Workplace Wellbeing

The Secret to More Effective Workplace Mental Healthcare? It’s All in the Data. Here’s What HR Leaders Need to Know.

A data-driven approach enables organizations to understand employee populations, identify needs, and provide tailored mental health support—ultimately fostering a culture of individualized care.

Written by
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John Park
Senior Product Marketing Manager
Clinically reviewed by
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    In recent years, I’ve witnessed a positive shift toward destigmatizing mental health. More individuals feel at ease discussing their mental well-being and reaching out for assistance, and many companies now recognize how key mental health is to overall organizational success.

    However, despite these positive strides, significant barriers remain when it comes to accessing high-quality mental healthcare, and there are notable gaps in mental health strategies at the organizational level.

    So, how can we tackle these interconnected challenges? One powerful solution lies in harnessing data. By leveraging data to spot mental health issues early on, we can design precise interventions and gauge their effectiveness. This means integrating data into all organizational mental health strategies and support systems.

    A data-driven approach empowers organizations to create a culture where mental health is prioritized, challenges are addressed proactively, and resources are optimized to support employees’ well-being.

    Data is a driver of organizational success

    Prioritizing workplace mental health support extends beyond addressing visible issues. It involves cultivating psychological safety, empowering managers to support those facing mental health challenges, and taking proactive steps to promote mental well-being.

    Why is this so important? 

    A recent report shows that for most employees, their job significantly impacts their mental health—often even more than their interactions with healthcare professionals. It speaks volumes that two-thirds of employees would take a pay cut for better mental health support.

    Historically, workplace mental health strategies have been reactive, only responding to concerns as they arise. However, by harnessing employee mental health data as part of a comprehensive mental health solution, organizations can proactively identify areas for improvement and focus resources on preventative measures. 

    Data-driven insights enable a proactive, targeted approach to fostering a supportive environment.

    Early detection: the key to proactive support

    Similar to physical health, early detection of mental health issues is crucial. The sooner a problem is identified, the better the chances are of preventing it from worsening and requiring higher levels of care. 

    Gathering and analyzing real-time data allows organizations to develop proactive, personalized mental health interventions, leading to better employee outcomes and a better return on investment. 

    A comprehensive data-driven approach enables HR leaders to track these insights, monitor trends across the organization, understand where to focus resources, and benchmark against industry peers.                                                                                                                                                                                            

    Data-driven personalization

    People enter mental health care for a variety of reasons, and also have different barriers to accessing and staying engaged in care. Those barriers might involve an individual’s internal stigma about mental health, their cultural environment, and other social determinants of health.

    In light of these individual variables, there are many ways to ensure individuals are paired with treatment and providers who can address their specific needs and break barriers.

    Within a company, employees with a variety of mental health conditions and demographic categories will seek mental healthcare through their workplace mental health solution. 

    Over time, a data-driven solution can collect anonymized data from individuals entering care, and use it in aggregate for provider-patient matching, which entails:

    • Learning from other people with similar demographics and mental health challenges
    • Looking at the providers they’ve used, the treatment they’ve had, and their clinical outcomes
    • Then, recommending a provider and treatment accordingly

    How data can drive organizational interventions

    Targeted mental health interventions at the organizational level are powerful and often overlooked. Here’s what this looks like in practice.

    Think about a manufacturing company.

    Industry research tells us employees in this field are more likely to be male and often less likely to read emails. So, when building a mental health strategy, it makes more sense to reach those individuals through avenues like a break room TV, a flyer, or a handout. 

    Zooming in even more might tell us that within the manufacturing company, employees at a specific location report a much higher stress level due to a workplace incident. 

    When that data comes to light, the HR leader could devote resources to checking on employees in that location and quickly deploy targeted interventions to address whatever is happening.

    Measuring impact—evaluating ROI and clinical effectiveness

    When a company invests resources into a mental health strategy or particular initiative, it’s important to understand the impact—in terms of whether employees are feeling better and also the return on investment. Resources allocated to ineffective benefits help no one.

    Ideally, by the time an organization kicks off a mental health initiative, there’s a data-informed goal around what metrics need to be met to show the initiative is successful. 

    Data is the backbone of this process. Without it, there’s no way to measure whether a mental health solution or campaign works. The data must also be high quality and measured regularly enough to understand whether the interventions work.

    Demonstrating validated return on investment for mental health benefits is quickly becoming the expectation for proving benefit efficacy.

    Data transparency and privacy are important concerns

    Data can be useful for organizational strategy without violating an individual’s right to privacy. However, for it to work, people must be comfortable accessing the benefits.

    Employees interested in signing up for a mental health benefit might be fearful about whether their treatment and conversations are private, or whether their manager or HR leader might hear about struggles they’re having with anxiety at work, for example.

    For workplace leaders, it’s essential to be transparent about data privacy and ensure employees understand their treatment and data are private. Any data a mental health solution provides about an organization’s mental health program and population data should be anonymized, to keep individuals from being identified in reports.

    Data as a driver of resource allocation decisions

    HR leaders are balancing the cost of mental health benefits with many other benefits. With limited resources, data can help determine a population’s highest-priority needs. 

    For example, May is Mental Health Awareness Month, and an HR team might want to build a campaign around that theme that applies to as many employees as possible.

    In reality, specific subpopulations within the organization likely need more help than others. 

    For example, a particular department, employee demographic, or location may be dealing with heightened stress levels. Data can surface that need, and the HR team can tailor the campaign to resonate with those demographics or departments. 

    SpringWorks: putting data to work for organizations and their leaders

    Spring Health is addressing the need to transform workplace mental healthcare with cutting-edge technology, data insights, and personalized organizational support through SpringWorks—which is part of our dual-pillar strategy approach to mental healthcare.

    SpringWorks equips HR and workplace leaders with the tools and data-driven insights needed to optimize mental health programs at every step of the benefits process, including:

    • Enrollment: deploying data-backed best practices to generate interest in the benefit
    • Engagement: continuing optimization throughout a member’s engagement process. If a particular subpopulation isn’t engaging with the benefit, data can pinpoint this and offer targeted outreach.
    • Clinical outcomes: tracking population outcomes to ensure employees are getting and staying better.
    • ROI: collecting and measuring data to show return on investment, productivity gains, and health plan spend.

    HR leaders don’t have time to sift through data and reports to understand what their organization needs. And they shouldn’t have to. 

    Spring Health brings the insights and expertise to form effective health strategies directly to their fingertips.

    Driven by data, grounded in a culture of care

    Data plays an integral role in understanding an employee population, their needs, and areas requiring support. It can equip organizations with the actions, insights, and outcomes required to meet those needs effectively.

    Ultimately, a data-driven approach enables organizations to foster a culture where employee well-being is prioritized and mental health support is tailored to each individual’s unique needs.

    In an era where mental health is recognized as a critical aspect of organizational success, companies that embrace data-driven strategies demonstrate their commitment to creating a healthier workplace environment, positively impacting the lives of those who drive the business forward: its people.

    A key component of data is ROI—and lately, mental health ROI claims seem to be everywhere. Our Head of Actuarial Analytics is breaking down how to decode these claims and measure true success. 

    About the Author
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    John Park
    Senior Product Marketing Manager

    John is a Senior Product Marketing Manager at Spring Health and has eight years of experience in Product Marketing and Strategy and Operations. He’s passionate about leveraging qualitative and quantitative data to shape strategic, high-impact digital health work that puts people first and the potential of technology to drive meaningful change in healthcare access, engagement, and outcomes. Throughout his career, he’s worked in the technology, chronic condition management, and mental health industries.

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