Organizations that offer other post-employment benefits (OPEB)—such as retiree medical, dental, vision, life, or long-term care—face a complex and evolving landscape that impacts the underlying value of OPEB benefits and rate at which retirees elect them.

Demographic and health assumptions are used in OPEB valuations to project the level of these underlying benefits and election rates by projecting annual costs that are based on the probability of coverage and the dollar value of coverage. These annual costs are then discounted using economic assumptions to determine the OPEB plan’s liability for financial disclosure and funding purposes.

To ensure that liabilities and costs are measured accurately, it is critical to periodically reassess the underlying demographic, health, and economic assumptions used in actuarial valuations. Health actuaries generally review the health assumptions (costs associated with a retiree for OPEB benefits, such as retiree medical) and how these costs increase into the future (trend) on an annual basis; however, one of the most effective ways to evaluate demographic and economic assumptions is by conducting an OPEB experience study.

What is an OPEB experience study?

An OPEB experience study is a comprehensive review of your plan’s historical data to evaluate and refine the assumptions that drive actuarial valuations. By analyzing actual participant behavior and economic trends, plan sponsors can ensure that their assumptions align with current realities and future expectations—leading to more reliable financial disclosures and, if applicable, funding strategies.

Benefits of performing OPEB experience studies

Experience studies provide a range of benefits to plan sponsors, including:

• Alignment with actual experience: Regularly studying your plan’s historical experience helps identify areas where participant behavior is diverging from current assumptions. This periodic realignment is essential for maintaining the accuracy of actuarial valuations.
• Proactive risk management: Experience studies reveal emerging trends in participant behavior, enabling sponsors to identify and address potential risks early. This proactive approach helps minimize adverse impacts and supports long-term sustainability.
• Assumptions that reflect plan realities: Plan provisions and demographics can change over time. In addition, outside factors, such as the legislative environment, can impact plans. For example, the Inflation Reduction Act implemented a Medicare Part D redesign that also impacted Group Part D plans.
  Whether you have introduced new benefit tiers, increased retiree contributions, introduced a different delivery method (such as through a Medicare Advantage plan rather than a Medicare Supplement plan), or frozen the plan to new entrants, an experience study ensures your assumptions remain relevant and reliable.
• Informed decision-making: Leveraging the insights from experience studies empowers plan sponsors to make data-driven, confident decisions about benefit offerings, funding policies, plan design, and succession planning—building trust with both stakeholders and participants.

Key economic assumptions to an OPEB study

Economic assumptions—such as investment return and discount rates (unless dictated by the accounting standard)—are particularly important for prefunded OPEB plans. Over time, actual investment performance may diverge from assumptions. An experience study provides an opportunity to compare historical returns to assumed rates and to update assumptions to reflect current market expectations and your plan’s asset allocation. For non-prefunded plans, relying on external sources (such as authoritative indices or government data) can streamline the update process and ensure assumptions are well-researched and consistent.

