Healthcare

The challenge and the opportunity

It is because of the complexity of both the human body and the devices and processes that we use to treat it that medical simulation for experimentation and discovery has trailed beyond other fields of study. However, it is also because of this inherent, systemic complexity that we must create robust medical simulation tools if we are to address the challenge we face in making health care delivery more effective and efficient in the context of rapidly advancing treatment technologies and a fragmented, non-uniform approach to health care practices, both clinical and business.

 

In many other industries, ineffective and inefficient practices are identified, measured, analyzed, and addressed through a commonly used set of business practice analysis techniques. However, as currently practiced in industrialized nations, clinical medicine at the point of care is often so complex that modeling it in a robust fashion for research purposes is difficult or even impossible using such traditional analysis techniques. Viewed from the standpoint of the relatively new discipline of system-of-systems engineering (SoSE), clinical medicine and the health care system in which it is practiced is now a “system of systems”—a meta-system that must be treated as such if it is to be understood and improved upon.

 

By using advanced simulation techniques to model health care systems, we can investigate inefficient and ineffective clinical practices and create virtual prototypes to test improvements to them, all within a virtual environment that exhibits four key inherent attributes:

Speed

Exploration, experimentation, and clinical trials can all be conducted far faster in a virtual world than in the real world. This is especially true when the questions being asked are amenable to offline, batch mode, non-man-in-the-loop simulations, which can be run in the thousands, generating data ready for statistical analysis.

 

Safety
A virtual environment is by definition a perfectly safe environment. In a flight simulator, after the worst possible accident, the pilot still gets up and walks out. In our simulated health care environment, no patient will ever be at risk.

 

Measurability

In a virtual environment, everything that happens (which may or may not be displayed), is generated via software (with or without human input), and so everything can be measured to whatever level of accuracy and detail is desired.

 

Reproducibility

As with measurability, since every action in a virtual environment is generated via software, every action can be reproduced precisely. A run of 10,000 iterations of a given experiment could optionally include the generation of all data necessary to perfectly reproduce any single run at any time after the experiment, as long as the data is retained.

 

This has the potential to dramatically increase the quality of the clinical care improvements we create while simultaneously decreasing the time it takes to bring them to market.

Want to know more?

ultisim Inc.

info@ultisim.com

  • Facebook Social Icon
  • Twitter Social Icon

*=mandatory fields

© 2019 ultisim Inc.