Even in exceptional circumstances, past behavior is always a dependable indicator of future behavior. (Image: Shutterstock)

After months of grappling with COVID-19, most businesses recognize that the pandemic is not a one-and-done phenomenon. They're focused on employees' health and safety while wondering: What will tomorrow's economic and business landscapes look like?

Significant change is all but guaranteed; "0,0" on the proverbial cartesian frame is shifting as the world adapts. With few precedents for this unusual situation, employers have to redefine what "normal" means for their workforces moving forward.

Related: Return to work: Mitigating the risk of COVID-19 in the workplace

Despite the uncertainty, data and analytics remain a familiar and reliable ally. Even in exceptional circumstances, past behavior is always a dependable indicator of future behavior. The same data that offered benefits insights before COVID-19 can do so now—it just needs to be viewed through a different lens.

Since emerging data is so crucial to decision-making, benefits brokers and employers may find that a phased analytics approach provides the most advantages:

• Immediate phase—quantify population vulnerabilities for strategic planning and resource management.
• Short-term phase—reevaluate the current benefit year, track wellness and begin cost modeling for 2021.
• New normal phase—accelerate health and wellness and invest in prevention and contingency planning.

Immediate phase analysis: Evaluate "back to work" risk

It's a complicated time right now. Many U.S. businesses feel they've already weathered the immediate COVID-19 crisis. Yet there are significant risks transitioning back to work and balancing employee health and safety against difficult economic pressures. Re-opening operations too soon could create greater long-term financial consequences if spikes in illness force secondary shutdowns.

That is why it's still crucial for businesses to analyze their employees' geographic distribution and correlating COVID-19 infection rates. Data from current epicenters remains valuable. However, data that reveals emerging hot spots and trends also should drive policy decisions—including rates of asymptomatic infection, and the capacity to provide testing, personal protective equipment (PPE) and other resources to ensure people's safety.

Locations where significant infection rates are either non-existent or declining would be candidates for the earliest re-openings. Businesses also can assess employee health risk as defined by the Centers for Disease Control and Prevention (CDC) versus job type, business function or critical/non-critical classifications. Employees at least risk—e.g. people under 60 with no chronic conditions who sheltered-in-place or quarantined—could be prioritized for return. Some companies, in fact, may allow least-risk employees to volunteer for early return to onsite jobs.

Businesses should account for the resources and time needed for required screening procedures before employees' start dates. Asking a few other questions may also help manage back-to-work strategies:

• Is your business likely to experience pent-up demand for products and services and/or a peak season that drives the need for unusually high activity? If so, how do these areas of increase map against your areas of medical, financial and personnel risk?
• Have any segments of the business experienced steady or increased productivity while working remotely? Consider bringing those employees back onsite later.

Short-term phase analysis: Model costs

It's a gross understatement to say that predicting direct and indirect health care costs related to COVID-19 has challenged businesses. How much will coronavirus testing and treatment ultimately cost? How will the pandemic alter the bottom line?

It's possible to model cost and/or productivity changes associated with COVID-19 using robust, well-documented impact planning models that are flexible enough to evolve with the ever-changing data.

For example, look at historical data for conditions with biological similarities to COVID-19 (i.e. other upper respiratory viruses that spread in similar ways, such as influenza.) Models are widely available that use community attack, hospitalization and fatality rates for the flu, and apply correction factors for COVID-19 based on CDC, World Health Organization (WHO) and other guidelines. Such predictive models can help quantify the:

• Number of employees who could be infected with COVID-19
• Projected number of employee hospitalizations
• Potential requirements for intensive care services

Using historical costs incurred due to flu and other respiratory-related hospitalizations, we can project potential hospitalization costs due to COVID-19. Adjusting for over- or under-reporting and taking disease mitigation policies into account could provide a projected cost range. Likewise, this data can be layered with other inputs to reveal repercussions on benefit utilization such as absenteeism, short-term disability and life insurance payments.

The direct cost of infection (i.e. testing and treatment) is only one aspect of the overall cost burden. Closer scrutiny of broader health care policies could provide a more complete view of change moving forward. One example: telehealth—or virtual doctors' visits.

