3 steps to strengthen employee benefits using non-traditional data – Employee Benefit News

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Seven out of 10 human resources leaders say their primary focus is on improving employee health and well-being in 2022, up nearly 10% since last year. But while leaders increasingly lean into non-traditional data sets like employee feedback to shape benefits packages and select new programs that meet employees’ needs, many fear they lack the right data — and the tools to leverage it.
For instance, employee feedback — a non-traditional data source, compared with standard sources like medical claims and prescription data — is the top data source for shaping benefits packages, an Artemis Health survey of 300 companies across sectors shows. Yet fewer organizations draw upon non-traditional data like social determinants of health (35%) and data from point solutions like wellness initiatives and condition-specific programs (35%). When they do rely on more diverse data sources, just 53% of benefits leaders feel “very successful” in doing so. This confidence gap is even more prominent when leaders rate their ability to use point solution data (39%) or disability data (50%).
Read more: How data can bring clarity to health plan management
Creating a competitive benefits package that supports physical, mental, social and financial health requires organizations to expand their data access to include more sources of intel. They also must invest in solutions that bring all their data sources — non-traditional and traditional — together in one place and break this data down into actionable insight. Here are three steps for leaders as they apply non-traditional data to craft stronger, more competitive benefits packages.
1. Take a fresh look at your approach. Even when benefits managers capture non-traditional data such as data related to wellness initiatives, mental health resources, and programs for musculoskeletal (MSK) conditions, which represent $600 billion in costs per year, most aren’t currently able to use this data, the Artemis Health survey shows. This results in wide gaps regarding what benefits leaders can see and learn about their population. It also limits their ability to design an effective well-being strategy that addresses their employees’ whole-person needs.
To stay ahead of the curve on benefits design, employers need a benefits analytics platform that can integrate and analyze disparate data sets from multiple sources — from point solution vendors that assist with diabetes care, mental health, fitness/weight loss goals, and MSK to data related to absenteeism, workers compensation, and diversity, equity and inclusion. The right platform will bring all of this data together in one place for a holistic view of the employee population.
One of our customers is a good example of this approach. They wanted to better support employee mental health, so they looked at data from their medical and prescription claims, absenteeism, and short- and long-term disability. They found employees with diagnoses for depression or anxiety were 13 times more likely to miss work, and were able to make the case for a behavioral health wellness program using this finding, among others. 
2. Focus on data storytelling. To use non-traditional data to determine the impact of benefits programs over time, organizations need data visualization tools that make it easy to depict progress over time. Best-in-class data visualization tools create “shareable stories” from employee data. They enable benefits leaders to confidently make a case for specific programs, manage point solutions, and measure the impact of benefits initiatives. They also empower leaders to share the value proposition of their efforts with senior leaders.
Storytelling, however, is only as good as the data that feeds it. To deepen the insight that is shared with senior leaders, benefits managers need the capabilities to:
3. Connect the dots for actionable insights. With the exception of staff surveys, most non-traditional data can be challenging to extract and analyze. Survey respondents who report the most success using non-traditional data supplement in-house expertise with data analytics partners to help connect the dots among disparate data sources and mine data for actionable insights. Benefits leaders deserve measurable next steps as they pursue better benefits. Software interfaces must be easy to use, with lightning-fast query speeds so that a casual question from the CEO, for example, can be answered in minutes, not days. It’s important to make connections across data feeds from both traditional and non-traditional sources that enable benefits managers to explore new methods of outreach and engagement for at-risk populations. For example, if your company has 1,000 members with diabetes, determine which of these members are also:
From there, organizations can design the right support for subpopulations of individuals to improve health and well-being while reducing healthcare costs.
Read more: Ask an Adviser: How can we protect employee data in the era of remote work?
Supplement the old with the new
Improving the health and well-being of employees isn’t just a worthy and admirable goal for benefits leaders. In times like these, it’s a necessity to reduce staff turnover and burnout. 
In 2022 and beyond, traditional data sources like medical claims and prescription data are no longer enough to assess the quality of healthcare benefits so crucial to staff retention. Organizations that expect to remain competitive must consider supplementing this data with a wide swath of non-traditional data, from absenteeism to data around point solutions and social determinants of health. Organizations that want to get ahead of the curve should find the right tools and expertise to maximize the strength of their benefits strategy. 
To do otherwise is to risk finding themselves in failing health.
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