Business Intelligence for Healthcare

Business intelligence also referred to as (BI) is the process of leveraging software and services to transform data into actionable intelligence that informs an organization’s strategic and tactical business decisions. Business intelligence tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts and maps to provide users with detailed intelligence about the state of the business. Although business intelligence does not tell business users what to do or what will happen if they take a certain course, it is not only about generating reports. Rather, business intelligence offers a way for people to examine data to understand trends and derive insights. This is one of the main reasons why Business Intelligence for Healthcare is very important.

One common use of business intelligence in healthcare is through data warehousing. n terms of business intelligence, the essence of data warehousing are measurement that leads to understanding, insight, and action. In general, a data warehouse is a centrally managed and easily accessible copy of data collected from the transactional information systems of a corporation or health system. These data are aggregated, organized, cataloged and structured to facilitate population-based queries, research, and analysis. Such queries, research, and analysis enable measurement, which in turn enables understanding and the most informed business and clinical decisions.

The data in a data warehouse come from multiple source systems. Source systems can be internal, such as electronic health records (EHR) systems, costing or financial systems, or patient satisfaction systems; or external, such as systems associated with a state or federal government (e.g., mortality data or cancer registries). Think of a data warehouse as a very large, very specialized kind of library – a centralized, logical and physical collection of data and information that is used repeatedly to achieve greater understanding or make the most informed decisions. Like a well-stocked library, the utility of a well-designed EDW is nearly limitless.

So we’ve established that Business Intelligence is very important and beneficial to the healthcare industry. Below are some of these benefits

Business Intelligence Enables

a More Efficient,

Scalable Reporting Process

Typically, hospitals or group practice executives meet to determine the categories of healthcare data they need to track progress toward strategic goals. They may already have a process in place for getting financial data. But now, with new value-based purchasing pressures requiring clinical and financial data, organizations suddenly are tasked with getting more data than ever before. A healthcare EDW streamlines and scales this process. It integrates disparate data from a wide variety of sources, including billing, financial, patient satisfaction and clinical sources. Executives can access the information in the same place every month. And with the tools the healthcare EDW delivers, staff can analyze and interpret the data, running visualizations and reports, and gain insights into new and better ways to achieve quality and cost goals.

Business Intelligence Ensures

Consistent Data That

Everyone Can Trust

Too often during meetings, people will present conflicting data or diametrically opposed trends in the organization’s performance. Why does one team member’s data show a different trend in net income than another’s? Why does one clinical leader show that length of stay (LOS) is going down while another clinician shows the opposite?”

A healthcare EDW establishes a single source of truth and enables healthcare analytics. When data definitions and tools are consistent, as in a healthcare EDW, everyone – from front lines to leadership – can rely on the accuracy of the information used to drive critical decisions. An EDW also serves as a foundation for developing and maintaining a data governance program. With such a program, data owners and experts can identify data issues within the organization, resolve them, determine who needs to use the data and define the best access path to the data.