AI in Healthcare

CHAPTER 5Using AI for Metrics, Performance, and Reporting

“Excellence is never an accident. It is always the result of high intention, sincere effort, and intelligent execution; it represents the wise choice of many alternatives—choice, not chance, and determines your destiny.”

—Aristotle

As you strategize and deploy AI operations (AIOps) into your healthcare setting, you will want to immediately reap the benefits and rewards. But you don't accomplish that by chance; it is the fruits of the choices made by deploying high-end tools to make an impact. What impact is made on the clinical side of the equation? Have you been able to reduce mean time to recovery (MTTR)? Have the automation and workflow enhancements made a significant impact on production? Have they reduced outages and relevant incidents? Has return on investment been achieved? All of these questions are asked prior to the deployment of AI, and the best way to find this information and prove that your answers are correct is within the tools themselves and the data you can mine from within. Specific tools, methods, and efforts can help to provide the data you need to get this accomplished. In this chapter, we will look at the tools and techniques you can use to achieve this goal.

This chapter discusses how to use AI and AIOps tools to identify service performance, looks at metrics for typical key performance indicators and critical success factors, and explains how to report on the outcomes of using AIOps to stakeholders, ...