How can employers continue to offer this critical component of care through benefits packages while containing costs? The key is to understand your population's health needs and its use of prescription drugs. Let's take a look at strategies benefits leaders can implement to keep these costs under control for their companies and employees.

1. Identify relevant data

Prescription drugs are often one of the most overlooked and under-scrutinized health care costs within benefits administration. Most companies lack data about — or more often, the insights into — employees' health and use of prescription drug benefits other than cases that are extreme outliers. So the first step is to identify and unify all relevant data sets to provide a holistic view of population health and use of benefits.

Combining information on health conditions, risk factors, and past medical treatments with the types of medications being prescribed to employees and their families is the best starting point. In addition, including both medical and drug claim information ensures that the full cost of drugs is accounted for, including those being delivered via the medical channel.

By getting the whole picture, benefits leaders can begin to proactively plan for prescription drug needs. They're also able to more effectively manage their benefits offerings and ensure that the right mix of preventative or clinical care is being accessed before members of the population are being prescribed costly medications.

2. Invest in prevention

The old saying goes, "An ounce of prevention is worth a pound of cure." While the exact exchange rate may not be 16 to 1, preventative strategies can still head off spending on more expensive treatments.

Health care leaders have pushed for years to focus on patient-centric care, including preventative care to help avoid chronic conditions. This forward-thinking approach minimizes long-term health risks and also provides a more cost-effective way to deliver health care compared with treating chronic or emergent conditions.

The same holds true for prescription drugs. People often find themselves in need of medications to treat conditions that might have been avoided with earlier and appropriate intervention. By analyzing health care data to predict emerging health conditions, benefits leaders can focus on health or well-being initiatives, or design benefits offerings that help people address health issues before they become life-threatening and costly.

As companies get better at collecting data and analyzing and predicting health care needs, they can encourage preventative treatment options for members, which might avoid chronic conditions and their associated costly medications altogether. However, that may not always be possible.

3. Escalate treatments step by step and require prior authorization

When prescriptions are required, one common strategy for avoiding unnecessary drug costs is step-therapy, in which patients try lower-cost drugs before stepping up to more expensive alternatives.

Algorithms that detect appropriate use of step-therapy can provide advanced warning when expensive prescriptions are anticipated, or when step-therapy is not being initiated appropriately. In those cases, patient education or pre-authorization requirements might be appropriate strategies to consider. The goal is not to raise barriers to appropriate treatment, but to ensure that the most expensive treatment is used only when necessary, and with informed decision-making by the patient and provider. It should be noted that a number of states have taken steps to allow physicians to override step-therapy requirements.

Requiring prior authorizations, especially for specific prescriptions or categories of drugs, can reduce costlier options. Limiting the quantity issued for single prescriptions, especially within specific time frames, is another way to avoid runaway costs.

In crafting prior authorization strategies, which can sometimes present an administrative burden, it is important to align the incentives of patients, health care providers, pharmacy benefit managers, and employers.

4. Substitute generics and biosimilars

Substituting generic drugs for name-brand ones is an important and well-known strategy to control costs. A good health analytics solution will help employers identify opportunities for savings from generic substitution by keeping on top of newly released generics and identifying patients who might be candidates for savings.

But with a certain category of groundbreaking medicine, a one-for-one substitution may not be possible.

Biologic drugs like Neupogen, Neulasta, and Remicade are large-molecule drugs made by living cells. As a consequence, it is not possible to create an exact copy the way that a generic drug duplicates a name-brand one. But there are still opportunities.

Biosimilar drugs are highly similar to FDA-approved biologic reference products, but can have minor differences, provided they do not impact clinical performance or safety. They typically cost less: On average, biosimilar drugs cost less than 30% as much as the reference product, with savings as high as 45% for some biosimilars.

Awareness of biosimilar options before a patient starts treatment can lead to better rates of adoption. Non-medical switching, the practice of changing a patient's medication for reasons other than the patient's health or safety, has been controversial with physicians. However, several studies have found that physicians are more willing to prescribe biosimilars to individuals initiating therapy than to those already taking a biologic.

Tying it all together

Data is critical. Accessing the right information, analyzing multiple sources, and leveraging technology to create predictive models and a deeper understanding of employees' health are critical to addressing benefits needs and preventing out-of-control costs. health care and prescription drug benefits that meet the needs of a company's most important resource — its people — are immutable. In a world of data insights, it is possible to contain costs and meet the needs of patients.

Anne Fischer has held multiple leadership roles in the health care information technology industry and garnered extensive experience in health care analytics, with a focus on complex algorithms such as episode groupers and risk models. Prior to joining Springbuk, Anne spent the bulk of her career at Truven Health Analytics, eventually leading the Value-Based Care Emerging Analytics team after Truven's acquisition by IBM Watson Health. Anne joined the Springbuk Health Intelligence team in 2019 as the Sr. Director of Data Science and Methods to spearhead the enhancement and development of analytics that drive value to health care payers and their members, and was elevated to Vice President in 2021.