Three out of five U.S. employers use health screenings and risk assessments to screen for expensive chronic conditions, such as cancer.¹ Yet, 79 percent of large U.S. employers and 44 percent of mid-sized employers do not measure the effectiveness of employee wellness programs, including preventive screenings.²

With the cost of employee health benefits expected to rise 5 percent in 2019, it is critical that employers and health plans develop a data-centric approach to measuring the effectiveness of preventive screenings.³

Analytics inform a high-value approach for health benefits design by providing employers and health plans insights into opportunities for targeted interventions that reduce costs and improve health. Data analytics also help avoid “one-size-fits-most” solutions that may not be a good fi t given member and provider characteristics.

Increasingly, analytics are used to track outcomes of preventive care. For example, a recent study examined the impact of preventive cervical cancer screenings and showed these eff orts resulted in substantially lower deaths and increased lifespans.⁴

Analytics can also help employers and health plans prioritize preventive cancer screening offerings. Criteria might include:

• Risk factors such as high proportions of members who are overweight, have high cholesterol or high blood sugar levels, or smoke.
• Regional health trends that may point to potential socioeconomic-based risks for members, like higher-than-average prevalence rates of lung cancer or heart disease. For example, 6.2 percent of Ohio’s population has heart disease, even as rates across the nation dropped.⁵
• Evidence of possible “hot spots” within a plan sponsor membership. For instance, analytics show certain locations where employers and health plans should focus eff orts on encouraging preventative cancer screenings (member education, onsite clinic involvement, etc.).

The analysis of claims data – as well as socioeconomic data that might be available from state and regional health organizations – can provide powerful insights in developing a high-value approach to preventative cancer screening health benefits for members that improves outcomes.

The results showcase the power of using data to measure the effectiveness of preventive screenings. When employers and health plans leverage claims and socioeconomic data analysis to refine their approach to benefits design, they are more empowered to reduce costs and improve outcomes.

1. “Top 10 Health Conditions Costing Employers the Most,” Employee Benefit News, Feb. 9, 2018,https://www.benefitnews.com/slideshow/top-10-healthconditions-costing-employers-the-most
2. Desai, P., “Why Health Screening Programs Fail and What Employers Can Do About It,” Corporate Wellness Magazine, https://www.corporatewellnessmagazine.com/worksite-wellness/health-screening-programs-fail/
3. https://www.shrm.org/resourcesandtools/hr-topics/benefits/pages/employers-adjust-health-benefits-for-2019.aspx
4. Kim, J.J., Burger, E.A., Regan, C., et al., “Screening for Cervical Cancer in Primary Care: A Decision Analysis for the U.S. Preventive Services Task Force,” JAMA, Aug. 21, 2018, https://jamanetwork.com/journals/jama/fullarticle/2697702
5. “Heart Disease Hotspots: 14 States with Highest Rates,” CBS News, https://www.cbsnews.com/pictures/heart-disease-hotspots-14-states-with-highest-rates/
6. HDMS proprietary data