Change your perspective: From 10,000 feet in the air to feet on the ground

Having varied levels of health data leads to a healthier workforce, healthier business

By , Rubina Rizvi, MD, PhD, and Mollie McKillop, PhD, MPH | 10 minute read | May 11, 2022

top view of a city full of cars and people walking

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Imagine you’re an aerial firefighter approaching a hotspot. Catching your eye at 10,000 feet are dark patches amid a lush landscape. Below 3,000 feet, mottled red embers. Closer still, smoke makes you cough. Your brain kicks into high gear. Are people in danger? Are homes at risk? Your team quickly reviews general reports for wind and rain. But only with feet on the ground can you see critical details—like waterways and underbrush—that might also affect the fire’s path. That data informs your next urgent steps.

To understand the health landscape for your employee or member populations, you need views into your data that could help you develop a similar game plan. Who is at risk for which health issues, and how do these risks impact your business? How could that knowledge of employee wellbeing inform interventions and plans for prevention? Analysis of key data can help pave your next steps, to a healthier, happier and more productive workforce and community.

What data do you need? And how can you get it?

The view from 10,000 feet: Population health

Every employer, manager and coworker understands, on some level, how illness impacts their work environment. At its simplest, poor health can lead to absenteeism. The result is that either others take on the work, or the work doesn’t get done. Leadership sees the effect of poor health play out in rising direct costs, including medical supplies, prescriptions, hospital admissions and other treatments. Workers call in sick, leave on short-term disability or, as we’ve seen in the last few years, resign.

High-level population health data can reveal trends related to the health of workers. You can then dissect the data at a more granular level. This analysis could help reveal the cause of specific health concerns and clarify what impact they might have on your workforce and your business.

For example, let’s look at diabetes and productivity in the workplace. Absenteeism can lead to about a 5% loss in productivity, according to a report from the Society for Human Resources Management (SHRM).1 But presenteeism, where a worker is present but less productive due to personal or family concerns, can cost multiples more: over 18%. For depression, absenteeism costs about a 2.6% loss in productivity; presenteeism costs 14.5%. Other mental health issues affecting the workforce and the workplace include anxiety related to COVID-19, loneliness due to isolation and mourning the loss of loved ones.2

However, understanding symptoms of poor productivity does not provide a clear path to solutions. Often, many factors are at play, muddling the root cause. For example, people with physical health conditions— such as heart disease, diabetes and HIV/AIDS—can have serious mental health conditions that affect many aspects of their jobs.3 Similarly, social isolation, stress and other mental health conditions can manifest as physical symptoms: fatigue, headache, neck or back pain, and an increase or decrease in appetite.4

No matter what the root cause or how health problems manifest, these issues have a business cost. But effective health programs can turn some of the red ink to black. Every US dollar applied to mental wellbeing programs for depression and anxiety, for example, results in a return on investment (ROI) of 4 US dollars, due to better health and productivity.

To achieve returns like this or better, business leaders need a roadmap to better understand the problem and identify where and how they can help workers improve their health.

The 3,000-foot view: A look at more types of data

To further analyze health trends, public and industry-specific data can give your organization more context for and detail of the high-level view. For example, related to the COVID-19 pandemic, researchers warn of a coming wave of long-COVID syndromes involving the heart, lung and nervous system for certain populations: in part from new diagnoses directly linked to COVID-19 and in part from care deferred for months or years.5,6,7

For similar reasons, researchers also forecast a rise in mental health issues, like social isolation, related to COVID-19. Worldwide, the pandemic both disrupted mental health care and led directly to more people having symptoms. Even among previously outgoing or optimistic people, depression, isolation and similar conditions increased during the pandemic.8

In the United Kingdom before the pandemic, 10% of people reported symptoms of depression. That rose to 20% during the pandemic.9 In the US, three times more people reported signs of depression in 2020 compared to pre-pandemic years.10 For those who worked remotely, isolation became—and continues—to affect mental health. Many workers had—and continue to have—financial stress.

