Category Archives: Pharma

Rebate considerations for prescription drug stakeholders

The prescription drug distribution chain is complex and involves several stakeholders. There are generally six in the supply and demand of prescription drugs: pharmaceutical manufacturers, health insurers (including self-insured employers), pharmacy benefit managers (PBMs), pharmacies, wholesalers, and patients.

These stakeholders’ contracts determine how much a patient’s health insurance pays for prescription drugs and the patient’s out-of-pocket costs. Pharmaceutical manufacturer rebates are one of the key drivers that influence how health insurers cover prescription drugs. Rebates affect the finances of all stakeholders involved in the prescription drug distribution chain.

Prescription drug rebates are generally paid by a pharmaceutical manufacturer to a PBM, who then shares a portion with the health insurer. Rebates are mostly used for high-cost brand-name prescription drugs in competitive therapeutic classes where there are interchangeable products (rarely for generics), and aim to incentivize PBMs and health insurers to include the pharmaceutical manufacturer’s products on their formularies and to obtain preferred “tier” placement.

The May 2018 “American Patients First: The Trump Administration Blueprint to Lower Drug Prices and Reduce Out-of-Pocket Costs” from the U.S. Department of Health and Human Services targets rebates as part of its goal to lower prescription drug prices. In this article, Milliman’s Gabriela Dieguez, Maggie Alston, and Samantha Tomicki explain the finances associated with rebates and their impact on health insurer coverage decisions.

Diagnosed opioid use disorder by payer

Over 25 million American adults report suffering from chronic pain on a daily basis, and a range of adverse health outcomes accompanies their pain. Beginning in the early 2000s, opioid analgesics were increasingly seen as a solution to the problem of under-treatment that had been a concern in the 1990s. From 1991 to 2011, the number of opioid prescriptions filled at U.S. retail pharmacies nearly tripled, increasing from 76 million to 219 million per year, though those numbers have started to decrease since the peak in 2011.

Despite the recent decrease in prescriptions of opioids, the human toll of the opioid crisis has continued to intensify. Illegally acquired heroin and synthetic opioids such as fentanyl have become the leading cause of overdose deaths. Opioid overdose deaths are now the single largest factor slowing the growth in U.S. life expectancy, and if current trends continue, opioid overdose deaths could outnumber suicides by 2019.

In this article, Milliman’s Stoddard Davenport and Katie Matthews help explain the scale of the opioid epidemic within the insurance industry.

Based on a sample of over 42 million people with commercial insurance, nearly 1.3 million Medicare beneficiaries, and a Kaiser Family Foundation analysis of Medicaid beneficiaries in 49 states, we estimate that over 1.5 million insured Americans were diagnosed with an opioid use disorder in 2015 (the most recent year available). Figures 3 and 4 summarize these findings by payer. These results (and others presented throughout this report) have been age- and area-adjusted to be representative of the U.S. insured population as of 2015 using U.S. Census Bureau data.12

Figure 3: Diagnosed opioid use disorder by payer, 2015 (or most recent year)

Commercial
(2015)
622,000
Medicare
(2015)
239,000
Medicaid
(2013)
642,000

We found that about 41.4% of those with diagnosed opioid use disorder were commercially insured, 15.9% were Medicare beneficiaries, and 42.7% were Medicaid beneficiaries. Overall, the diagnosed prevalence rate of opioid use disorder was 3.28 per 1,000 for the commercially insured, 5.39 per 1,000 for those with Medicare, and 8.90 per 1,000 for those with Medicaid. Across all insurance payers, we found that the prevalence of opioid use disorder was 4.91 per 1,000.

Figure 4: National estimates of opioid use disorder diagnosis by payer, 2015 (or most recent year)

Payer Diagnosed prevalence per 1,000 Total diagnosed nationally No. (%)
Commercial (2015) 3.28 622,000 (41.4)
Medicare (2015) 5.39 239,000 (15.9)
Medicaid (2013) 8.90 642,000 (42.7)
Total 4.91 1,503,000 (100.0)

The authors also highlight the rate of opioid use disorder by age and sex.

Rates of opioid use disorder varied widely by age and sex, with men generally experiencing higher rates of opioid use disorder through age 65, and women experiencing higher rates from 66 and older. Rates were quite low through childhood, followed by a marked increase in the late teen years, peaking in the mid-20s at a rate of 5.47 per 1,000 for women (at age 24) and 10.00 per 1,000 for men (at age 25). Rates showed a sharp drop-off in the late 20s, followed by a rise to another peak in the mid-30s of about 3.76 per 1,000 for women (at age 35) and 6.37 per 1,000 for men (at age 36). From the late 30s through age 64, the gap between men and women closed and both experienced prevalence rates hovering between 3.50 to 4.00 per 1,000 through retirement age. Opioid use disorder rates for Medicare beneficiaries were generally higher for women than for men, and tapered off with advancing age. Comparable data for Medicaid were not available.

Implementing new pharmacy benefit manager

Sponsors of prescription drug plans that decide to change pharmacy benefit managers (PBMs) may need help with pre- and post-implementation tasks. An experienced consultant can work with a sponsor to navigate complex contractual terms, develop an implementation plan, and conduct annual audits to ensure that the sponsor continues to receive the pricing terms and rebates negotiated with the PBM.

This paper by Milliman’s Angela Reed and Brian Anderson explores the PBM implementation process. The authors highlight key items that sponsors must consider for a successful PBM implementation and how an implementation manager can assist.

Using prescription drug data for identifying missing diagnoses and for medical management in the Medicare Advantage market

Even though the Centers for Medicare and Medicaid Services (CMS) does not use prescription data in assigning risk scores, Rx data can still be a valuable resource for Medicare Advantage (MA) plans. Because the revenue for an MA plan each year is based on member diagnoses incurred in the prior year and submitted within 13 months of the end of that period, MA plans have a meaningful period of time to ensure complete and accurate coding as well as to identify members for disease management and potential drug adherence outliers. Milliman consultants Corey Berger and Brooks Conway provide perspective in this paper.

Hepatitis C treatments: Emerging trends

The high cost of therapy for patients with chronic hepatitis C (HCV) infection has been an important topic of discussion for key stakeholders in pharmacy benefit design and management. Multiple effective treatments have been introduced, with cure rates approaching 100%.

Although costly, curing HCV early on can prevent serious liver complications, such as hepatic cirrhosis, organ failure, and cancer, for the approximately 2.7 million affected people in the United States.

Trends
In 2016, there was a downward cost and utilization trend for the HCV Specialty category. Express Scripts reported in its 2016 Drug Trend Report that utilization of HCV therapies had decreased by 27.3% and the unit cost had decreased by 6.7%. The cost per member per year (PMPY) for HCV drugs decreased to $25.26 PMPY from $38.44 PMPY the previous year.

Why have cost and utilization suddenly decreased after two years of steady growth?

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The “Rxisk” of adjustments in 2018 ACA risk adjustment

The Centers for Medicare and Medicaid Services (CMS) is adding a new prescription drug category classification system to the 2018 risk adjustment model. Starting in 2018, a condition will be identified through a Hierarchical Condition Category with associated medical diagnosis codes, a prescribed medication, or both—each one affecting the final risk member score differently. This paper by Milliman consultants approximates the likely CMS mapping based on the publicly available information to date.