As we know, most physicians have switched to video visits to ensure care continuity for their patients, often with no cost-sharing. Virtual visits will likely remain popular long after COVID-19, even with the expected reinstatement of cost-sharing. So, businesses may want to explore the potential health and productivity benefits of telehealth screenings.

Reducing infection rates is one idea behind such screenings. Employees worried they might have the flu or a stomach bug, for instance, could use telehealth screenings to help decide whether to go to the office or work from home. Parents with young children could conveniently consult virtually with their pediatrician for simple common ailments, to reduce exposure to other sick children.

Despite little telehealth history, businesses can use data from the pandemic shutdown months to gauge telehealth adoption levels. Diagnosis and procedure code data helps identify the reasons people are using telehealth now. Modeling a 25-30% increase in telehealth adoption for the identified diagnoses and procedures when physician offices operate at full capacity, this helps inform future direction, evaluation of technology related investments, as well as savings if/when cost-sharing is reinstated.

Businesses will need to balance projected costs against employee productivity and retention needs. To accommodate continuing disruptions, it may be worth extending concessions made during the pandemic—e.g. continuing to offer additional childcare benefits while summer camps, daycares and schools remain closed or on altered schedules.

Studying workflows established during the COVID-19 shutdowns—and their impact on employee productivity and satisfaction—can guide financial policies. Flexible schedules and work-from-home options are an example. Although they might require some technology infrastructure investments, companies may choose to permanently transition parts of their workforce to remote work to cut down on facility and overhead costs, as well as enhance employee productivity, satisfaction and retention.

As the nation starts "going back to work," health care utilization rates that declined during the shutdowns will gradually rise, impacting long-term costs. Data models can easily help project trends—such as preventive care, emergency care and elective procedures—to inform 2021 benefits strategies.

"New normal" phase analysis: Promote wellness

Moving forward, the best business investments will be direct investments in human capital aka employees. Since health is a product of physical, mental and emotional wellness, a targeted focus on mental and behavioral health benefits should be considered in addition to preventive and wellness programs. Integrating medical and supplemental mental/behavioral health benefits, e.g. employee assistance programs (EAPs), can ensure continuity of care, leading to better health and lower costs over the long haul.

One indicator of COVID-19's effect on people has been a skyrocketing number of antidepressant and anti-anxiety prescriptions. Some experts have even dubbed this "the second pandemic of 2020." When the COVID-19 crisis abates, mental health conditions won't just ebb away. It's imperative for businesses to address employee mental health and productivity if they want to lower long-term costs.

Before the COVID-19 crisis, one national retail business used medical claims data to analyze the prevalence and impact of mental health conditions on the company and its employees. It found that more than 12% of its workforce had a mental health or substance abuse-related diagnosis. These diagnoses were becoming more common, and over three years led to a 7.7% per member per month (PMPM) cost increase. The company also identified correlations between mental health-related claims and employee sick days, performance metrics and staff turnover. Despite rich psychotherapy benefits, awareness and utilization were low. Consequently, the employer improved communication around its mental health benefits to enhance plan engagement and promote a stigma free culture.

This example illustrates that mental health benefit utilization is commonly low because employees may lack awareness of their existence. Hence, frequent communication is key. Businesses with EAPs could work with their vendors to engage all employees proactively, acknowledge the strain of COVID-19 on the individual and families, and extend mental health support if needed.

To balance the bottom line, focus on employee health

COVID-19 is not a one-time event. The infectious nature of the disease will require ongoing data analysis to ensure agile staffing and benefits models. Businesses should be prepared for repeated adaptation.

Just because COVID-19 appeared quickly does not mean change has to occur overnight. Data and analytics can support gradual policy and benefits adaptations. By taking a people-centric and data-driven approach, businesses can ensure employee productivity and engagement remain high—which, over time, can bring better results to the bottom line.

Rani Aravamudhan is senior clinical consultant at HDMS. She is a physician (specialty- General Medicine) with extensive experience in the EMR/EHR and population health industries with a focus on clinical transformation, workflow design and development, value-based care, risk management and clinical quality and performance reporting. Her strong background in clinical medicine and experience in the HIT industry make her successful in navigating payer, provider and technology vendor landscapes.

Read more: 

• Data analytics offers a peek behind the curtain in employee benefits plans
• Thinking about returning to the office? The answer is in your data
• Predictive modeling helps cut through coronavirus confusion