What must issuers of pediatric dental benefits consider with AV ranges gone?

The draft Notice of Benefit and Payment Parameters for 2019 was published in October 2017. In this rule, there is a significant change affecting dental benefit plans—removing Actuarial Value (AV) requirements for Patient Protection and Affordable Care Act (ACA)-compliant standalone pediatric dental plans. This change in policy provides new flexibility for dental issuers and closer alignment of pediatric dental benefits between standalone dental plans and pediatric coverage embedded within an ACA medical plan.

In this paper, Milliman consultant Joanne Fontana discusses this change and why it will be critical for dental issuers to understand and act on as the 2019 pricing cycle starts.

Chronic disease management considerations

Disease management strategies can include a range of activities with varying approaches and levels of intensity. These strategies are also often mixed with other care management approaches.

Differentiating the disease management programme components, targets and interventions is important before evaluating return on investment or cost and quality impact. There are three broad programme designs to consider:

• Transitional care models
• Telephone-based disease management
• Utilisation and case-based disease management programmes

Although demonstrating savings in disease management programmes has proven difficult, it is not impossible. In this paper, Milliman’s Lalit Baveja and Mason Roberts explain the reasons why and also explain why it’s important to thoughtfully manage and continually review performance.

Comprehensive Care for Joint Replacement Performance Year 1 results: Key considerations

The Comprehensive Care for Joint Replacement (CJR) model is a bundled payment model in which 799 participating hospitals from 67 metropolitan statistical areas are required to participate. The first CJR reconciliation for Payment Year 1 (PY1) was completed in spring 2017. This paper by Milliman’s Pamela Pelizzari, Jocelyn Lau, and Harsha Mirchandani combines data from the report of PY1 results and other publicly available sources to compare hospitals that received payments in CJR PY1 to those that did not.

Employers cope with rising healthcare costs

In May 2017, Milliman released its 2017 Milliman Medical Index (MMI), which measures the cost of healthcare for a typical American family of four receiving coverage from an employer-sponsored preferred provider organization (PPO) plan. The MMI increased $1,118 (4.3%) to $26,944, including a 3.6% increase in average medical expenditures and an 8.0% increase in prescription drug expenditures. This increase of more than $1,100 (a continuation of similar annual increases in the index since 2001) shows that federal healthcare reform efforts, which have mainly targeted the individual insurance market and Medicaid, have had little effect on reducing employers’ costs. Although this year’s MMI saw the lowest annual percentage increase in healthcare costs for a family of four with employer coverage since at least 2001, healthcare cost increases continue to outpace consumer price index (CPI) inflation trends, as shown in the chart below.

Employers have responded by:

Gradually transferring more of the cost to employees through contributions and plan design
Over the past five years, the MMI has increased 30%, while the employers’ share of healthcare costs has increased 25.7%. As a result employees are paying about 43% of the MMI, up from 41% in 2012.

Putting more pressure on vendors
For example, employers sponsoring self-insured prescription drug plans should be regularly reviewing pharmacy benefits manager (PBM) arrangements through requests for proposals (RFPs) and market checks.

Managing utilization of benefits and cost shifting by providers through strategies such as narrow networks and proactive medical management

Staying ahead of the prescription drug pipeline
Over the past few years, prescription drug trends have been greatly influenced by the entry of extremely expensive, curative hepatitis C treatments. While it looks like these treatments are no longer driving prescription drug trends, it is important to monitor the status of the prescription drug pipeline to understand what employers can expect to spend on prescription drugs in the coming years. Employers can stay ahead of the curve through strategies like utilization management, including prior authorization, step therapy, and pursuing specialty pharmacy rebates.

This article first appeared in the January 2018 issue of Health and Group Benefits News and Developments.

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CMS proposed changes to the Medicare Advantage risk adjustment model

Late last month, the Centers for Medicare and Medicaid Services (CMS) released a 60-day “Advance Notice of Methodological Changes for Calendar Year (CY) 2019 for the Medicare Advantage (MA) CMS-HCC Risk Adjustment Model,” which describes proposed changes to the 2019 Part C risk adjustment model. CMS is seeking comments on the proposed changes, which are due by March 2, 2018.

The 21st Century Cures Act (Cures Act) requires CMS to make improvements to the CMS-HCC risk adjustment model for 2019 and subsequent years. The Cures Act directs CMS to:

• Evaluate the impact of including additional diagnoses for mental health and substance abuse disorders, as well as chronic kidney disease
• Make adjustments to the risk payments to account for the number of diseases or conditions of a beneficiary
• Phase-in the above changes to the risk adjustment payment over a three-year period, beginning with 2019 and fully implemented for 2022 and subsequent years

Based on the evaluation of the additional diagnosis codes, CMS is proposing to add to the model three new Hierarchical Condition Categories (HCCs) related to mental health and substance abuse, and one new HCC related to chronic kidney disease. In addition, CMS is proposing to include additional diagnosis codes for an existing substance abuse HCC.

