Through queuing theory and fuzzy logic: Optimization of patient queue management in hospitals using InterSystems IRIS

Description: I propose to develop a solution using InterSystems IRIS that optimizes the management of patient queues in hospitals, addressing the management of patient queues organized by rooms through queuing theory and fuzzy logic. The tool will simulate the evolution of patient arrival and care, but this time, we will apply the power of InterSystems IRIS to improve the efficiency, speed and sustainability of the process.

Objectives of the idea:

Improve system performance: Using InterSystems IRIS, we will optimize queue management processes, reducing waiting times and increasing the efficiency of medical resources.

Reduce required hardware resources: We will implement advanced fuzzy logic techniques and intelligent algorithms in InterSystems IRIS to optimally allocate available resources, minimizing the number of doctors and nurses needed without affecting the quality of care.

Speed Development and Deployment: InterSystems IRIS will allow us to rapidly develop and test prototypes, accelerating implementation time and reducing the man days required to get the system up and running.

Reduced environmental impact: By improving the efficiency of the hospital and reducing the resources used, our system will contribute to the reduction of the carbon footprint in medical care.

The solution will be based on queuing theory and fuzzy logic, but with the power and versatility of InterSystems IRIS, enabling smarter and more efficient management of patient queues in hospitals.

Let's break down how the idea fulfills the requirements:

Improve system performance: The proposal aims to optimize queue management processes in hospitals using InterSystems IRIS. By applying queuing theory and fuzzy logic, the idea can reduce waiting times and increase the efficiency of medical resources, thus improving the performance of the solutions.

Reduce required hardware resources: Through the implementation of advanced fuzzy logic techniques and intelligent algorithms in InterSystems IRIS, the idea plans to optimally allocate available resources in hospitals. By minimizing the number of doctors and nurses needed without affecting the quality of care, this can lead to a reduction in required hardware resources.

Speed Development and Deployment: The use of InterSystems IRIS allows for rapid development and testing of prototypes, which can accelerate the implementation time of the queue management system in hospitals. This helps reduce the workdays required for development, testing, implementation, and user training.

Reduced environmental impact: One of the key objectives of the proposal is to contribute to the reduction of the carbon footprint in medical care. By improving the efficiency of the hospital's patient queue management and optimizing resource allocation, the solution aims to reduce resource consumption and, in turn, have a positive impact on the environment.

Overall, the idea demonstrates a clear focus on leveraging InterSystems IRIS to create a smarter and more efficient patient queue management system in hospitals. It aligns well with the theme of the Idea-A-Thon and has the potential to bring significant benefits to the healthcare industry in terms of improved patient care and environmental sustainability.