Key demographic and election assumptions to an OPEB study

• Withdrawal (termination) rates: The likelihood that active participants leave employment before retirement eligibility can significantly affect projected liabilities, as OPEB benefits are generally not offered in these circumstances. Regularly tracking turnover trends ensures assumptions remain accurate.
• Disability rates: Disability assumptions estimate the probability that active participants will qualify for benefits due to a disabling condition before retirement. Benefits provided to disabled retirees often differ from those for other retirees, resulting in different cost patterns. For example, disabled retirees can sometimes commence OPEB benefits earlier than other retirees; also, Medicare may subsidize the benefit (even prior to age 65) if the retiree is eligible for Medicare disability coverage. Reviewing historical disability experience ensures the costs associated with disabilities are properly valued.
• Retirement age: Retirement behavior can vary widely, depending on the plan’s retirement provisions. Plans that offer generous benefits (such as fully-subsidized pre-Medicare coverage) and allow earlier enrollment often result in members retiring at a younger age than those with plans with more restrictive provisions (such as plans that require retiree contributions).
• Election rates: Not all retirees will elect OPEB coverage. For example, retirees may have access to more generous coverage through their spouse, or the retiree contribution required to participate may be cost-prohibitive. Studying historical election rates allows for more accurate projections of future costs. For larger plans, consider analyzing changes in coverage after retirees become eligible for Medicare.
• Lapse rates: Some retirees who initially elect coverage will later leave the plan. Lapse assumptions are typically highest in the first few years and decrease as the retiree moves further away from their initial enrollment date.
• Dependent and spousal coverage: Understanding how many retirees will enroll dependents or spouses and the typical age difference between couples is vital, as many OPEB plans offer spouse coverage for the life of the retiree or the life of the spouse. Over- or underestimating these factors can significantly skew liabilities, especially for medical coverage.
• Plan and tier selection: If multiple plan or tier options are available, analyzing election patterns helps estimate future claim costs and contribution rates.
• Mortality: Mortality rates differ by demographic group and occupation. Plans often start with industry-standard mortality tables and adjust them based on actual plan experience.

Is my OPEB plan the right size for a demographic experience study?

A robust experience study requires sufficient data to produce credible results. For smaller plans, statistical variability can limit the usefulness of a custom study. In this case, it is appropriate to use assumptions from external sources. When doing so, it is crucial to compare your plan’s demographic profile to any external or pooled data source, considering:

• Occupational differences: Does your workforce differ significantly from the reference group? For example, safety employees (law enforcement or fire protection) may have higher disability and mortality rates than teachers or general employees.
• Benefit eligibility provisions: Variations in retirement eligibility or vesting can lead to different participant behaviors and cost projections.
• Age and gender mix: Plans with older participant groups or a disproportionate number of one gender might deviate significantly from standard industry or pooled assumptions.

There is no definitive size threshold for conducting an experience study; we recommend consulting your actuary to assess whether your plan has sufficient data and scale to support a meaningful analysis.

Can pension plan assumptions be used for OPEB?

OPEB and pension plans often cover similar populations and share eligibility provisions, making it efficient to leverage certain assumptions (e.g., termination, disability, retirement, mortality, or economic) across both plans. Consider the following factors when evaluating whether your OPEB plan can appropriately adopt the assumptions used for your pension plan:

• OPEB-specific assumptions: Some assumptions—such as election rates—are unique to OPEB plans and may not be captured in a pension plan’s experience study. These should be reviewed and set independently where appropriate.
• Cohort consistency: If the covered populations are essentially the same, using identical assumptions can promote consistency and administrative efficiency.
• Asset allocation differences: If the OPEB and pension plans have distinct asset mixes, separate economic assumptions—particularly for investment return—may be necessary.
• Inflation expectations: Pension inflation assumptions are often suitable for OPEB. Note that inflation is only one component of the health cost trend assumption.
• Headcount vs amount-weighted assumptions: Pension plan assumptions are typically developed using salary- or benefit-weighted data, which may not align with the headcount-weighted nature of OPEB liabilities. Adjustments may be necessary, particularly for assumptions such as mortality rates, to ensure they are appropriate for OPEB valuations.

How often should an OPEB experience study be conducted?

Industry best practice is to perform an experience study every three to five years, or more frequently if significant changes occur, such as:

• The introduction of new benefit tiers or changes in plan provisions
• Major shifts in workforce demographics (e.g., retirements, layoffs, mergers)
• Significant changes in asset allocation for prefunded plans

Conclusion: The value to employers of an OPEB experience study

OPEB experience studies provide a rigorous, data-driven approach to updating and validating plan assumptions—whether your plan is large and fully funded or smaller and reliant on external data sources. By keeping assumptions current and reflective of actual participant behavior, sponsors can lay the foundation for stable and predictable plan liabilities and costs. Engaging your actuarial consultant throughout this process can help you thoughtfully address all relevant considerations and ensure your OPEB plan assumptions remain robust and reliable.