Form to compute the financial losses due to a certain medical condition in a population
This form calculates the estimated productivity losses in a population (e.g., a country, or an organization) due to various medical conditions (e.g., diabetes, anxiety disorders, burnout, etcetera).
It generates a number that represents "annual costs", that is, the annual financial losses incurred by that population due to that medical condition.
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Enter the appropriate numbers in the fields below
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Population size:
Incidence of the condition:
Duration of the episode:
Productivity loss due to that medical condition:
NOTE: enter only the number, not the actual currency you want to compute this in. The currency is just something for you to keep in mind when you interpret the results.
Gross annual salary:
COSTS =
LEGEND
COSTS = the financial losses (annual or total, depending on the duration of the episode you entered) incurred by that entity (country / organization) due to the existence of that medical condition in that population.
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EXAMPLE
Let's talk about a concrete example. Let's say that we have a company employing 10000 people, with a gross average salary of 100000 $/year. Let's say that, based on a prior organizational assessment, we know that the (point) prevalence of depression in this organization is 12% (i.e., 0.12). We also know from literature that the average duration of a depressive episode is 8 months (i.e., 0.66 years). Furthermore, we know from the scientific literature that the average productivity loss for depression is approximately 20% (i.e., 0.20). With these numbers, we can now calculate the financial losses due to depression in this organization.
The results for this hypothetical organization are:
ANNUAL COSTS OF DEPRESSION IN THIS POPULATION = 15840000 dollars per year
This means that, each year, this organization loses approximately 15 million dollars due to the existence of this medical condition in its employees. Other medical conditions in this population will increase these costs further. This number also suggests that intervention programs for depression in this population will likely lead to substantial savings and profit increases.
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