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Using Data to Make Informed Health Plan Design Decisions for Group Benefit Plans

April 27, 2020

By Tammy L. Brown

Designing health and group benefit plans has become a challenging process.

With ensuring compliance with the Affordable Care Act, selecting insurance carriers, setting employee contribution limits and much more, administrators, HR departments and business leaders are faced with more decisions than ever before.

Not to mention, the healthcare landscape has become increasingly complex. Healthcare and pharmacy costs have skyrocketed, providers are administering care in new environments, and new technologies are revolutionizing how individuals receive care. In this environment, plan administrators are faced with a unique set of challenges when designing health and group benefit plans.

Thankfully, the volume of healthcare and patient data has exploded in recent years, creating an opportunity for plan administrators and HR departments to make more informed, strategic decisions. When leveraged correctly, using data to design plans can boost participation, keep costs down and deliver a superior end product to employees.

However, leveraging data in this way requires a certain level of expertise. Here’s what employers need to know before diving in.

What specific data is most useful?

The high volume of healthcare data available to decision makers can be overwhelming at first. Experts predict the total volume of data in the industry will grow faster[1] than any other industry in the next five years.

Instead of looking at this data in its entirety, employers should first determine what type of data will help them make better decisions. For example, census data that shows how many families will join the plan as opposed to individuals, the average ages of participants and other demographic information can help paint a clearer picture of the employee population in need of coverage. Employer benefit offerings are often tied to specific populations and industries.

Behavioral data can also help decision makers understand how employees are using their benefits. For example, the amount of healthcare dollars spent on in-network versus out-of-network providers can give employers a sense of whether or not they should consider changes to their network of providers. The setting in which patients receive care dramatically affects the end cost. For example, assessing whether patients tend to visit urgent care facilities or hospitals can provide powerful insights to plan administrators looking to reduce expenses.

Also, employers can take a closer look at claims information by diagnosis code to determine how many employees need chronic care requiring expensive treatments. With this information, they can make adjustments to the plan to better account for ongoing claims and expenses. Members can then be directed to seek care in the most effective setting to drive favorable outcomes.

Leveraging data analysis capabilities and expertise

After identifying useful data, a level of expertise is required to leverage this information effectively. Data warehouses have emerged as valuable service providers that can help employers. Not only do these services store and organize the data, they also provide services to help employers analyze it.

An insurance broker that brings new technology and experience analyzing healthcare data can also add value to this process. For example, actuarial platforms can help model plan design changes and the impact on costs and utilization. Claims repricing systems can measure a carrier’s provider network discounts to ensure a thorough analysis is performed when evaluating networks. While all carriers contend they alone have the best discounts off of charges, consultants and employers need to focus more on net cost. Other tools are available that capture all of a group’s claims and utilization experience to allow for a panoramic drill down analysis into drivers of cost and gaps in care so that specific actions can be taken to address cost and quality proactively.

Gaps in care identification will reveal opportunities to support wellness programs. Employers should look to promote programs that focus on diabetes, high blood pressure, obesity and other chronic conditions. Member contributions may quite often be linked to completion of a health risk assessment, smoking attestations and routine connections with a health coach to encourage behavioral changes.

Mitigating pharmacy costs

The cost of pharmaceutical drugs has skyrocketed in recent years. According to the most recent data from the CDC, 9.5% of all national health expenditures[2] in 2017 were spent on pharmaceutical drugs. This has led many businesses to take a closer look at how to bring down these costs for their employees.

Data analytics can help employers accomplish this in a number of ways. Employers can look into which name brand prescription drugs are close to having their patent expire. Considering the cost of generic drugs are far less than brand name drugs, employers can make plan decisions that incentivize the use of these less expensive, yet equally effective, alternatives. In looking at claims by diagnosis code, employers can also get a sense of how many employees will be in need of expensive drugs and treatments. Additionally, they can look at which drugs are currently in the clinical trial stage and what impact they may have on overall costs once approved.

You don’t know what you don’t know

Healthcare data can provide valuable insights that can save companies money and help them deliver a better experience to employees. Yet many employers today are simply unaware of the powerful cost-saving advantages data analytics can provide their business. The first step in taking advantage is to gain awareness of this information. From there, an insurance broker with experience tracking down, organizing and analyzing healthcare data can help administrators and HR professionals make more informed decisions around their benefits plans.

[1] https://www.businesswire.com/news/home/20181126005585/en/Seagate-Launches-New-Data-Readiness-Index-Revealing-Impact

[2] https://www.cdc.gov/nchs/fastats/health-expenditures.htm

 

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FILED UNDER:

Data Analytics

Practice Leader

Tammy L. Brown

Executive Partner, Practice Leader, Data Analytics & Actuarial Services & Training

Previously was Underwriting Director for Horizon Blue Cross Blue Shield of New Jersey.

More than 30 years of employee benefits experience