For proactive programs, one of the most potent sources of ambiguity is how the health of the member population will change over time.
Without credible optics on future costs and conditions of a population, proactive wellbeing programs will certainly be appropriate for some members, but just as certainly not for others.
Being able to see, in advance, who needs what program, allows proactive programs to be more targeted, so that a higher percentage of their members receive programs specific for their needs.
Strong predictive analytical systems can show how a population is trending with regard to healthcare utilization. Projections of upcoming costs helps organizations by anticipating costs without being blindsided by them. Also, the predictive capacity allows them to tailor communications, incentives, and the thoughtful selection of programs for exactly the targeted outreach needed.
But the predictive analytics system must also report trends down to the member level. Under- standing, for each individual, the nature and degree of healthcare issues and costs—both actual and forecast—is critical, prompting the organization to target the main issues in advance of their occurrence. In the absence of this specific information on each individual, the specific proactive programs chosen are simply the result of guesswork. Applying a predictive component can improve confidence that the program can reach the right person with the right program.
Link to Full Article in the Journal of Compensation and Benefits:
