Tag Archives: Lindsy Kotecki

Milliman model analyzes COVID-19 recession and healthcare coverage in the U.S.

The COVID-19 pandemic and the mitigating actions in response by citizens and governments alike have precipitated unprecedented economic disruption in the United States. The second quarter of 2020 marked the largest single-quarter economic contraction in modern U.S. history, driving unemployment rates from historically low levels in February to peaks last seen during the Great Depression.

The unraveling and recovery of the U.S. economy have had and will continue to have a similarly disruptive influence on the enrollment in and composition of U.S. health insurance markets. These impacts will be felt throughout the health system, including in state Medicaid budgets and hospital, physician, and pharmaceutical margins, as well as in the financial performance of commercial and Medicaid health plans.

To understand the interconnected nature of economic changes and health insurance coverage and to project impacts to U.S. health insurance markets, Milliman built a tool referred to as the COVID-19 Advanced Population Shift model. This model combines detailed information on the economic status, health insurance coverage, and health status of each state’s population prior to the COVID-19 pandemic with emerging information on the economic impact of the pandemic response. It allows forecasting the resulting shifts in enrollment and population morbidity across the healthcare markets while providing insight into the key factors driving change. Milliman’s Fritz Busch, Lindsy Kotecki, and Jeff Milton-Hall summarize the findings in this paper.

Equalising risk in global healthcare systems

Health insurance, like most insurance, can be priced using risk ratings, where premiums are set based on the relative risk of insured lives and the propensity to claim. This may result in unaffordable health insurance for the most high-risk members of society. As a result, many governments restrict the use of risk ratings in health insurance markets in favour of “community rating.”

In a community-rated system where all consumers are charged the same premium, many high-risk consumers are protected from paying unaffordable premiums. Other consumers, such as healthier or younger individuals, will generally pay a higher premium to subsidise sicker and often older individuals. Consequently, premium revenue collected by insurers or other risk-bearing entities may no longer truly reflect the underlying risk associated with their insured populations.

In many healthcare systems and health insurance markets around the world where risk rating is not allowed, risk equalisation is used to enhance consumer protection and market stability. Its aim is to compensate for the risk profiles of different groups of the population such that the additional medical expenses associated with high-risk members are shared amongst healthcare providers or insurance companies.

In this paper, Milliman consultants have set out a “how-to” guide to risk equalisation, or risk adjustment. They use illustrative examples from around the world to explain the challenges and practicalities that should be considered in the design and management of a risk equalisation program.

Analyzing the actuarial implications of a Medicare Advantage buy-in option for older adults

Currently, there are two Medicare buy-in policies proposed by Congress. Both policies would allow individuals aged 50 through 64 to enroll in a public option Medicare buy-in plan or a private Medicare Advantage and Part D (MA-PD) buy-in plan.

These buy-in plans would be structured in ways similar to Medicare, but the economics around the funding of the plans would be very different. In particular, the benefits and administrative expenses for such a plan would be entirely funded through member premiums. By contrast, the vast majority of funding for traditional Medicare and MA-PD comes from the federal government.

Milliman’s Lindsy Kotecki and Stan Westrom have performed a case study on the actuarial implications of one potential MA-PD buy-in option. The scenario considered would permit individuals aged 50 through 64, who are not otherwise eligible for Medicare, Medicaid, or employer group coverage, to purchase a plan that looks like a typical MA-PD plan. The purpose of the study was to explore the concept of an MA-PD buy-in option by analyzing potential outcomes under one set of policy and program characteristics.

To read their entire study, click here.

America’s relationship status with healthcare: It’s complicated

Financing and regulating healthcare in the United States is complicated. Fortunately, actuaries understand the intricacies and can provide unique perspectives to address the system’s complex challenges. In the article “Healthcare: It’s complicated,” Milliman’s Hans Leida and Lindsy Kotecki discuss issues related to reform that actuaries have helped navigate.

Here is an excerpt:

Besides predictability problems caused by regulatory or political factors, two challenges facing health actuaries during these transitional years have been (1) the lag between when market changes are implemented and when data on policies subject to the new rules becomes available, and (2) the difficulty in predicting consumer behaviour in reaction to major changes in market rules such as guaranteed issue and community rating. How many of the uninsured would sign up? How price-sensitive would members be when they renewed their coverage each year? How will changes in other sources of coverage (such as Medicaid expansion) impact the individual market? How will potential actions by competitors affect an insurer’s risk?

Despite the daunting nature of these challenges, actuaries have, out of necessity, found ways to try to address them. For example, faced with the data lag problem, they explored ways to augment traditional claim and enrollment data with new data sources such as marketing databases or pharmacy history data available for purchase. Such sources can be used to develop estimates of the health status of new populations not previously covered by an insurer. Many actuaries also developed agent-based stochastic simulation models that attempted to model the behaviour of consumers, insurers and other stakeholders in these new markets. Such models continue to be used to evaluate the potential outcomes of future changes to the healthcare system, and will probably be essential should efforts to repeal and replace the ACA prove successful.

How to stabilize the ACA marketplace ahead of change

Any upcoming changes to the Patient Protection and Affordable Care Act (ACA) will not likely be fully implemented until 2019 or 2020. The stability of the individual and small group health insurance markets during this period of transition will depend on the regulatory changes that are made in the interim and the transparency of those changes.

A new paper by Milliman’s Lindsy Kotecki and Hans Leida presents five key considerations for promoting market stability for the 2018 and 2019 benefit years under the assumption that they are transitional years with many current ACA rules in effect.

1. Don’t collapse the stool.
2. Extend risk mitigation programs.
3. Extending the transitional policy.
4. Consider interim rule changes carefully.
5. Transparency is key.

What issues may affect 2017 ACA rates?

As 2016 approaches, healthcare insurers should already be thinking about the 2017 premium rates they will need to file for their Patient Protection and Affordable Care Act (ACA) business. In the article “Ten potential drivers of ACA premium rates in 2017,” Milliman’s Aaron Wright, Hans Leida, and Lindsy Kotecki discuss several factors that may influence ACA plan rates moving forward. The factors are listed below.

1. Trend.
2. Changes to essential health benefits and the Centers for Medicare and Medicaid Services (CMS) Actuarial Value Calculator.
3. Additional data.
4. Continued migrations.
5. Carrier shuffling.
6. Ongoing political uncertainty: Court cases and elections.
7. Transitional reinsurance.
8. Risk corridors.
9. Risk adjustment.
10. Changes in fees and taxes.