I work in population health management, which involves a lot of healthcare data analysis and reviews of clinical guidelines. My company analyzes risk measures and quality of care being received by a patient and by a client’s total population at large. We just do the data, so we don’t have any pressure to make numbers lower or higher for certain measures.
Wellness fairs have a lot of problems associated, including dispensing outdated or invalid clinical advice, using outdated guidelines, not providing context for tests taken (such as the blood pressure example, above).
But the problem comes with the wellness programs, not necessarily the fairs. Because the fair is the *first *step.
There is pressure on employees to “get their numbers down”, which does lead to additional visits and tests and medication. Yes, this is potentially beneficial to the employee and a long-term savings (though generally after the employee has retired), but it will not be a short-term savings, and companies must understand that. (Too many do not, BTW, based on client questions that I get.)
Wellness programs also do a good deal of cough creative accounting of the numbers. For example, the state of Nebraska claimed a few years ago that its workplace wellness program saved over 500 lives from cancer…when the patients did not have cancer at all, only benign polyps of the colon (which are common among folks in middle and older years).
Al Lewis (one of the originators of the idea of workplace wellness, now a critic at how it’s being carried out) pointed out in one of his books that Nebraska claimed $4.2 million in savings even though only 186 people’s risk declined, and claimed a 3% reduction in use of chronic disease medications even though they diagnosed an extra 40% of the population with a chronic disease needing medication.
This is only one example out of dozens that I can think of off the top of my head. (But it’s late, and I do not want to bore the entire SDMB to death.)
It’s possible that you don’t see it in the IT side of things, but I do know how data is repackaged and massaged before it’s presented to the clients to “prove” savings.