Fundamentals of Healthcare Analytics

If you always do what you always did, you will always get what you always got.

—Albert Einstein

Effective healthcare analytics requires more than simply extracting information from a database, applying a statistical model, and pushing the results to various end users. The process of transforming data captured in source systems such as electronic medical records (EMRs) into information that is used by the healthcare organization to improve quality and performance requires specific knowledge, appropriate tools, quality improvement (QI) methodologies, and the commitment of management. This chapter describes the key components of healthcare analytics systems that enables healthcare organizations (HCOs) to be efficient and effective users of information by supporting evidence-informed decisions and, ultimately, making it possible to achieve their quality and performance goals.

How Analytics Can Improve Decision Making

Healthcare transformation efforts require decision makers to use information to understand all aspects of an organization’s performance. In addition to knowing what has happened, decision makers now require insight into what is likely going to happen, what the improvement priorities of the organization should be, and what the anticipated impacts of process and other improvements will be. Simply proliferating dashboards, reports, and data visualizations drawn from the HCO’s repository of health data is not enough to provide ...

Get Healthcare Analytics for Quality and Performance Improvement now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.