Analytics -- the mathematical savior of oh-so-many population health management (PHM) programs -- is all the rage in health IT marketing circles these days. As the electronic medical records gold rush slowly ebbs over the next few years, attention is gradually shifting to approaches we can use to fundamentally change the cost and quality of care... and what we should do with all this data.

But how transformative are these PHM solutions? Many PHM offerings today look remarkably like yesterday's offerings:

For executives making decisions on new solutions, the issue is further clouded by marketing messages that describe any product capable of running a report as having "analytics" with "models" for improving the quality and/or cost of care. Is that really all it takes?

Along any organization's evolutionary journey, a disconnect can occur between an organization's goals and it's methods for attaining those goals. As the following figure illustrates, goals can vary from operational improvements to new discoveries in the practice, delivery, and reimbursement of care. Similarly, methods for achieving those goals can vary from current day-to-day techniques all the way out to breakthrough methods that have never been applied in healthcare. The disconnect comes when executives want to pursue more transformative goals, labeled "discovery" and "development" here, but only opt to use "common" methods.

Many PHM programs today include analytics that sit clearly in box 1 -- focusing on individual measures using descriptive statistics ("quality metrics" such as counts, averages, and percentages). Box 1 is good and important for many reasons, but can it power real transformation? For example, are yesterday's methods likely to surface and prioritize the current, real-world factors associated with variations in practice that impact efficacy, safety, and costs? Do they adequately capture the dynamics in population health delivery models? Or are they more likely to give us a lagging view of yesterday's beliefs of what might be important?

Health organizations need a balanced portfolio of health analytics capabilities -- some focused on supporting the status quo, and others helping the organization to pursue more strategic goals. If value-oriented transformation is a component of your organization's future growth, here are five questions that may help ensure you can get out of box 1 when needed:

But these five questions are only a start. In moving towards true value-based care, the new leaders will evolve their data warehousing and health analytics strategies beyond the tempting thought that transactional/operational systems can easily provide analytics outside of box 1. The problem -- and opportunity -- in health transformation is much bigger than that.