These broad datasets for workplace wellbeing are informative. But other types of data can offer insights that might be more relevant to your workforce. For example, how do younger and older people vary in the way they experienced the pandemic? In late 2021, 1 in 10 people under age 35 said they had “always” felt lonely in the prior 30 days. For people 65 and older, only 1 or 2 in 100 respondents reported the same, according to the IBM® Watson Health® PULSE® Health Poll.11 Financial security, including income and savings, also impacts workers’ mental health.12

These few examples demonstrate what research confirms: a mental health condition like depression, for example, is a very specific health issue that requires very specific interventions.13 In order to help employees, an organization needs to collect the right data, using the right tools, at the right time and from the right people. However, getting such data can be resource intensive, researchers say.14

Where can you begin in supporting your workforce and improving your bottom line? Other layers of data provide insight.

Feet on the ground: How data specific to the health of your population can improve the health of your business

Business leaders need an unbiased view of their workers’ health status to help them first pinpoint symptoms and then the underlying causes. To help with this, analysts look at two types of data: subjective and objective. Subjective data can reveal trending health issues and help measure results from a broader perspective. This type of data often comes from multiple stakeholders (such as leaders, employees and family members) and from a variety of documentation (self-reported polls and surveys to measure social wellbeing, physical wellbeing, job satisfaction and work-life-balance; interviews; and observations). Objective data (medical test results, health insurance claims, absentee rates, site-specific figures) can help leadership identify areas of focus as well as help them measure the success of interventions.

Below, read how three large companies used data to improve workplace health in ways that impacted their business.

Mental health disorders topped all other chronic health conditions at one large organization. Data pointed to cost-effective solutions to help workers, and the company.

Improving mental health makes good business sense

Using a variety of data sources, a 12-campus US hospital system discovered that mental health was at the top of all chronic conditions for their workforce, even higher than high blood pressure or diabetes. As reported by Healthcare IT News,15 a subjective survey found that over half of the people in their wellness program “sometimes or often” had feelings of anxiety or stress. Health insurance records showed that mental health care for about 2,300 of their plan members totaled over USD 2.2 million in one year. And anti-depressant medicines were among the top 10 prescriptions for their workers and dependents. Altogether, these numbers got leadership’s attention.

After evaluating options, the system decided on a wellness initiative that met both medical treatment and financial goals. They offered workers an online program instead of more costly face-to-face mental health care. At the end of a year, analysis confirmed success:

  • Surveys showed improvements for 7 of 10 workers who had “moderately severe depression” and for 6 of 10 who had “severe anxiety.”
  • The system earned a return on investment of 17 USD for every 1 USD spent on the program. This was well above findings of other surveys, which report that every 1 USD applied to better care for depression and anxiety results in a 4 USD return on investment, in better health and productivity.16

Relieving financial stressors helps improve productivity

High level research finds that financial stress can impact worker productivity.17 A global financial services company, Prudential, wanted to know if this were true for their workforce. With an analytics team from Watson Health, they created custom risk profiles for specific business groups. And they tracked key measures over time via employee opinion surveys and health risk assessments, using our Health Insights® solution and analysts.

The team of analysts helped them evaluate population health risks by connecting the organization’s data to the extensive Health Insights data warehouse. Analysis showed that among their workers, higher financial stress was linked to:

  • Higher absenteeism (two additional days per employee)
  • Lower productivity
  • Greater incidence of short-term disability

With this information, Prudential had the data to help them create actionable interventions. They offered employees a variety of support, including additional benefits, and even created a task force dedicated to examining financial health risk.

Read the Prudential Financial case study.

Honing in on interventions, with feet on the ground

Another large company consulted with Watson Health to examine how the pandemic was affecting their workforce and their families. Health Insights analysts found that, between 2018 (pre-pandemic) and 2020 (pandemic), trends among their workforce included:

  • Anxiety overall increased 35%.
  • Depression overall increased 29%.
  • Substance abuse decreased. But there was an increase of almost one-quarter for people needing in-hospital care related to the condition.
  • Spouses were about 40% more likely than workers to have substance abuse issues.

With their “feet on the ground,” analysts offered leaders actionable data. For example, the data revealed the locations—down to specific work areas or departments—where their organization’s employees had the highest incidences of anxiety and depression. Data also revealed four specific US states where workers had the highest prevalence of substance abuse, and four different states where the need for in-hospital care for substance abuse among workers was highest.

With such a rich level of timely information, leaders could focus their efforts where they would have the best impact for their workforce.

