Blog Post

5 key considerations for measuring the ROI of your care management interventions

September 12, 2017

    Of the hundreds of conversations I've had this year about population health management, there is perhaps no question I get more than how to calculate the ROI of the incredible work many of you are doing to better manage patients and bend the cost curve. Since the impact of care management efforts is often articulated in terms of cost savings, the question you are asking is just how to determine those cost savings.

    Here are five things to do when determining your own ROI framework.

    1. Track changes in per member per month (PMPM) spending for attributed populations.

    Across any risk-based contract, tracking changes in PMPM is the industry standard to measure the impact of an organization's investments in population health. Calculating the change in PMPM from the start of care management interventions to the present is a foundational step in determining the net savings of those interventions.

    2. Determine the best benchmark for expected spend to compare against actual PMPM growth.

    Many population health initiatives can take years to implement and realize a return. The time needed for a new intervention to ramp up makes it difficult to reduce actual PMPM spending and achieve net cost savings in the early years of a new initiative. In these scenarios, the goal of population health investments is to inflect the rate of growth in health care costs. At a minimum, risk-based contracts require providers to bend the cost-to-payer growth curve for an attributed population.

    Providers can then measure impact as the difference between actual spending (and utilization) compared to expected year-over-year trends.

    Expected vs. observed illustrated trends in population spend

    Expected versus observed illustrated trends in population spend

    In general, there are three methods for tracking spending trends for a population. Depending on which metrics are available to providers, each method varies in accuracy and difficulty of measurement.

    1. Pre-Post Analysis: Track inflection in total spending before and after implementation of an intervention.
    2. Observed vs. Expected Analysis: Benchmark actual spend to expected spend for the attributed population. Base expected trends in spending on market- or population-specific growth rates.
    3. Control vs. Intervention Analysis: Create an intervention group (e.g., high-risk patients enrolled in a complex care management) and compare spending against a control group (e.g., high-risk patients who have not received care management outreach). Then adjust for age and severity whenever possible to minimize confounding variables in the analysis.

    While the control vs. intervention method provides the most accurate picture of ROI of the three, isolating the variables needed to do this can be difficult. Instead, many care management programs default to the observed vs. expected analysis.

    3. Recognize limitations of measuring only impact by tracking population-wide changes in PMPM.

    For attributed populations that are small in size, PMPM can easily fluctuate in outlier years where unpredictable health care events occur among a few individuals (e.g., cancer, premature newborns, and trauma-related events). Outlier spending has the greatest impact on PMPM when the attributed population size is small.

    Base return on investment calculations on expected versus actual spending across multiple years—rather than only one-year changes—for an accurate perspective of your care management impact over time.

    4. Measure performance outside of pure dollars and cents.

    No single metric is sufficient to provide a comprehensive picture of care management ROI, so consider several metrics in aggregate to illustrate the true impact. While changes in PMPM provide a baseline story for population health management, the metric hides the impact of specific care management initiatives.

    Successful population health management requires providers to manage chronic conditions, right-size utilization across sites of care, activate well individuals in health maintenance, and deliver appropriate preventive services for all attributed patients. Include quality, process, and clinical metrics that are applicable and actionable to capture a holistic view of impact.

    Get the Cross-Continuum Care Management Metric Picklist

    5. Document positive growth in typically underutilized services.

    Determining the ROI—particularly outside of capitated contracts—should not be limited to cost avoidance metrics. There are some health care targets where effective care management results in increased utilization. For example, improving patient engagement and closing gaps in care should lead to more primary care visits for unattached patients and prevent leakage. Improved medication management (and physician engagement) can lead to better generic prescribing rates. Better screening supports earlier identification of unavoidable disease (e.g., cancer) and improved care management.

    High-performing providers invest in non-billable services like care coordination, transportation, and housing, which are best captured in the short-term through increases in primary care utilization. Under payment models like the Medicare Shared Savings Program, care management improvements resulting in more primary care utilization in the short term means new revenue under fee-for-service, decreases in network leakage, and increases in the total attributed population. In the long term, improved care management results in downstream reduction in avoidable ED utilization and re-hospitalization.

    Population health managers can maximize the return of their efforts by increasing the proportion of attributed patients seeking care from high-performing provider partners.

    Scenario planning for closing gaps in care

    Scenario planning for closing gaps in care

    Track savings across your organization's population health initiatives

    Organizations looking to access their investments under risk-based payment models often track changes in a population's PMPM spend as their go-to metric. However, this metric doesn’t always offer full visibility to the soundness of an investment over time.

    That's why we created the Population Health Intervention ROI Estimator. This tool will help you quantify the impact of PMPM changes tied to your population health interventions over a five-year term and analyze the return on investment under risk-based payment models.

    Try it now

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