As the volume of data that is electronically available promliferates, the health-care industry is identifying better ways to use this data for patient care. Ideally, these data are collected in real time, can support point-of-care clinical decisions, and, by providing instantaneous quality metrics, can create the opportunities to improve clinical practice as the patient is being cared for. The business-world technology supporting these activities is referred to as business intelligence, which offers competitive advantage, increased quality, and operational efficiencies. The health-care industry is plagued by many challenges that have made it a latecomer to business intelligence and data-mining technology, including delayed adoption of electronic medical records, poor integration between information systems, a lack of uniform technical standards, poor interoperability between complex devices, and the mandate to rigorously protect patient privacy. Efforts at developing a health care equivalent of business intelligence (which we will refer to as clinical intelligence) remains in its infancy. Until basic technology infrastructure and mature clinical applications are developed and implemented throughout the health-care system, data aggregation and interpretation cannot effectively progress. The need for this approach in health care is undisputed. As regional and national health information networks emerge, we need to develop cost-effective systems that reduce time and effort spent documenting health-care data while increasing the application of knowledge derived from that data.