Leveraging data analytics to control health plan and pharmacy spending

Faced with perpetually rising health care and pharmacy costs, challenges in retaining and attracting employees, and now a surge in inflation, today’s business owners, benefits advisors and HR managers find themselves operating with little margin for error. These challenges create a difficult dynamic: To attract top talent, businesses must offer a total rewards program that is demonstrably valuable to employees, and to keep businesses running, they must design and implement these programs in a manner that is purposeful, efficient and effective.

Data analytics provides the needed insight into benefits performance plan metrics, enabling empowered decision making to reduce pharmacy and medical costs while also enhancing the health and wellness of the workforce. Through analytics, businesses can not only predict the future health and wellness needs of their workforce but also develop timely interventions to maximize savings and health outcomes.

The population health approach

To truly move the needle on benefits spend, businesses and their advisors need to adopt a population health approach that addresses cost, impact and experience of care. Through data-driven risk-stratification, businesses can identify and group employees based on common traits, including medical history, vital statistics and the potential for developing chronic conditions, and then develop meaningful health and wellness programs to target the needs of these various groups. Over time, employers will not only save money on health care costs, but also benefit from an engaged workforce that’s more productive and likely to stay with the organization.

In addition to improving the health of populations within the workforce, analytics help employers and benefits advisors determine how best to allocate their health care spend. According to data from Vital Incite, waste ¾ use of services that do not advance the health of the individual ¾ accounts for least 35% of medical plan spending in the U.S. A deep dive into claims data can reveal the sources of waste, as well as identify ways to redirect the spending to achieve better health and financial outcomes. The following examples reveal how analytics can identify the needs of the employee population, access current spending and the efficacy of care, and pinpoint solutions to improve access to services that ultimately enhance health outcomes.

Empowered decision making

Many businesses are experiencing higher spending on cancer care even though cancer rates have not increased among their employee population. Common reasons for this uptick in spending include an increase in use of more expensive medications and later-stage diagnoses. Businesses can counter these cost drivers by promoting and incentivizing cancer screenings, and by providing genetic testing to determine the efficacy of the high-cost treatment. In some instances, testing may direct care toward a treatment plan that is both less expensive and a better, more effective option for the patient.

Many businesses are also seeing an increase in spending on mental health services. Since the start of the COVID-19 pandemic, there’s been a sharp increase in mental health diagnosis of anxiety and major depression leading to an increase in monthly plan spend, Vital Incite data indicates. Incidence rates are climbing for all plan members, with the highest increases seen among dependents. To support employees and their dependents with emerging mental health needs, businesses should analyze their current mental health service offerings to determine if they are reaching the right individuals and then assess how best to engage these individuals in their care. Identifying and providing solutions not only for children but which parents can utilize to learn how to support their children dealing with mental health concerns, will not only improve outcomes but help improve employee presenteeism.

Gain actionable intelligence

Data analytics provides actionable intelligence so employers and advisors can make informed decisions about the health and wellness programs they offer employees. Access to comprehensive medical and pharmacy claims data can provide insight into compliance of care and direction of care but adding values such as biometric data allows employers to understand if strategies are improving chronic condition control.  Data such as A1c values, allows for an objective view to determine if strategies for diabetes for instance are not only engaging the correct members, but actually improving their disease control.  With data in hand, companies can quickly determine if strategies, such as formulary expansion, are improving risk control and can pivot strategies quickly to reduce plan spend waste.

It’s important to remember there is no one-size-fits-all approach. Through population health management, employers can leverage data to develop and target the populations with the greatest need, and align health and wellness offerings to enhance the experience of care through greater coordination and communication. Using comprehensive population health data, the employer can make strategic decisions based on facts instead of being influenced by the “new shiny objects” being sold.  They are able to run their health plans like they do the rest of their business

A healthy workforce is vital to an organization’s bottom line. Time lost to employee illness not only hurts productivity and drives up payroll costs but also increases how much an organization spends on its health plan and prescription drugs. Businesses that collect comprehensive data which leverages risk indexes and use analytics to determine which treatments and preventative measures are both needed and efficient will deliver the best outcomes and be able to achieve sustainable results. A healthier, engaged workforce is a critical effectiveness factor that will set businesses on the path to success.

Mary Delaney, MS PT, CWP, is managing partner at Vital Incite, an Alera Group company.