U.S. healthcare organizations are always seeking better ways to determine current outcomes, predict future outcomes, and implement best practices to ensure positive healthcare outcomes for their patients. The trend in the U.S. healthcare delivery system is to apply business intelligence, analytics, and data science to implementation processes. Prescriptive analytics is often implemented as a tool, which is built upon “first responder” tools like descriptive and predictive analytics. Researchers use tools such as artificial intelligence, algorithms, and cloud data architecture to aid in the computation processes. Prescriptive analysis seeks to provide decision makers in healthcare organizations with the ability to know how they should respond. This could be called decision optimization processes.
Many people face barriers to quality healthcare services. However, recent trends in business intelligence, analytics, and data science are showing great promise for improving access, reducing cost, and improving the quality of care.
In this week’s discussion, address the following prompts about how prescriptive analytics can aid healthcare organizations to make the best decisions for their patients. Your post should be a minimum of 500 words,
Define prescriptive analytics and explain how it can be applied in the healthcare industry to improve patient outcomes.
Discuss two model-based, decision-making processes and trends in modeling. Examples: model libraries, solution technique libraries, architecture-cloud-based tools, linear program model and multidimensional analysis modeling.
Explain why modeling may not be used in the healthcare industry as frequently as it should or could be.
Describe three benefits of using spreadsheets in prescriptive analytical modeling examples.