In order to account for the number of conditions for each beneficiary, CMS has proposed to include new HCC count variables in the proposed risk adjustment model. As part of the development of the new count variables, CMS compared the predictive power of a model that counts only the conditions that result in a payment to MA plans in the CMS-HCC model (“Payment Condition Count” model) to a model that counts all conditions, regardless of whether they are used for risk payment (“All Condition Count” model). CMS concluded that the “Payment Condition Count” model increased the predictive accuracy of the risk adjustment model, while the “All Condition Count” model decreased the predictive accuracy. Both models are included in the Advance Notice for comment. CMS also noted that, in order for the overall fee-for-service (FFS) risk score to remain revenue-neutral, adding the new count variables would result in a decrease to the coefficients for many HCCs.

For 2019, CMS is proposing a model phase-in schedule that blends 25% of the risk score calculated using the proposed “Payment Condition Count” model and 75% of the risk score calculated using the existing 2017 CMS-HCC model. The weights of the “Payment Condition Count” model are proposed to increase to 50% in 2020, 75% in 2021 and 100% in 2022. However, CMS comments that because the three-year phase-in is required over a four-year period (2019 to 2022), it may be possible to use 2019 for comments and implement model changes in 2020.

In addition to the requirements directed by the Cures Act, CMS is proposing to recalibrate the 2019 CMS-HCC model using more recent data. The Advance Notice also proposes an increase to the weight given to the Encounter Data System (EDS) risk scores, from 15% in 2018 to 25% in 2019; these weights are used to blend the EDS and Risk Adjustment Processing System (RAPS) risk scores during the transition to 100% EDS. For 2019, CMS is proposing to combine the two phase-ins (increasing the weight for EDS and adding the proposed new model) by using the “Payment Condition Count” model exclusively for EDS risk scores and the existing 2017 CMS-HCC model exclusively for RAPS risk scores. Hence, CMS will only calculate two risk scores, one using the proposed model and EDS data at a 25% weight, and the second using the existing model and RAPS data at a 75% weight. CMS also plans to include RAPS inpatient submissions as an additional data source for the EDS risk scores, noting that inpatient submissions for EDS are low compared to RAPS. No explanation is offered for why inpatient submissions are low under the EDS methodology.

In the CMS fact sheet, it is stated that the new model will lead to an estimated 1.1% risk score increase across all MA plans, which equates to a 0.3% risk score increase after recognizing the 25% phase-in. However, results will vary for each plan. We expect to be able to evaluate the impact using actual data for individual plans once CMS releases the updated mapping of diagnoses to HCCs later this month.

The full text of the Advance Notice can be found here. The CMS Advance Notice Fact Sheet can be found here.

Partnering with health microinsurers to increase Kenya’s healthcare coverage

Kenya’s public health insurance scheme—the National Hospital Insurance Fund (NHIF) provides much of the country’s health insurance. However, the percentage of citizens covered by the NHIF falls short of Kenya’s national goals related to healthcare access. One key way that the NHIF can improve participation rates is by partnering with health microinsurers (HMIs).

In his article “Benefits of public-private partnerships in health microinsurance: the Kenyan context,” Milliman’s Mitchell Momanyi provides an overview of the NHIF and the reasons for low participation in the program. He also outlines several ways it can work with HMIs to enhance its benefits and increase its health insurance coverage.

Here is an excerpt from the article:

HMIs offer simple and affordable benefits that, when paired with public schemes such as the NHIF, can encourage beneficiaries to participate in and use their public insurance benefits when necessary. An example of such a benefit offered by many HMIs is ‘hospital cash.’ Hospital cash pays a fixed amount of money to the beneficiary when a qualifying inpatient hospital stay is triggered. This money can be used to pay for costs related to seeking treatment such as transportation, food and partial replacement of lost income. These costs aren’t covered by the NHIF and would present a barrier to some individuals seeking treatment. The SAJIDA Foundation in Bangladesh and the Microfund for Women in Jordan are examples of organisations that have successfully launched hospital cash products.9

A second way in which the NHIF can increase its reach is by pairing its benefits with an HMI policy that provides value-added services. Examples of such services may include access to discounted medication and access to preventive services such as free health check-ups. Value-added services are included in some HMI policies in order to increase client value by making the benefits more tangible. Beneficiaries don’t have to wait for catastrophic events such as an inpatient admission in order to use their benefits. An example of an HMI that has successfully implemented value-added services is Uplift in India. Its ‘dial-a-doctor’ service is popular among beneficiaries.10

The government can also partner with HMIs in order to increase awareness of the NHIF programme. The Impact Insurance Facility describes the lack of awareness of public benefits as a key emerging lesson in Ghana. In discussing a field test conducted to gauge citizens’ awareness of the country’s National Health Insurance Scheme, the Facility states that the test group did not know about the costs and eligibility requirements of the programme. It went on to state that ‘this lack of understanding is an initial barrier to enrolment and a factor in low retention in the scheme – even with a government sponsored scheme intended to provide universal cover.’11 In order to distribute their products effectively, HMIs typically build valuable partnerships with entities such as local community groups, unions and cooperatives. The NHIF can leverage these partnerships in order to promote the programme effectively in remote areas that the government would otherwise be unable to reach.