods, M. (2020). Using clinical simulation to study how to improve quality and safety in healthcare. BMJ Simulation and Technology Enhanced Learning, 6(2).

  • DISCUSSION 2-

According to Palisade, 2014, “Monte Carlo simulation is a virtual experiment that repeats a process or project or situation a large number of times and generates a large number of random samples bound by a specific set of parameters”. “A simulation model is a computer model that imitates a real-life situation. It is like other mathematical models, but it explicitly incorporates uncertainty in one or more input variables. When you run a simulation, you allow these random input variables to take on various values, and you keep track of any resulting output variables of interest. In this way, you are able to see how the outputs vary as a function of the varying inputs” (Albright, 2017).

  • Simulation model can be beneficial to healthcare setting. For example, wait time in the emergency room can be improved using the data and variables gathered, organized, and analyzed. Using the Monte Carlo simulation is like rolling the dice and predicts its outcome but in more efficient and accommodate variety of risk assumptions in many situations. For instance, wait time in ED can present different scenarios such as patients that require more critical and immediate needs such as stroke and heart attack in comparison to someone who had a broken bone. To make the situation more challenging is ruling out these patients of Covid. Other variables that can affect the wait time is staffing. How many triages nurse is available? This information can be analyzed and implement new strategies to reduce wait times. For example, registration process can be done by using an app in a smart phone or tablet. Patients can submit chief complaints ahead of time to the triage station and in return, the patients can receive estimate wait time. Another data that can be analyze is the weather and time of the day. When it is too hot or too cold, more patients can be anticipated to arrive such as the homeless and elderly. Another scenario is during the holidays where more accidents and violence can be attributed to more consumption of alcohol and illegal drugs.

References

Albright, S. C., & Winston, W. L. (2017). eBook: Business Analytics: Data Analysis & Decision Making (6th Edition). Cengage Learning US. https://mbsdirect.vitalsource.com/books/9781337225274

Palisade [PalisadeCorp]. (2014, January 29). Introduction to Monte Carlo simulation and risk analysis using @RISK and RISKoptimizer [Video file].