The healthcare industry is being transformed continually by the biological and medical sciences, which hold considerable potential to drive change and improve health outcomes. However, healthcare in industrialized economies is now poised on the edge of an analytics-driven transformation. The field of analytics involves “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.”1 Analytics often uses historical data to model future trends, to evaluate decisions, and to measure performance to improve business processes and outcomes. Powerful analytical tools for changing healthcare include data, statistical methods and analyses, and rigorous, quantitative approaches to decision making about patients and their care. These analytical tools are at the heart of “evidence-based medicine.”
Analytics promises not only to aid healthcare providers in offering better care, but also more cost-effective healthcare. Several textbooks have been written on the cost-effectiveness of health and medicine, and health economics and the methods described can be used in healthcare decision making.2, 3, 4 Moreover, as healthcare spending rose dramatically during the 1970s and 1980s in the United States, an increased focus on “market-driven” healthcare developed.5 Today, as the amount spent on healthcare has risen to nearly 20% of GDP in the United States, analytic techniques can be used to direct limited resources to areas where they can provide the greatest improvement in health outcomes.
Analytics in healthcare is an issue for several sectors of the healthcare industry involving patients, providers, payers, and the healthcare technology industries (see Figure 1.1). As shown, the patient is the ultimate consumer within the healthcare system. This system consists of several sectors, including providers of care; entities such as employers and government that contribute through subsidized health insurance; and life science industries, such as pharmaceutical and medical device companies.
Figure 1.1 The healthcare analytics environment
A key domain for the application of analytics is in healthcare provider organizations—hospitals, group practices, and individual physicians’ offices. Analytics is not yet widely used in this context, but a new data foundation for analytics is being laid with widespread investments—and government subsidies—in electronic medical records and health outcomes data. As data about patients and their care proliferate, it will soon become feasible to determine which treatments are most cost-effective, and which providers do best at offering them. However, to maximize their usefulness, analytics will have to be employed in provider organizations for both clinical and business purposes and to understand the relationships between them.
Tom Davenport and Jeffrey Miller in Chapter 2, “An Overview of Analytics in Healthcare Providers,” make the case that analytics for healthcare providers is poised to take off with the widespread digitization of the sector. They describe the current maturity level of provider analytics as low and describe current analytical applications along the continuum of descriptive, predictive, and prescriptive for both clinical and financial business purposes. And they address future areas for analytics contributions including meaningful use, accountable care organizations, taming the complexity of the clinical domain, increased regulatory requirements, and patient information privacy issues.