Gregory ShufeltMost of the traditional metrics used to measure financial performance in a fee-for-service world will not be applicable or appropriate under value-based payment models. The financial metrics needed under a shared savings arrangement are fundamentally distinct from fee-for-service-oriented metrics. Under a shared savings payment model, population-level total cost of care is the ultimate determinant of financial success. In a shared savings program, total cost of care should be viewed as an outcome, with the two core components—utilization and cost per unit of service—being the primary areas of Michael Miyagifocus when developing target metrics. Organizations should identify and effectively deploy strategies that will target one, or both, of these components. 

Examples of common utilization-oriented metrics used by organizations participating in value-based payment models include emergency department visits per 1,000 in population and imaging procedures per 1,000. 

Examples of metrics that measure the unit cost side of the equation include cost per care episode, cost per component of care (across the continuum), and generic drug dispensing rate. Detailed population data analytics should be used to identify where an organization is a high-cost provider or is over-utilizing care, and appropriate care models should be developed and deployed. 


The most common challenge organizations face associated with incorporating population-oriented metrics, and often the most difficult for them to overcome, is acquiring the ability to access detailed utilization and cost data for the specific populations that use, or may use, provider services across the care continuum. This type of data is typically controlled by payers and may be difficult to obtain without fundamentally changing the relationship most provider organizations have with payers. 

Another common pitfall organizations face after they have obtained and analyzed this data and identified variances is the failure to effectively implement underlying care model changes required to achieve sustainable results in the utilization and unit cost patterns. It is impossible over the long term to achieve and sustain total cost of care targets without the effective deployment and implementation of appropriate care models. 


Ultimately, to be financially successful with value-based payment models, organizations need to identify financial targets that are tied to population-level utilization and cost data, clinical analytics, and new care models. For health systems that are self-insured, the utilization and cost data for their employees and their dependents is a readily accessible data source that should be immediately analyzed. Detailed population-level data by county for each state also can be obtained from the Centers for Medicare & Medicaid Services. 

Understanding how to aggregate and analyze population-level data, and ultimately communicate the 

results and implications to organizational leadership, related physicians, and the board, will be critical. 

The use of external benchmarking can help organizations develop a clear and layered message. Benchmarking can help identify utilization and unit cost variances, and when deployed effectively can assess performance by level of service (e.g., inpatient admissions, imaging), physician or practice group, and/or by individual disease categories. 

Measuring and tracking utilization and unit cost of care at these more granular levels can be instrumental in assessing the effectiveness of care models, which will ultimately drive financial performance in a value-based world. The right financial metrics can both facilitate assessment of financial and clinical performance and provide actionable information to address variances. Identifying where current utilization or unit costs exceed expectations and linking these results to financial risk from a total cost of care perspective are critical actions when developing and prioritizing action plans, determining the allocation of resources, implementing new models, and making changes to incentive plans. 

Gregory Shufelt, MBA, is a vice president with The Camden Group, Chicago. 

Michael Miyagi, MBA, ASA, is a senior vice president with The Camden Group, El Segundo, Calif. 

Publication Date: Wednesday, March 19, 2014