Payers for healthcare, including both governments and private health insurance firms, have had access to structured data in the form of claims databases. These are more amenable to analysis than the data collected by providers, who have relied largely on unstructured medical chart records. However, historically payers focused on collecting data that ensure efficiencies in billing and accounting, rather than healthcare processes and outcomes. Even with limited administrative databases, payers have, at times, been able to establish that some treatments are more effective and cost-effective than others, and these insights have sometimes led to changes in payment structures. Payers are now beginning to make inroads into analytics-based disease management by redesigning their information databases to include electronic medical records. However, there is much more to be done in developing medical information databases and systems and employing analyses within payer organizations. In addition, at some point, payers are likely to have to share their results with providers, and even patients, if systemic behavior change is to result.
Kyle Cheek in Chapter 3, “An Overview of Analytics in Healthcare Payers,” concentrates on analytics as a value driver to improve the business of health insurance and the health of its members. He provides a framework of the types of analytics that can add value, and he reviews the current state, which he describes as “analytical sycophancy.” He concludes with paths to maturity and best practice examples from leading organizations.