Pharmacy benefits: Super-sized, minimized or right-sized?

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Simplifying product lines requires business decisions that can improve or decrease product quality, satisfaction and costs. Similarly, employers’ health benefit decisions to streamline choices can impact health care quality, patient satisfaction, work productivity and total healthcare costs. Over the past few years, healthcare benefits and choices have narrowed to manage costs. Thus, the number of in-network providers, pharmacies, and reimbursable treatments has decreased.

Within pharmaceutical benefits, medication choices can be limited using exclusive or restrictive formularies. Exclusive formularies cover only a subset of treatments for a condition. For example, patients who need alternatives excluded from the formulary pay the full cost. Restrictive formularies limit when medications are reimbursed based upon meeting certain criteria, such as liver damage from Hepatitis C treatment.

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The criteria used to determine what is on formulary often assume a “one-size fits all” approach to medication management. Preferred treatments are selected based upon what works for the “average” patient, regardless of disease severity, age, gender, race or patient preferences. Because these restrictions or exclusions narrow treatments for common conditions, such as diabetes, asthma, hypertension and immunology, these formulary designs can affect many plan members.

Rather than improving healthcare quality and lowering costs, limited health choices without thoughtful consideration can have unintended consequences by lowering healthcare quality and raising costs.

“Super-sized” benefits, or too much flexibility in medication choices, can lead to higher costs without improved care. “Minimized”, or a “one-size fits all”, approach to treatment choices can lead to unintended consequences. As we learn more about biological, genetic, and predictive analytic approaches to personalized medicine, ensuring pharmacy benefits are “right sized” is an important and complex task.

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To understand how to “right-size” benefits, the National Pharmaceutical Council conducted interviews and focus groups that included researchers, clinical experts, employers, and health plan pharmacy and medical directors. These experts agreed that the need for treatment flexibility for a particular condition should drive the flexibility permitted in the benefit design. While no magical balancing algorithm emerged, a framework was identified based upon the interviews and subsequently tested in focus groups. The answers to the following questions in this framework can help employers and health plans determine when benefit designs for particular conditions are “super-sized”, “minimized” or “right-sized.”

Need for flexibility for a condition
For some conditions, a small number of treatment choices can be sufficient. For others, more treatment options may be required to account for differences in disease severity or treatment response. To differentiate among conditions in which more or less treatment flexibility is required, four considerations were identified. A preponderance of yes responses indicates greater need for treatment flexibility.

· Are treatment outcomes unpredictable? For some conditions such as breast cancer, genetic tests can predict if a particular treatment is likely to be more effective. Test results guide optimal care, resulting in less treatment flexibility. For other conditions, such as depression, treatment success with the initial treatment choice occurs for only one in three patients. Thus, treatment response is unpredictable and requires more treatment flexibility.

· Can patient experience inform treatment plans? Patient experience, such as prior treatment success or adverse reactions, are readily available to the provider but typically not to health plans in their routine administrative data. In these cases, more flexibility is needed as the provider has greater knowledge than the plan. Other health information, such as patient history, can inform providers and health plans and, therefore, a targeted care approach with fewer options may be appropriate.

· Are patient preferences important? In some cases, differences in patient preferences may not justify the incremental treatment cost. For other conditions, patient preferences matter because complex treatment regimens or side effects may affect treatment adherence and health outcomes. In these scenarios, broader treatment choice is needed.

· Are the consequences of not starting with the best treatment option serious? Treating an uncomplicated upper respiratory infection like sinusitis with oral first-line treatments before initiating more expensive antibiotics may have minimal long-term consequences. However, requiring patients with rapidly progressing rheumatoid arthritis to try multiple lower-cost treatments prior to more effective biologic treatment may cause irreversible joint damage or lower the likelihood of future treatment success. In this case, less restrictive benefits that allow more intense treatment may be appropriate.

Assessing the plan benefit design flexibility for a condition

Plan benefit design can encourage or discourage treatment flexibility through patient cost-sharing and logistical hurdles. Five considerations were identified to help differentiate among plan designs that allow for flexibility. Again, the preponderance of yes responses indicates that for a particular condition, the benefit design allows greater flexibility.

· Is the formulary open? Open formularies allow coverage, although at different copay or cost-sharing levels, for all or nearly all medications and therefore allow greater treatment flexibility. In contrast, closed formularies provide coverage for only those treatments listed on the formulary; patients who require non-formulary alternatives are responsible for the full treatment cost.

· Is the difference in patient cost-sharing between formulary tiers minimal? Over time, the number of formulary tiers has increased from two – generic or brand – to four or five – generic, preferred, non-preferred, specialty and non-preferred specialty. Patient cost-sharing has increased as well. The average copayment for a patient in an employer-sponsored plan can vary from $11 for generics to $54 for preferred medications and $93 for non-preferred treatments. Even small changes in cost-sharing can affect medication initiation and adherence: the greater the difference in cost-sharing between tiers, the less treatment flexibility allowed.

· Are many options included on the preferred formulary tier? Some plans include more than one treatment on the preferred tier for a condition; others only have one option. Because the non-preferred tier is associated with higher cost-sharing, benefits with limited options on the preferred tier discourage flexibility.

· Are the utilization management criteria easy to navigate? If patients comply with treatment steps are they offered reduced cost-sharing? Many benefits manage utilization of higher-cost treatments by requiring prior authorization for a treatment, step-therapy or quantity limits. The more utilization management criteria in place, such as requiring two or three treatment failures or lab tests every six months, the less flexibility allowed. However, some patients might require non-preferred treatments despite qualifying for these criteria. Are those patients financially penalized with higher cost-sharing associated with higher tier treatments? Some plans allow copay relief, which encourages patients to use the optimal treatment.

· Is the medical exceptions and appeals process easy to navigate? The medical exception and appeals process provides a safeguard for patients with unique circumstances. The greater the burden (e.g., excessive documentation, persistent follow-up, and hassle to the patient and providers), the less plan flexibility exists.

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These considerations require careful balance. When the need for flexibility is small, plan benefits can restrict treatment choices. Conversely, when the need for flexibility is high, plan benefits should permit flexibility. Treatments that work best for the “average patient may not work for all patients. Because the most inefficient care is the care that does not work, a “one-size fits all” approach to medications may not meet the diverse healthcare needs of plan members.

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