According to Kaiser Health News the Institute of Medicine (IOM) recently released a report that contradicts the long-standing claims of the Dartmouth Health Atlas that variations in Medicare spending are attributable mostly to the greed of doctors.
The context of the report was to inform policymakers on the wisdom (or lack thereof) of proposals to pay providers more in low-cost areas and pay less in high-cost areas. The $8.5 million report found that local variations in Medicare spending do not correlate with variations in non-Medicare spending.
This finding is unsurprising. In fact, NCPA Scholars Andrew Rettenmaier and Thomas Savings came to precisely the same conclusion in a report published four years ago (surely for a whole lot less money).
The NCPA study found, for instance, that while “In 2004, the last year in the data we use, average Medicare spending in Louisiana (the most expensive state for Medicare) was $8,659 while spending in South Dakota (the least expensive state) was $5,640, almost 35 percent less.” However, total per capita spending in the two states paints an entirely different picture. Here South Dakota was more expensive ($5,327) than Louisiana ($5,040). The study went on to look at state-by-state variations in Medicaid, and private insurance as well as Medicare, and what factors might influence these differences.
IOM also found that in Medicare the variation in costs is mostly “due to spending in post-acute services such as nursing facilities, home health care and long-term-care hospitals,” while “In the commercial market, by contrast, higher prices negotiated by hospitals, doctors and other medical providers were the key factor in regional variations.”
This finding completely undermines Dartmouth’s contention that it is greedy doctors who cause Medicare variations. Physicians don’t profit from these post-acute care services.
But the article says the IOM report –
…affirmed the general subject of Dartmouth’s analysis, concluding that “after accounting for differences in the age, sex and health status of beneficiaries, geographic variation in spending in both Medicare and commercial insurance is not further explained by other beneficiary demographic factors, insurance plan factors, or market-level characteristics. In fact, after controlling for all factors measurable within the data used for this analysis, a large amount of variation remains unexplained.”
So, IOM is not dismissing Dartmouth’s analysis and remains puzzled by the cause of the variations. After all, they have “accounted for differences in age, sex and health status,” what more could you possibly want to know about these patients?
Good grief! Are those the only meaningful variations between patients ― age, sex, and health status? Is it remotely possible that there might be other differences between groups of patients that would cause some to require more post-acute services than others? Of course there are, and you would think researchers getting paid $8.5 million to do a study would be motivated to look for it.
The NCPA study adds race, income, and education in its analysis, and while these are important contributors to health behavior, it still doesn’t go far enough. There are many, many more factors that could effect whether a patient needs post-acute institutional care, including –
- · Marriage status. Does the patient have a spouse at home to help provide care?
- · Adult children nearby. Children can also help with care.
- · Home ownership. Patients are more likely to return to a home they own and have lived in for a long time.
- · Religious affiliation. Belonging to a church helps provide a support network of people who might bring cooked meals, wash dishes and the like.
- · Civic involvement. Like the church, being involved in one’s community suggests an active support network.
These are all factors that directly help a patient return home after a hospitalization. The absence of these factors would require the need for professional assistance, such as home health services.
In an earlier post on this blog I called out Dartmouth for ignoring factors such as these in a study they did puzzling over why patients in Ogden, Utah are more likely to die at home than patients in New York City.
I have to conclude that health care researchers really don’t care very much about people. They are much more comfortable doing a simplistic regression analysis than actually looking at the human dimensions of health care. It makes me cringe that such people will influence the future of our health care system.