The opinions expressed herein are the writer's and do not necessarily reflect the opinions of Moreton & Co.
A curious thing happened during a recent renewal. The policy being renewed was a disability benefit based on covered payroll. After marketing the policy to several carriers, my team began the usual process of analysis using spreadsheets to compare proposals. When we compared current plan costs to the proposals, it became clear that the proposals were rated differently than the incumbent's renewal. Since apples don't compare fairly with oranges, we investigated to find the cause of the difference. Eventually the discrepancy was discovered: the census of "actively at work employees" erroneously contained previously terminated employees.
This inadvertent inclusion of terminated employees for coverage impacted cost for the renewing disability policy for a few reasons. Overall demographics (age, gender, job descriptions, etc.) of the group with the terminated employees compared to the same statistics after removing the terminated employees made the group look entirely different. One key difference was the additional payroll. The incumbent carrier rated the case based on a census it had on file whereas the proposing carriers rated the case based on the incorrect census obtained from the client. Once the census was corrected, the policy was properly re-marketed, re-rated, and eventually renewed.
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The lesson of this story is "check the census." Brokers and consultants have an obligation to ensure all parties are treated fairly and that the client is represented accurately. Checking the census before sending it along during a marketing process can save time and avoid errors down the road. Some things to remember are:
- Overall head count: Do you have everyone you expect on this census?
- Does payroll make sense? How does total payroll compare to the incumbent renewal?
- What is the average age of the group?
- What is the ratio of females to males?
After this experience, a thought occurred to me; what can be learned by checking the United States census? What is the affect of our country's demographics on national health care cost? The answer to these questions was well worth the effort and research.
The following exhibit compares relative health care costs by age and gender. The graph is fairly intuitive in that we are well acquainted with the costs of aging. We become more fragile, more susceptible to illness and accident as we age. Our bodies just plain wear out. Maintaining them becomes a costly burden over time.
Our review of US Census data included median age and total population count from 1960 through 2008. All statistics and data were obtained from the Census Bureau's website. What's most interesting is how the Census data compares with the graph above over time. In 1960, just a few years before Medicare was introduced, the American population was vastly different than it is now. Here is what the chart looks like with 1960 census information included:
Here is what the chart looks like with 1960 census information included: 
Now compare 1960 to 2008 census figures against the same backdrop. 
The difference of 48 years is significant. The median age for those living in the United States went from 29.6 to 36.8 years – an increase of 24 percent! The green shaded areas highlight the cost curve for ages over 50. This is the "point of no return" for health care costs. From age 50 on, both male and female health care costs are above average (e.g., above 1.0). In 1960, this was 4.3 million Americans or roughly 23 percent of the population. In 2008, this same cohort included 87.6 million people, or 29 percent of the total population. By any standard, the census from 1960 compared to the census from 2008 is nowhere near the same.
By looking at this data, one comes to a few conclusions readily. First, is it any wonder why health care costs are rising so rapidly? Does it do any good to transfer wealth from one class to another in order to create "affordable health care"? Clearly, we need to let some air out of the balloon and simply reduce what it costs to pay the health care bills for all, long-term.
Yes, this author is aware of the simplicity of this analysis. We didn't account for improvements in technology or growth in GDP over time. But relative costs by age and gender are relatively constant and we didn't factor in the costs associated with obesity and other recent adverse health trends. Overall, the conclusion of increased costs associated with an aging population is sound. By focusing on the causes of health care costs, rather than the financing of health care, we focus on the real problem. When we focus on the real problem, we begin solving it.
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