Two people reviewing healthcare benefits analytics on a computerTwo people reviewing healthcare benefits analytics on a computer

What to do with healthcare benefits data anomalies

February 15, 2021
Heidi Pearson

When your healthcare benefits data departs from the norm, these tips can help you use your program analytics and make data-driven plans for the future.

HR and benefits roles come with a unique set of responsibilities and goals at every organization. But one thing all HR professionals have in common is a reliance on data, especially when it comes to your health plan and benefits design.

Every year, your program generates a wealth of data you can use to understand your employee’s health needs, care utilization, engagement with specific benefit offerings, and more. This data can help you understand what’s working, what needs to change, and where your budget should be allocated to best support your team’s needs. Looking at trends year-over-year, you can start to model how your claims spending, population health, and other program characteristics may change over time, and develop a proactive plan to address these anticipated changes.

But what do you do when your program data looks completely different from the previous year’s results? (Thanks, COVID-19.) The pandemic upended 2020 healthcare spending and benefits utilization in numerous ways, resulting in data that looked very different than usual. According to the PwC Health Research Institute, many employers incurred unplanned COVID-related testing and treatment costs in 2020. However, since many Americans chose to delay preventive care and elective procedures last year, these costs were more than offset at many companies, resulting in a net decrease in healthcare expenditures. And some benefits that may have had limited use in the past, such as telemedicine or mental health apps, saw huge increases in employee engagement.

Whether or not these specific trends impacted your company, your 2020 claims costs and benefits engagement likely look very different than previous years’. But that doesn’t mean you should scrap your 2020 health benefits data. On the contrary, these analytics can play a key role in helping you navigate 2021 and beyond. Here are a few tips to help you consider how you should (and shouldn’t) use last year’s data to inform your program going forward.

Tips for analyzing 2020 healthcare data

Although 2020 was an outlier for most benefits programs, there are still many helpful insights you can glean. Here are a few things to think about when analyzing your data.

Determine your main goals. Data is a decision-driver, so it’s important to align your HR and benefits goals with the priorities that are top-of-mind for your leadership team. Some of these priorities might include keeping employees healthy as they return to the office or preserving assets in light of market uncertainty. Once you know what decisions are keeping your C-suite up at night, you’ll be better able to review your 2020 analytics and distill relevant trends.

Look for self-care clues. Taking a close look at 2020 health plan and benefit utilization data can tell you a lot about how your employees are handling their personal health and wellness in light of COVID-19. Identifying changes in common service types and condition codes, for example, can shed light on whether or not employees skipped preventive care—including annual wellness exams and screenings—or neglected to adequately manage chronic conditions. All of this information can, in turn, provide enormously helpful insights to guide your team’s 2021 employee engagement efforts and benefits strategy. For example, you might put a stronger focus on promoting telehealth wellness visits or bring on a new wellness app to support employees with pre-diabetes.

Find the why. Changes in numbers tell a story. An increase in behavioral health provider claims, for example, might indicate that your employees are struggling with increasing rates of anxiety and social isolation during the pandemic. Armed with this insight, you can make a strong argument for additional investment in mental health services going forward—and develop a solid plan to promote these offerings companywide.

Seek safe assumptions. Making accurate projections and models based on pandemic data is challenging, but if 2020 showed a decrease in healthcare utilization, it’s reasonable to assume there will be a surge in utilization at some point in the future as people feel comfortable resuming ordinary activities. For example, if your volume of knee surgeries decreased in 2020, consider whether claims might increase in the next 12–18 months as employees pursue delayed elective procedures or resume activities that might contribute to related injuries.

Factor in 2021 predictions. A Kaiser Family Foundation survey reports that spending in 2021 remains uncertain as employers and insurers continue to adapt to an evolving situation. That said, many organizations are braced for a potential uptick in healthcare costs in 2021 and beyond. Forty-four national and regional insurance carriers that participated in an HR Drive survey predicted that COVID-19 will increase U.S. employer medical claims by an additional 2%, on average, above normal 2021 trends. And nearly 60% of employer respondents to a Willis Towers Watson survey anticipate a small to moderate increase in healthcare costs this year.

Use short-term data anomalies to think long-term

While 2020 learnings have a lot of relevance for 2021 benefits decisions, it’s important to use what you learn to start thinking even further ahead. A survey by Mercer of 234 insurers across 56 countries led them to assert that “the ripple-effect of the COVID-19 will change health benefits in the future,” adding that the pandemic “brings opportunity to reinvent.” Now more than ever before, HR and benefits professionals have a chance to use data-driven insights to inform new, innovative employee benefits to safeguard healthcare spending, guide employees to smart healthcare benefits options, and protect employee wellness—no matter what unforeseen changes may happen down the road.

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