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Do companies believe that wellness programs are an attractive employee benefit? Do businesses think that Corporate Wellness Programs reduce absenteeism, increase productivity, and otherwise improve employee health? Or, is there another deeper, underlying reason why companies are continuing to invest in corporate wellness programs, despite increasing difficult economic times and massive employee layoffs?
While improving employee health is of course a major concern for all businesses around the globe, perhaps the greatest motivator for companies large and small to invest in employee wellness programs is to decrease corporate health care expenses.
There are many ways that wellness companies are attempting to measure and monitor the financial efficacy of Employee wellness programs. Some of these tactics include:
• Comparing corporate data to national averages
• Using ROI calculators to predict what savings should be
• Showing soft data such as participation levels and aggregate survey trends
While these methods are industry standard and may have considerable research behind them, often times customers are left asking the questions: "So did we actually save money?" and if so "Where is it?"
In the medical field, doctors have always focused on proper diagnosis and measurable results. Doctors then bill patients for specific procedures and treatments based off of the diagnosis. This is the same approach that must be taken for all employee populations when it comes to corporate wellness and health risk management.
Wellness companies should first look at the actual medical claims data including ICD-9 and CPT-4 codes in order to properly diagnose an employee population and then seek to implement specific programs and interventions that in turn change the population's health status and reduce the total medical claims expenditure.
This philosophy has led us to hold our company, Kersh Risk Management, to a new standard of practicing corporate wellness. You cannot change what you cannot monitor. And you cannot monitor what you do not measure.
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