Starting again: Begin at 10,000 feet

In summary, look at three different levels of data:

  • At the 10,000-foot level, population health data offers insights into the current and growing number of people who have health challenges. It also reveals what those challenges are. Allow this high-level data to illuminate the focus areas that can make the most impact to improve mental and other high-priority health issues.
  • At the 3,000-foot, organizational level: Analysis of objective and subjective data gives important snapshots in time. It’s useful as a benchmark and as a way-finder to help monitor and improve the workers’ health landscape. This analysis should include populations that might be underserved. It should also include a review of workplace wellness, intervention and prevention programs that have proven to work in other organizations.
  • At the feet-on-the ground level, assess the health benefits and programs you’ve already made available to workers and their dependents. How is employee engagement? Are they aware of the programs? Are they using them? Gather data from workers and their dependents about their concerns, barriers to care, and awareness of specific resources available to them.
  • As you narrow in on the best wellbeing initiatives, consult experienced analysts from a solution such as Watson Health’s Health Insights to develop “success metrics.” These could include retention, worker satisfaction and a variety of other objective and subjective data.
  • Collect data pre- and post-intervention to ensure you’re using all your resources in the best way. Monitor employee use, results and opinions. Review effectiveness of providers and programs.

Note that, without strong C-Suite support for workplace wellbeing initiatives targeted to help employees, success in sustaining them is very challenging. We recommend giving leaders key metrics throughout the process, so they can objectively evaluate each intervention and understand which adjustments that can improve results.

For your company in general, for your various locations and for individual workers, what data are you using to understand worker challenges and the impact on your business? With the right analysis and application, you can prevent smoldering embers from becoming a spreading fire. You can create a new health landscape that supports growth for your people and your business.

Learn more about healthcare analytics

  1. Chenoweth, David. Promoting employee well-being: Wellness strategies to improve health, performance and the bottom line. SHRM Foundation’s Effective Practice Guidelines Series. (PDF, 4,2 MB) Accessed 18 Apr 2022
  2. Mental health matters. The Lancet Global Health. November 2020 Accessed 18 April 2022.
  3. Elsevier. “Burden of physical health conditions linked to increased risk of suicide: Chronic illness, even in patients with no record of mental health problems, raises suicide risk substantially.” ScienceDaily. 12 June 2017.  Accessed 18 April 2022.
  4. Trivedi, Madhukar H. “The link between depression and physical symptoms.” Primary care companion to the Journal of clinical psychiatry vol. 6,Suppl 1 (2004): 12-6. Accessed 18 April 2022.
  5. Solomon MD, et al. “The Covid-19 Pandemic and the Incidence of Acute Myocardial Infarction”, N Engl J Med. 2020 Aug 13;383(7):691-693. doi: 10.1056/NEJMc2015630. Epub 2020 May 19. PMID: 32427432.
  6. Yasmin F, et al. Exploring the impact of the COVID-19 pandemic on provision of cardiology services: a scoping review. Rev Cardiovasc Med. 2021 Mar 30;22(1):83-95. doi: 10.31083/j.rcm.2021.01.241. PMID: 33792250.
  7. Centers for Medicaid and Medicare Services. MEDPAR Limited Data Set (LDS) – Hospital (National). Order/LimitedDataSets/MEDPARLDSHospitalNational Accessed 2021
  8. Thapa, B., Torres, I., Koya, S.F. et al. Use of data to understand the social determinants of depression in two middle‐income countries: the 3‐D Commission. J Urban Health 98, 41–50 (2021). Accessed 18 Apr 2022.
  9. Schraer R. Depression doubles during coronavirus pandemic. British Broadcasting Corporation (BBC). Published 2020.
  10. Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, Galea S. Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Netw Open. 2020;3(9) Accessed 18 Apr 2022.
  11. IBM PULSE(r) Healthcare survey, November/December 2021
  12. Sturgeon, John A et al. “The Psychosocial Context of Financial Stress: Implications for Inflammation and Psychological Health.” Psychosomatic medicine vol. 78,2 (2016): 134-43. doi:10.1097/PSY.0000000000000276
  13. Thapa, B., Torres, I., Koya, S.F. et al. Ibid.
  14. Ibid.
  15. Siwicki, B. St. Luke’s reduces employee burnout and mental health costs with digital health tool. 8 Dec 2020.  Accessed 18 Apr 2022
  16. Mental health matters. The Lancet. Ibid.
  17. Sturgeon, John A et al. Ibid.