The generic definition of business intelligence (BI) is a set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information for business purposes. This termand the practiceis applied widely throughout various industries. BI handles large amounts of data and information to help identify and develop new opportunities. Making use of new opportunities and implementing an effective strategy can provide a competitive market advantage and long-term stability. BI technologies provide historical, current, and predictive views of business operations. Common functions of BI technologies include reporting, online analytical processing, analytics, data mining, complex event processing, business performance management benchmarking, text mining, predictive mining, predictive analytics, and prescriptive analytics.1

Clinical intelligence (CI) is an emerging adjunct to BI that is focused on the healthcare industry. With the proliferation of various forms of electronic clinical data use, as well as industry and political pressures to obtain and utilize clinical measurements, BI is the obvious technological foundation for CI. The aforementioned BI definition works perfectly as CI's mechanics and functionality underpinning. Thus a generic definition of CI is a set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information for clinical purposes. Specific uses for healthcare BI and CI include statistics, scorecards, quality metrics and reporting, multipurpose presentation dashboards, outcomes-based compensation, longitudinal care management, key performance indicators (KPIs), alerts, supply-chain analysis, experience-based rating engines, and population management.

There is no convenient singular description or collections of words to make a cogent definition for the many meanings and types of healthcare BI and CI. Healthcare BI and CI are very subjectiveremember, "Health care is local," and so is data use. The application of an intelligence process may be static and trivial, or it may be dynamic and extremely complicated. Thousands of discrete software applications and tens of thousands of discrete data elements are used daily by providers, payers, and related health organizations, all of which would have their own description for what and how data intelligence is relevant for them.

There are a nearly infinite number of current and imagined healthcare BI and CI content examples. We will review some next.

Business/BI Example A CEO wants a dashboard that is refreshed nightly. A single dashboard screen presentation includes all of the organization's profit and loss data, accounts receivable (A/R) status, insurance payment denials, patient throughput volumes, prospectively booked appointments, and additional KPIs. The CEO will be able to review the insurance payment denials graphic and hover her computer mouse over the bar chart for the Blue Cross/Blue Shield (BCBS) payer indicator, double-click, and open the details for all the claims without outstanding denied payments. She may then tag this detailed report and send it to her CFO with questions and a requested response expectation.

Clinical/CI Example In the purchasing department conference room, the director of materials management for a mid-sized hospital is listening to a pharmaceutical sales representative propose certain purchases of disposable surgical items and associated pharmaceuticals. From his laptop, the hospital executive selects multiple items within his CI system to display in a count, cost, shelf-life, surgeon preference, and surgical room scheduling pie chart. He compares these metrics with the recommendations from the pharmaceutical representative and places a very focused order.

Question

Do you believe that BI/CI should be mandated and controlled bt the various government agencies that are involved in health care? Why or why not?