Forecasting health care expenses

My friend works under the trademark name “The retirement quarterback”. He reminds us that he can plan out your retirement finances with perfect precision if you can give him one peice of critical information: the month and year of your death. what he does instead is use a maximum lifespan probability in his financial planning calculation that ignores the relatively small risk of living beyond that estimate.

The same concept applies to health care planning. If we can forecast our future health care expenses then we can plan out insurance coverage perfectly. Without that information, we are taking some unnecessary risk or overspending on insurance.

Most of us have under $1,000 in annual medical expenses. A small portion have expenses that run over $100,000. How much should we spend on insurance? The only accurate answer relies on information that we do not have available.

There is a growing belief among health insurance professionals I know that that small business health insurance works best to insure expenses perhaps up to $100,000. Expenses above that are best paid through some government-coordinated plan (and distributed as a social cost) rather being forced as a premium rate cost on the small business employer. If we adapt this paradigm that eliminates outlier medical costs then it becomes much easier to forecast the actuarial medical costs of the group. That would be a major cost-reducer on commercial medical insurance.

One way or another, the only way to accurately estimate medical costs is to isolate and remove the small chance of catastrophic upper outlier costs.

Understanding this concept is essential to maximizing the financial planning opportunities that will soon be made available under the Trump administration.

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